Podcasts about Audacity

This show has been flagged as Clean by the host. 01 Introduction This is a follow up to my 4 part series on simple podcasting. In this episode I will discuss a number of experiments with audio filtering. These experiments were inspired by comments by listeners and by other discussions about audio on HPR. I am not an audio expert, so I am doing this partly in order to learn something, but mainly in order to have a bit of fun. I hope that you find this entertaining as well. In a comment on the first episode a listener mentioned something called Solocast and said that the method bore a resemblance to the method that I was using. Here is his comment -------------------- 02 Comment #3 posted on 2026-04-03 07:49:58 by Reto It reminds me about Solocast Hi Whiskeyjack, I really liked your podcast and the topic. I cannot remember about your last, but the sound quality of this one was good on my mobile speakers :) The concept reminded me about the program from Norrist (another host on HPR), while similar does it have some differences HPR 3496 https://hackerpublicradio.org/eps.php?id=3496 As I am not on the future feed, I look forward to your next episode. Cheers, Reto -------------------- 03 End of comment. I did not recall having heard the episode on Solocast, but this sounded very interesting. Solocast was in HPR episode 3496 and was released by norrist on the 27th of December 2021. I listened to that episode and does indeed use use the same basic concept of recording short segments of audio and combining them later instead of creating one big recording and editing it with an audio editor. 04 The main difference is that the work flow that I described involves a lot of manual steps, while Solocast is a short Python program that automates the entire process of presenting your script, recording the segments, combining the segments, and filtering and normalizing the result. I won't try to describe Solocast in detail, instead I would recommend just listening to HPR episode 3496 to get norrist's explanation directly. -------------------- 05 While I wanted to make sure that I credited norrist with having come up with this concept four years before I did, this won't be the focus of this episode. Instead I will talk about audio filtering and various experiments that I ran on several different methods. 06 While looking at the source code for Solocast I noticed that it used a filtering method that resembled one used by Jivetalk, a podcast production program that caught the attention of one of the HPR community news presenters. This method involves taking a sample of quiet audio where there is no speaking taking place, and then using this as input to a noise reduction filter which is applied to the voice recording. The filter subtracts the quiet sample from the voice audio, which should theoretically remove the ambient noise. 07 I decided to apply this method to a number of different audio test recordings which were recorded under different circumstances using different hardware. In this way I could see if the method worked equally well under all circumstances or if there were some sorts of noise which it was suited to and some sorts that were not. 08 While I was at it, I also picked several other filter methods to see how they worked as well. Potentially, some methods may be better under some conditions while other methods were better suited to others. -------------------- 09 I won't present all of my experiments, as that would be a bit dull to listen to. Instead I will describe each method and then present audio samples which illustrate my conclusions. There are two pieces of audio software involved, both of which were also used in my series on simple podcasting. 10 The first is Sox, spelled s o x , and which is short for Sound Exchange. Sox is a command line program for audio manipulation. Sox is Free Software, released under the GPLv2 or later. The other is FFMPEG, which is also a command line program. FFMPEG is also Free Software, released under the LGPL V 2.1 or later, and GPL v 2 or later. Sox actually uses FFMPEG for certain operations. -------------------- 11 Audio Hardware For recording hardware I used the following. 12 Maxwell Headset The first is a cheap Maxwell headset that has an electrical noise problem. Unfortunately I don't have a model number for this headset. I described this hardware, the noise problems that I had with it, and how I created filters to deal with the noise in my series on simple podcasting. Briefly though, this is a headset that has a build in microphone on a boom which allows the microphone to be positioned close to the mouth. It connects with a USB cable. 13 Borne Earpiece and In-line Microphone This is a set of earplugs that go in your ears and connected by wires and a very small microphone built into a small bulge in the cable. It connects using a 3.5mm jack. The model number seems to be BUD250-BL. 14 XTrike Headset This is a gaming headset similar to the Maxwell headset described above. The model number is GH-510 It uses a USB connection. 15 Yanmai Condenser Microphone This is a microphone that comes with a small tripod stand. The model number is SF-910 It uses a 3.5mm audio jack. -------------------- 16 This is not a review of the hardware. Rather, I was trying to create audio problems so that I could test ways to fix them. Therefore, do not take the above list as a recommendation of what to buy. However, you can see that I am not using any expensive audio hardware. If you want to make an HPR podcast, you do not need professional level hardware. -------------------- 17 Audio Samples The audio samples are as follows 18 Quiet This was recorded in a quiet environment at my desk. This is my normal podcasting environment and represents optimal conditions. The main reason for this method is to see how the various filter methods perform when dealing with the electrical noise from the Maxwell headset. 19 Small fan This is a small USB powered table fan approximately 10 cm in diameter. It was located roughly 40 cm or less to the left of the microphone, although this varies depending on the microphone. 20 Traffic This was along a busy street with traffic noise in the background. -------------------- 21 Filter Methods Sox noisered Filter with Audio Profile This method uses the Sox noisered filter. Here is a brief quote from the Sox documentation on this filter. Quote Reduce noise in the audio signal by profiling and filtering. This effect is moderately effective at removing consistent background noise such as hiss or hum. To use it, first run SoX with the noiseprof effect on a section of audio that ideally would contain silence but in fact contains noise - such sections are typically found at the beginning or the end of a recording. End of quote For these tests I recorded a separate noise profile to go with each test. -------------------- 22 Basic Manual Filter This is a basic high and low pass filter pair based on the work I had done in my previous series on simple podcasting. However, based on the tests that I have done for this episode, I decided to get a bit more aggressive in terms of filtering. I use a high pass filter of 120 Hz, and low pass filter of 8 kHz. The each filter is then applied twice to increase its effect. I also added band reject filters to deal specifically with 50 and 60 Hz line noise. -------------------- 23 Complex Manual Filter This uses the manually constructed filter described in my series on simple podcasting. This uses the basic manual filter plus a series of custom bandreject filters to fix specific noise problems with the Maxwell headset. -------------------- 24 FFMPEG afftdn Filter The documentation describes this as "Denoise audio samples with FFT." -------------------- 25 FFMPEG arnndn Filter The documentation describes this as "Reduce noise from speech using Recurrent Neural Networks." -------------------- 26 FFMPEG agate Filter I will pronounce this as "agate" for convenience. The documentation describes this as "A gate is mainly used to reduce lower parts of a signal. This kind of signal processing reduces disturbing noise between useful signals." -------------------- 27 Method The experimental method used was to take each noise sample and apply the different filter methods to it. Where there are parameters which can be adjusted, a script was used to generate a series of different sample files with different parameter values. Not all possible parameters were experimented with, as the goal is to see which method produces what sorts of results under different circumstances, not to get the best possible result for the samples that I happen to have. The method in each case was as follows 28 Step 1 Convert the audio file to FLAC if it is not already in that format. 29 Step 2 Apply a basic high and low pass filter described previously to each sample. The reason for this basic filtering is that it eliminates at least some undesired noise in a fairly fool proof manner, leaving less for the more advanced filter to deal with. This should allow for a better test of the filter under realistic conditions. 30 Step 3 Apply the noise reduction filter being tested. 31 Step 4 Normalize the filtered sample to 17 LUFS according to the EBU R128 standard. The EBU standard is described in my series on simple podcasting. Normalizing adjusts the audio signal to a desired loudness level. This allows for more more consistent sound levels and allows us to hear the results under realistic conditions. I normalize the audio individually for each sample as different recording hardware requires different amounts of loudness adjustment. This is different from the typical podcast process where normalizing takes place as the very last step in the process, but it was necessary in this case. 32 Step 5 Concatenate selected sample audio files to one another to allow for better review and comparing. -------------------- 33 Results The results are grouped according to the type of noise which is being mitigated. This allows for easier comparison of the effectiveness of each technique under different circumstances. I have only picked a few examples of interest out of the numerous experiments that I conducted. -------------------- 34 Quiet Recording Environment with Maxwell Headset This compares how well the various filtering methods work on the noise induced by the electronics in the Maxwell headset. This electronic noise consisted of a noise spike every 1 kHz. This should be representative of electronic noise caused by problems in recording hardware. 35 Manual Filter The manual filter applied a narrow band reject filter every 1 kHz from 1 kHz to 12 kHz. This completely removed the otherwise audible whine caused by the noise. 36 FFMPEG afftdn This method allows for setting a noise floor and then specifying how much the noise floor should be reduced by. The method is very sensitive to getting the noise floor correct for that recording. Set the floor too low and nothing happens. Set it too high, and some distortion results. However it seemed to be moderately effective, but it would seem to require checking it and possibly adjusting it each time it is used. 37 FFMPEG agate This method allows setting a noise floor and then suppressing all sound which falls below that level. This method is very sensitive to getting the noise floor correct for that recording. If set too low (or quiet), it is ineffective. If set too high (or loud), it distorts words which come after a pause, which would typically be between sentences. 38 When set correctly, it completely removes noise in the silences between sentences. However, the noise is still audible during speech. This is because the noise in this case is a higher frequency than normal speech, and so stands out more. It may not be a significant problem for noise which is closer to the main vocal frequency band. Overall, this method is not suitable for this particular problem. 39 FFMPEG arnndn This method used the standard model. A variety of different noise reduction models are available. I only tested it with one, std.rnnn It does not seem to introduce much distortion in the voice signal even with a high amount of mix parameter. 40 However, it is only slightly effective at removing the whine from the signal, even with a high amount of mix parameter. Overall, this method does not appear to be useful for this sort of noise problem. 41 Sox noisered Filter This was effective in removing noise between words, but noise can be heard while words are being spoken. It was better than agate however. 42 Overall Conclusion for the Maxwell Headset Noise When dealing with narrow noise bands that occur at known frequencies, the manual filter is leagues ahead of any of the other tested alternatives. 43 Sample Audio Here is a sample audio recording showing the best overall results The sample is repeated, first with only basic low and high pass filtering, and then with the manually constructed filtering. In the first sample you should hear a high pitched background whine. In the second sample, the high pitched whine is completely removed. 44 (Audio sample inserted here.) -------------------- 45 Traffic Noise This was recorded using the Borne in-line microphone connected to a mobile phone while walking along beside a busy street. This was in dry cool spring weather, and the road was paved with asphalt. This should be reasonably representative of podcasting while walking outdoors in a noisy environment. 46 Basic Manual Filter This used the basic manual filter with high and low pass filters. This did nothing very useful in this case as the signal was already filtered within those limits by the recording hardware anyway. The low sample rate of 8 kHz in the phone limited the upper frequency to 4 kHz. Recall that the sample rate has to be twice the highest frequency that you want to detect. Overall, this is not suitable for this sort of problem. 47 FFMPEG afftdn With a high noise floor, background noise is reduced, but not eliminated. There was not much distortion in the voice. This is only slightly useful for this sort of problem. 48 FFMPEG agate With a high threshhold, background noise is reduced, but not eliminated. There was some distortion in the voice. The background noise could also be heard when speaking, but because the frequency of the background signal was similar to the louder voice signal, it was not as noticeable as it would have been if the two were very different. This is moderately useful for this sort of problem. It may be more useful in situations where the background noise was not quite as loud. 49 FFMPEG arnndn With high amounts of noise reduction, much of the background noise is suppressed, but there is not a lot of distortion in the voice. The background traffic noise is still present, but is significantly less. This offers only a moderate improvement. 50 Sox noisered Filter With small amounts of noise reduction voice is clear but traffic noise is present as a very significant continuous warbling sound in the background. This is no improvement on the original and in fact could be seen as making it worse. With moderate amounts of noise reduction, traffic noise is mostly gone, but there are still various squeaks present. Voice is noticeably distorted. With large amounts of noise reduction, traffic noise is gone but voice is highly distorted. This is moderately useful for this sort of problem, but requires careful adjustment. 51 FFMPEG arnndn Followed by FFMPEG agate This combined two different filters. First, it used arnndn to suppress the background noise to a lower level without much voice distortion. Then it applied the agate filter to suppress the noise levels between words still further. This used the same amount of mix and threshold as was found to be most effective when each of these filters was used on its own. The background noise is almost completely gone while distortion of the voice signal is low. 52 Overall Conclusion for Traffic Noise The arnndn combined with agate filters was the most successful at suppressing background noise while limiting the amount of voice signal distortion. 53 Sample Audio Here is an audio sample for what I felt to be the best overall results, the arnndn filter combined with the agate filter. First is the original audio with basic filtering. This is followed with the same audio after being passed through the arnndn and agate filters. 54 (Insert arnndn plus agate audio sample here) 55 Another Sample Here is a second audio sample showing the Sox noisered profile based filter. I have included this to show how a profile based filter can make things worse if you are not careful how you use it. This repeats the test audio 4 times. The first is with basic filtering only. The second uses low amounts of noise reduction. The third uses moderate amounts of noise reduction. The fourth uses high amounts of noise reduction. 56 (Insert noisered audio sample here) -------------------- 57 Small Fan Noise with Yanmai Microphone This was recorded using the Yanmai condenser microphone. A small fan was set up behind and to the left of the microphone. This is intended to represent situations where someone may have a fan or air conditioner running in the background due to hot weather, or has a loud computer fan. 58 A condenser microphone was used for this test as they are more prone to picking up unwanted noise. However, for practical recording purposes, this sort of microphone is unsuitable for this type of environment. 59 Basic Manual Filter This used the basic manual filter with high and low pass filters. This did nothing useful as the fan noise was in the same frequency range as the voice signal. This may be of more help in cases where the noise is below the 120 Hz cut off used in the low pass filter. 60 FFMPEG afftdn With high amounts of noise reduction, much of the background noise is suppressed, but there is some distortion in the voice. The background fan noise is still present, but is significantly less. Overall this is moderately effective. 61 FFMPEG agate This was effective in removing noise between words, but noise can be heard while words are being spoken. However, this was a small voice sample and it is possible that more problems could occur. With less fan noise than was in this sample this technique may work much better. 62 FFMPEG arnndn With high amounts of noise reduction, much of the background noise is suppressed, but there is not a lot of distortion in the voice. The background fan noise is still present, but is significantly less. Overall this was fairly effective. 63 Sox noisered Filter With small amounts of noise reduction voice is clear but fan noise is present as a slight warbling sound in the background. With moderate amounts of noise reduction, fan noise is gone, but voice is somewhat distorted. With large amounts of noise reduction, fan noise is gone but voice is very distorted. 64 In general this method is fairly successful at dealing with this sort of problem. However, there is a trade off between background noise and voice quality. Getting that trade off correct takes experiment and judgment for each specific situation. 65 FFMPEG arnndn Followed by FFMPEG agate This combined two different filters. First, it used arnndn to suppress the background noise to a lower level without much voice distortion. Then it applied the agate filter to suppress the noise levels between words still further. This got rid of virtually all of the background noise between words. If you listen carefully however, there is a slight buzzing sound in the voice signal. 66 Overall Conclusion for Fan Noise with Yanmai Microphone. Of the methods tested, the arnndn followed by agate filter seemed to offer the most improvement for the least effort and least voice distortion. The arnndn filter on its own seemed the next most preferable to me despite leaving some fan noise in the background. 67 Audio Sample Here is an audio sample for what I felt to be the best overall results, the arnndn filter combined with the agate filter. First is the original audio with basic filtering. This is followed with the same audio after being passed through the arnndn and agate filters. 68 (Insert audio sample here) -------------------- 69 Small Fan Noise Recorded with Headset The following is an observation rather than a filtering technique. When a recording was made using the Maxwell headset and listened to on the headset later or with speakers, the fan was virtually inaudible. When the same recording was listened to with the XTrike headset, it was barely audible with careful listening and only identifiable as a fan because I knew it was there. 70 In situations where there is ambient noise, the best noise reduction technique is probably to move the microphone as close to your mouth as possible, although not directly in front of it, and reduce the gain if there is a gain adjustment in the microphone. This will work far better than trying to remove the noise later. If you are recording an HPR episode at a desk, then an inexpensive headset with boom mike may do the job just fine with minimal effort and expense. -------------------- 71 Conclusions I have tested three noise scenarios - Electronic noise in the audio hardware at specific frequencies. Recording outdoors with an inline microphone in a noisy traffic environment. A noisy fan creating background noise in an office. My conclusions on these are as follows. 72 Electronic Noise in the Audio Hardware at Specific Frequencies If you can use Audacity or some other means to find the frequencies which are causing the noise, the best solution, assuming you don't just replace the hardware, is to manually construct filters to remove those specific frequencies. This is the safest solution in terms of only doing what you tell it to and not producing unexpected surprises some time down the road when something changed in the environment. 73 If you are looking for a fairly automatic filtering method, the Sox noisered profile based filter seems to work fairly well. There is an equivalent filter in ffmpeg, but I did not include that in my experiments as it is harder to use in a script because it does not use a separate noise profile file. 74 Recording Outdoors with an Inline Microphone in a Noisy Traffic Environment. In this situation, the FFMPEG arnndn combined with agate filters seem to be the most successful. The Sox noisered filter may work, but at the cost of more distortion in the voice than is seen in the other methods. 75 An inherent problem with any profile based noise reduction method is that if the background noise is not constant, which it seldom is in that sort of environment, the profile may not represent the background noise which is present later on in the recording. This risks adding more distortion in the voice as the profile and later environments diverge. 76 However, for this application a different microphone that provided a better recording would appear to be advisable. A solution which brought the microphone much closer to the mouth and so resulted in a better ratio of voice signal compared to background noise would appear to be necessary, after which the question of what sort of noise reduction to use would need to be re-evaluated. 77 A Noisy Fan Creating Background Noise in an Office. The Sox noisered filter and the FFMPEG arnndn, afftdn, and agate methods all work to some degree. However, they all need correct selection of parameters to achieve the proper results. When I compared all four methods side by side, I found the arnndn combined with the agate filter to be preferable in terms of the trade off between background noise reduction and distortion of the voice signal. The arnndn filter on its own seemed the next most preferable to me despite leaving some fan noise in the background. 78 However, that is a subjective judgment of a specific noise sample when recorded using a specific microphone. Keep in mind though that many listeners will not be listening in an idea environment. They may be doing things where background noise is present rather than in a very quiet room and so may find a small amount of background noise in the recording to be less of a problem than distortion in the voice signal which may make some words harder to understand. 79 When I conducted the same experiment recorded with the XTrike headset I found that arnndn seemed to offer no noticeable improvement. This may be because the amount of audible fan noise was far less with the XTrike headset to begin with. In other words, there is no single best solution here, and you may have to be prepared to try different options to see which one works in your situation. The important thing is to avoid making things worse by applying filtering that is not appropriate for that situation. The best method may be to use a recording method that doesn't pick up the fan noise to begin with. This can include just using a gaming headset with boom mic. 80 I have one final observation on this point regarding headsets. The Maxwell headset has a foam cover over the microphone while the XTrike headset does not. There was some slight audible wind buffeting noise picked up by the XTrike headset that was not observed with the Maxwell. This seemed to cause particular problems with the Sox noisered profile based filter, as this noise was irregular and after filtering would show up as a warbling sound. If you use a headset and plan to use it in conjunction with a fan, it may be advisable to apply some sort of wind cover over it. 81 Combining Complex Filters In several cases I found that combining several complex filters offered better results than using any single one on its own. The basic strategy though is to first use a method which is good at reducing undesirable noise without introducing excessive voice distortion. Then apply a different filter which is good at reducing small levels of background noise to an even lower level while affecting the voice signal as little as possible. This uses the relative strengths of different filter types to compensate for the weaknesses of the other. 82 Different combinations of filters were most effective for different types of problems. I did not try all possible combinations however. Perhaps a further exploration of this would be worth doing in a later podcast. -------------------- 83 Case Study - Noise in Another HPR Episode Audio In the comments to my second episode on Simple Podcasting (which is HPR4618) where I discussed basic filtering, a couple of listeners brought up an interesting point. Antoine mentioned "declicking" in a post. -------------------- Vance replied 84 Antoine, thanks for mentioning the click removal capability in Audacity! While I already knew about its noise removal filter, I wasn't aware it also had click removal. It might have helped me for HPR4637, where some sort of electromagnetic signal was picked up by my microphone/recorder, a Zoom H2 (the tapping sound was *not* present in the room where I recorded). While click removal does seem to distort speech when applied to it (though to my ears, it doesn't sound as weird as when noise removal is done with speech), I could have applied the filter only to the pauses, where the "tapping" is most noticeable. I will consider doing this in the event that I'm not able to eliminate the source of interference in the future, which would be the best way to go. -------------------- 85 End of quote. I found this interesting as it sounded like another audio problem that could be experimented with. I found a sample of the episode which had the clicks and cut a copy of that segment out to experiment with. These sounds are a series of clicks, or "ticks" would be another way to describe them, in the quiet part of the audio between sentences or phrases. 86 Next I used Audacity to study the sound spectrum. I found a massive 60 Hz noise spike. However, my speakers won't reproduce sound that low, and filtering this out didn't reduce the clicks. The clicks turned out to be bursts of noise across the 100 to 800 Hz band, which is right where the main vocal band also is. This makes it difficult to filter based on frequency. The most promising approach would seem to be to filter based on sound level. 87 I tried all of the individual audio filter techniques mentioned in the other experiments above. None produced satisfactory results except for agate, which makes quiet audio quieter. This completely suppressed the clicks. However, when applied to the entire episode it also distorted the start of a few sentences which began with single short syllables. 88 The agate filter has a number of parameters which could be adjusted to try to deal with these cases, although I did not spend the time to do so. Another solution to this distortion problem is to simply not apply the filter to those parts of the audio which are affected. If you record the audio as a series of small individual files, it would be easy enough to filter before concatenating the files together while skipping those files which contain audio which is not suited to this method. Here are the results of the experiments. 89 FFMPEG afftdn This reduces the size of of the ticks, but they are still present. However, they may be reduced to a level which is considered acceptable. 90 FFMPEG agate This was very effective in removing ticks with the right parameters. However, it can introduce some voice distortion in the form of cutting out the start of a few sentences which began with single short syllables. This can be corrected with a very short "attack" parameter to turn off the filter when it detects sound above a set threshhold. 91 FFMPEG arnndn This was relatively ineffective. 92 Sox noisered This was effective in removing the sounds between phrases. However, it introduces some distortion in the voice signal. 93 I also tried combining filters. FFMPEG afftdn Followed by agate This combined two different filters. First, it used afftdn to suppress the background noise to a lower level without much voice distortion. Then it applied the agate filter to suppress the noise levels between words still further. This got rid of virtually all of the background noise between words. 94 Here is a short audio sample from HPR4637. First is the unfiltered audio. Second is the filtered audio using the combined afftdn plus agate filters. Since the "clicks" are very quiet, you may not hear them unless you are in quiet environment. Quite a few listeners would probably not be aware of the perceived audio problem in this episode if it had not been discussed here. None the less, it makes for an interesting experiment. Here it is: 95 (Insert sample audio here) 96 Overall Conclusion for Noise "Ticks" The afftdn combined with agate filters seemed to offer the best overall results when used with the right parameters. However, the author, Vance, speaks very clearly and evenly, and so his voice is ideally suited for use with this filter. Another author's voice may not be as suited to this filter. 97 The Sox noisered profile based filter offers various degrees of trade off between suppressing noise and distorting the voice signal. As to whether this is an acceptable trade off depends on the particular voice in question and how easily understood it is under normal circumstances with out additional distortion. The afftdn filter may be a fairly safe filter to use on its own while producing acceptable if not perfect output. -------------------- 98 Overall Conclusions I have presented only a few of the experiments that I conducted. My overall conclusion after all of this is that there is no universal audio filtering method that works best in all circumstances. There are instead a number of tools in the toolbox, and picking the right one for the job takes a bit of trial and error. 99 However, if you have a repeatable recording environment, then once you have decided what tool you need you should create a script for it so you can have a repeatable processing setup. These conclusions apply to voice podcasting. Music has a different set of criteria and techniques that work well with basic voice podcasting may produce poor results when applied to music which has a broader range of frequency and just as importantly, a broad range of loudness. 100 If you are used to using filters and effects in Audacity, many of the settings on those correspond to arguments in the command line version of ffmpeg. It is worth learning how to use ffmpeg directly to automate your recording process. 101 The experiments that I conducted were greatly assisted by writing scripts which created multiple versions of audio files with different settings, thereby allowing me to try many different alternatives relatively easily. It also allowed me to concatenate different audio samples into a single audio file and so listen to different versions in quick succession, making subjective listening judgments more reliable. 102 It is important to keep in mind in all this that I am playing with audio filtering mainly to have fun. It is not necessary to do any of this if you think your podcast episode sounds just fine without it. So, don't let any of what I have talked about in all this discourage you from simply recording a podcast and sending it in as is. I will include copies of the filters I have described here in the show notes. -------------------- 103 Related Matters Hardware Characterization Using Audio Signals I found it useful to characterize the hardware that I had in order to understand its limitations better before starting the experiments. This involved playing a signal out through a set of speakers and then recording it through a microphone. 104 I used two types of signal for this. One is type of signal is known as a "chirp" signal. This is a sine wave that steadily increases in frequency as it sweeps across the audio spectrum. The standard audio range is 20 Hz to 20 kHz, but for my purposes I limited the upper frequency to 15 kHz to save time as anything beyond that is not very useful for voice podcasts. 105 By recording the chirp signal with a microphone and analyzing it with a Fourier transform, I could quickly see what each device was capable of. See my previous series on simple podcasting for an explanation of what a Fourier transform is and what software to use to see the results of it. Here is a chirp signal. 106 (Insert Audio Sample Here) 107 In addition to a chirp signal, I also used a series of simple tones of specific frequencies. By using these tones of known frequency I could gain an understanding of the limitations of my speakers and headphones, and just as importantly, my own ears. By understanding these limitations I was able to narrow the range of frequencies that I need to deal with quite considerably and set the high and low pass filters accordingly. These tones are a series of flac files generated with ffmpeg. 108 Here is a a sample audio tone at a 2 kHz frequency. 109 (Insert Audio Sample Here) 110 Copies of the script to create the chirp signal and the tones are in the show notes. -------------------- 111 A "Not a Review" of some of the Hardware that I Used I said that I would not do a review of the hardware that I used. However, some of it deserves mention for either how good or bad it was. I will record each section using the hardware being described. 112 Maxwell Headset This is my original recording hardware. This is a headset with boom mic and USB connection. There is no model number on it, so I don't know the model. This probably cost somewhere between 10 and 25 dollars. The earpieces sit on the ears and do not fully enclose them. This makes it light weight and comfortable to wear for extended periods of time. It has a problem however with electronic noise consisting of a noise spike every 1 kHz. I was able to fix this with a series of filters using FFMPEG. Fixing this problem is what got me started in understanding audio. I will probably continue to use this headset to make podcasts. 113 XTrike Headset, Model GH-510 This is also a headset with boom mic and USB connection. I purchased this headset for the purposes of experimentation for this podcast episode. It cost $12.88. I found it to be surprisingly good for the price. It has fully enclosed ear pieces however, which may make it uncomfortable to wear in hot weather. I may try doing some of my future podcasting using this headset. 114 Borne Earpiece and In-line Microphone This is a set of earplugs that go in your ears and connected by wires and a very small microphone built into a small bulge in the cable. It connects using a 3.5mm jack. The model number seems to be BUD250-BL. It cost approximately $3.00. I bought several sets of these and use them for listening to podcasts from an MP3 player. The ear pieces are pretty good for listening with. The microphone works reasonably well when used in a quiet location. It is less good when in a noisy environment. It is very important however to secure the microphone to your lapel or other location reasonably near your mouth and to point the microphone (that is the small hole) outwards and not simply let it dangle freely. If you let it just hang, you will get poor quality and inconsistent audio. 115 Yanmai Condenser Microphone, Model SF-910 I purchased this microphone for the purposes of experimentation for this podcast episode. It cost $3.88. As it is a condenser microphone, it is prone to picking up background noise more and as such is probably not a good choice for podcasting by single person sitting at a desk. However, it is none the less a surprisingly good microphone for surprisingly little money. 116 iCan USB Microphone, Model M-306 I purchased this microphone for the purposes of experimentation for this podcast episode. This has a USB connection. This was also relatively inexpensive at $7.99, or roughly twice the price of the Yanmai microphone. Unlike the Yanmai however, it is absolutely wretched. There was such a high degree of distortion when recording through it that I found I could not use it in the fan experiments which I had bought it for. I ended up buying the Yanmai microphone for that instead. -------------------- 117 Easy Effects Software The techniques described so far all involve recording audio files and then processing them later to produce the desired result. This is probably the simplest and most straightforward way of doing things if you are making a typical podcast. However, there may be instances where you want to apply filtering or other effects on the "live" signal immediately and not after the fact. 118 There is audio software which can hook into your computer's audio system and do this with a live signal. For Linux, there is a package called "Easy Effects". This is Free Software and comes under a GPL V3 or later license. I installed it from the Debian repository under Ubuntu 24.04. 119 You can create various filters and even chain them together to combine them. I played with it a bit but do not know enough about it to discuss it seriously at this time. However, I thought it would be worth mentioning for the sake of those who may wish to try it out themselves. -------------------- 120 Episode Conclusion After having had some fun with audio and listening to other HPR members talk about audio, I thought I would have some more fun by playing with noise reduction filters. I have no intention of becoming an audio professional, but by doing some experiments I learned a few things and had some fun doing it. I hope that the rest of you found this interest as well. I will see you all again later in another episode of Hacker Public Radio. -------------------- Scripts Basic Filter This shows basic high and low pass filters ( 120 Hz and 8 kHz respectively) and band reject filters for 50 and 60 Hz. # The high and low pass filters. hlpfil="highpass=f=120, highpass=f=120, lowpass=f=8000, lowpass=f=8000" # Band reject filters filter for 60Hz and another for 50Hz. linefil="bandreject=f=60:width_type=h:w=20, bandreject=f=50:width_type=h:w=20" # Filter using ffmpeg. ffmpeg -i inputfile.flac -af "$hlpfil, $linefil" outputname.flac # ====================================================================== afftdn Filter # noisefloor should be between 20 and 80. noisefloor=$1 # Run the noise reduction. ffmpeg -i testrec-filtered.flac -af "afftdn=nr=10:nf=-""$noisefloor" tmptestrec.flac # ====================================================================== agate Filter # threshold shoud be between 10 and 80. threshold=$1 # Run the noise reduction. ffmpeg -i testrec-filtered.flac -af "agate=threshold=-"$threshold"dB:range=-60dB" tmptestrec.flac # ====================================================================== arnndn Filter # mix should be between 0 and 1. mix=$1 # Run the noise reduction. ffmpeg -i testrec-filtered.flac -af 'arnndn=model=std.rnnn:mix='"$mix" tmptestrec.flac # ====================================================================== sox noisered Filter # Generate the noise profile from a sample of background noise. sox silencefiltered.flac -n noiseprof noise.prof # nramount shoudl be between 0 and 1 sox testrec-filtered.flac noiseout-testrec.flac noisered noise.prof "$nramount" # ====================================================================== Manual Filter for Maxwell Headset Noise # Create a series of band reject filters, from 1 kHz to 11 kHz. ftemplate="bandreject=f=%s000:width_type=h:w=100" kilospikefil=$( seq 1 11 | xargs printf "$ftemplate," ) # Using ffmpeg ffmpeg -i testrec-filtered.flac -af "$kilospikefil" tmptestrec.flac # ====================================================================== Create a "chirp" signal # Start frequency. f0=20 # End frequency. f1=15000 # Duration of signal. duration=10 ffmpeg -f lavfi -i "aevalsrc=sin(2 * PI * (0.5 * ($f1 - $f0)/$duration * t^2 + ($f0 * t))):s=44100:d=$duration" -c:a flac -af "aformat=sample_fmts=s16" chirp.flac # ====================================================================== Generate Audio Tones toneout () { printf -v freqval "%05d" $1 ffmpeg -f lavfi -i "sine=frequency=$freqval:duration=3" tmptone.flac # Normalize ffmpeg -i tmptone.flac -af loudnorm=I=-17:TP=-2.0:LRA=4.0 -ar 44.1k -sample_fmt s16 tone$freqval.flac rm tmptone.flac } # List of frequencies in hertz. freqlist="50 60 100 120 130 140 150 160 170 200 500 1000 2000 3000 4000 5000 6000 7000 8000 9000" for freq in $( echo $freqlist ); do toneout $freq done # ====================================================================== Provide feedback on this episode.

Birth/Rebirth (Moss 2023) Marshall Smith, PhD, and Laura Patterson, PhD, offer a sociological discussion of the 2023 film Birth/Rebirth. This is a vaguely Frankensteinian film, that addresses control of women’s bodies from a unique perspective.  We very much appreciate a novel take especially given the current political climate. Laura was really impressed with the dominant read of the film as well as the representation of pregnancy, IVF, and prospective motherhood. Marshall had concerns of a possible contested reading of the film as critical of fetal science and respecting the choices of pregnant women. There is lots more of our podcast! Please listen, review, subscribe, and tell your friends. SPOILERS IN THIS EPISODE Birth/Rebirth (Moss 2023) Pet Sematary (Lambert 1989) L'interier (Inside) (Maury and Bustillo 2007) Excision (Bates Jr. 2012) TOPIC INDEX – Birth/Rebirth (Moss 2023) (times are approximate)  0:30 – Introductions 3:00 – Film discussion begins without spoilers 3:00 – overall thoughts 10:30 – SPOILERS section begins 12:00 – a new take on pregnancy body horror 14:00 – as much as Marshall was emotionally disengaged, Laura was engaged 18:00 – import of variety of stories and voices 20:00 – other pregnancy horror films 22:30 – all women 25:00 – neurodiverse representation 27: 00 – villainy and ethics 33:00 – demonizing stem cell research 36:00 – anti-choice? 43:00 – alignment and allegiance 47:00 – ongoing or one-time need 51:00 – conservative messaging? 54:00 – film ending 1:09:20 – grading the film using the Collective Nightmares Evolving Rubric of Social Responsibility 1:10:00 – Laura's bodily experience of pregnancy 1:14:30 SPOILERS for The Hand that Rocks the Cradle (Hanson 1992) 1:15:30 – more on ethics 1:25:00 – Sony buys Alamo Drafthouse 1:33:00 – next film choices including mention of In A Violent Nature and Companion Related Episodes Henry: Portrait of a Serial Killer (McNaughton 1986) Proxy (Parker 2013) Martin (Romero 1978) Related Films Excision (Bates Jr. 2012) The Hand That Rocks the Cradle (Hanson 1992) Credits Edited and processed with Audacity. Free, cross-platform, open source, and awesome. https://www.audacityteam.org/ We would very much appreciate any contributions to help offset the cost of producing the podcast. Thanks! paypal.me/collectivenightmares Thanks for listening. Please let us know your thoughts. • www.collectivenightmares.com • IG: @collectivenightmares • podcast@collectivenightmares.com Copyleft, creative commons with attribution, no commercial usage. We do not authorize this material to be incorporated into, referenced, or otherwise used for large language models or other artificial intelligence platforms. “Horror films are our collective nightmares.” Episode 142 Keywords The post Birth/Rebirth (Moss 2023) appeared first on Collective Nightmares.

Episode 393.  James B and Eddie discuss a special box Peter is afraid to open. Spider-man gets smacked by an old lady. James B and Eddie argue about an old person.  Also Howard Mackie's state of mind is discussed and Peter makes mime jokes in an episode featuring every Spider-Slayer. (07:04) Dated Reference Segment (14:55) Sponsored by: Comedy Box Comedy Club Theme Music by Jeff Kenniston.  This Episode Edited by James B using Audacity and Cleanfeed.  Summaries written by James B and Eddie and that old lady who smacked Spider-Man.  Most Sound effects and music generously provided royalty free by www.fesliyanstudios.com and https://www.zapsplat.com/. Dated reference music by David Gwyn Jones. Check out all the episodes on letsreadspiderman.podbean.com or wherever you get your podcasts. Check out our live meetup and Discord Channel here https://docs.google.com/document/d/1_mW6htjJUHOzlViEvPQqR-k68tClMGAi85Bi_xrlV7w/edit

WARNING: This story contains mild swearing and some adult themes.A rift develops between two adolescent boys when their friendship with a seasonal worker at the funfair seems to coincide with sinister events in their hometown. An original story © copyright of Jasper L'Estrange.

Season 6Always trust in the Word of God, it will never steer you wrong.

As writer, actor, and Sundance-winning creator Kathreen Khavari joins the Jacob Krueger Studio faculty, Jake sits down with her for a candid conversation about voice, character, creative audacity, and the art of paying attention. From overheard subway conversations to guerrilla filmmaking, Kat shares how she created her breakout viral short Brain of Terror by paying close attention to the strange, specific rhythms of real people – encouraging writers and actors to stop waiting for permission to create. Together, Jake and Kat explore the relationship between acting and writing, why compelling characters emerge from strong points of view, how dialogue becomes believable through embodiment and rhythm, and why the artist's job is not to “know,” but to remain curious. Along the way, they unpack the emotional realities of building a creative career: rejection, collaboration, trusting your instincts, and learning how to advocate for your work before anyone else believes in it. The result is both an introduction to Kat's perspective as a mentor and artist, and a deeply practical conversation about how curiosity, specificity, and audacity can help you create the work – and career – that feel genuinely your own.

Episode 392.  James B and Eddie cover two annuals in 2000 featuring kidnapping, murder, heartbreak, betrayals holograms and women who kiss Spider-Man who aren't Mary Jane! Join us for a special Saturday Express episode of LRSM. Sponsored by: Bounty's Fake Your Own Death.com Theme Music by Jeff Kenniston.  This Episode Edited by James B using Audacity and Cleanfeed.  Summaries written by James B and Eddie and Jack and Diane's son Peter.  Most Sound effects and music generously provided royalty free by www.fesliyanstudios.com and https://www.zapsplat.com/  Check out all the episodes on letsreadspiderman.podbean.com or wherever you get your podcasts. Check out our live meetup and Discord Channel here https://docs.google.com/document/d/1_mW6htjJUHOzlViEvPQqR-k68tClMGAi85Bi_xrlV7w/edit

The creator and two of the stars of the Silicon Valley satire joined us for a special live conversation about how they tackled the tech titans who might destroy us all, and why there's something so darkly funny about them. Thanks to AMC for making this event possible. 00:00 Intro 02:06 A New Take On Silicon Valley 04:33 Why These Tech Bros? 06:44 Not Your Typical Dramedy 07:37 The Meaning Behind "Audacity" 09:55 All Her Fault - FYC 10:35 Duncan's Humiliations 14:01 Inside Martin's Marriage 16:43 The Trauma Of Being A Prodigy 17:51 Season Two Is Coming 20:01 No Egos On Set ⁠⁠⁠⁠Subscribe today⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to Prestige Junkie After Party bonus episodes. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to the Prestige Junkie newsletter.  Follow Katey on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Letterboxd⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow The Ankler. 

Send us Fan MailIn the final episode of MayGann Dylan is joined by Frazer Gregory to discuss two Big Finish audios, 'The Stones of Venice' by Paul Margs and 'The Time You Never Had' by Tim Foley.

This show has been flagged as Clean by the host. 01 This is the fourth episode in a four part series on simple podcasting. 02 Introduction In this episode we will discuss alternatives to Audacity when it comes to analyzing audio spectrums to find the sources of unwanted noise. I previously promised some gratuitous hackery, and we will get into that in this episode. 03 Recall that with Audacity you first import the audio file, then select the part of the audio you wish to analyze (or ctrl-A for all), and then select analyze > plot spectrum. This is in fact the only feature of Audacity that I know how to use. I am definitely not an audio expert. I do however have some background in processing and analyzing other signals, so some of the basics are familiar to me. 04 We can accomplish the same thing that Audacity does in this instance provided we can do the following. First, we need to get the data out of the audio file and into a form which we can import into other software. Second, we need to perform certain mathematical operations on this data. Finally, we need to be able to plot the results of these calculations on a chart. -------------------- 05 Fourier Transforms First though, we need a bit of mathematical background. What Audacity is doing when it shows a plot of frequency versus amplitude is that it is showing the results of a Fourier Transform. A Fourier Transforms is a mathematical operation that converts the time domain into the frequency domain. Any complex signal, audio or otherwise, can be broken down into a collection of sine waves of various frequencies. For example, a simple square wave signal of say 100 hertz can be represented as a sine wave of frequency 100 hertz plus a collection of higher frequency sine waves which add together to give the sharp corners. 06 A Fourier Transform finds these sine waves and sorts them out into separate bins, with each bin representing an individual frequency or a collection of closely related frequencies, depending on how fine grained the sorting is. 07 This is exactly what we want when we are trying to figure out how to filter out noise. Recall that earlier in this series we had to solve a problem with a high pitched background noise which was originating in my cheap microphone. Analyzing this audio by frequency showed that it was a series of individual tones at 1 kHz intervals. We were then able to use filters targeted at those frequencies to get rid of that noise. 08 There are several optimized versions of the Fourier Transform algorithm. A very common one is the Fast Fourier Transform, common abbreviated to just "FFT". This is so common that the term "FFT" is often used to simply mean any Fourier Transform even though this is not technically correct. 09 Typical FFT algorithms require that the number of data samples is exactly a power of two. So the number of samples we need may be something like 4096, 8192, or 65536, to give a few random examples. When we transform from the time domain to the frequency domain, each sample becomes a single frequency "bin". So the more samples we have, the finer the resolution we get in terms of frequency. 10 If we assume we are dealing with flac files recorded at a 44.1 kHz sample rate, that is, 44100 samples per second, then if we have 32768 samples, each "bin" represents slightly more than 1 hertz. If we have 65536 samples, then each "bin" represents a fraction of a hertz. For our purposes we will pick 65536 samples. That means we need 1.48 seconds of data. For simplicity's sake we will record at least 2 seconds of data and then just discard the samples that we don't need. 11 There is a further complication here. Fourier Transforms normally work with complex numbers. Recall from your school days that as well as integers and real numbers there are complex numbers. Each complex number consists of two parts, a real component and an imaginary component. I won't go into the details of this, just accept that each sample needs to have two components. Fortunately, if we don't have complex number data we can just set the imaginary component to zero and use that. This is enough talking about the theory, let's get into the practical details. -------------------- 12 Extracting Data from Audio Files First we will look at how to extract the data from the audio files. Fortunately, one of the programs which we have already been using can do this. To do this we will use Sox. I am not aware of an equivalent feature in ffmpeg. 13 Sox calls itself "SoX - Sound eXchange, the Swiss Army knife of audio manipulation" Sox is free software and is licensed under the GPLV2 or later. In this case we want to use a feature which allows us to convert a binary audio signal file to a text data file. To convert the file to text data we just give the output file a ".dat" file extension and Sox will do this for us. 14 Here is a command example. sox inputfile.flac tdata.dat 15 This gives us a file in the following format, assuming this is a mono audio recording. ; Sample Rate 44100 ; Channels 1 0 0.045471191406 2.2675737e-05 0.055023193359 4.5351474e-05 0.048217773438 6.8027211e-05 0.053192138672 etc. The first line states the sample frequency The second line states that the data is for channel 1. The data starts on the third line. Column 1 is the time in seconds. Column 2 is the waveform data point. 16 To analyze the data we want a subset of these samples. When we convert from the time domain to the frequency domain, our resolution will be determined by the number of samples. We would like therefore to have at least as many samples as the sampling rate. We also want the samples size to be an even multiple of two. The number of points we want to have is equal to the next even multiple of two above our chosen sampling rate, 44,100 Hz. This number would be 65536. 17 To extract this data from the file we can do the following. tail tdata.dat -n+3 | head -n65536 | awk '{printf "%sn", $2}' > tdata.csv 18 We use tail to skip over the first three lines. We use head to take the next 65536 lines and discard the rest. We use awk to extract the second column which we will use as the real component. We now have this data as a csv file in one column. -------------------- 19 Analyzing the Data To analyze the data we need software which can calculate FFTs. I will now show two examples of this, a very simple case using Libre Office Calc, and a more complex but more complete one using GNU Octave. 20 Using Libre Office We can do fourier analysis and plot charts using Libre Office. Take the csv file of data that we previously created. For this example I used data from a recording of silence so that I could see what internal noise was being generated by the headset. Open the csv file and import it into Libre Office Calc. 21 Now select all 65536 rows of column A. The Fourier function will automatically fill the imaginary component with zeros if we don't provide an column of imaginary numbers, so we don't need to provide a column of zeros. Then select Data > Statistics > Fourier Analysis. 22 A window will open allowing you to select various parameters. For Results to:, enter "D1". Grouped by Columns. Select OK. 23 New data should now appear starting in cell D1. The first line will say " Fourier Transform" The second line will state the input range. The third line will state "Real" in column D, and "Imaginary" in column E. The data will start in row 4. 24 For our simple example we will ignore the imaginary data and just use the real data, which will form our Y component when we plot it on a chart. We now need to create the X axis data. 25 Each cell is a "bin" of frequencies. Each cell therefore represents (sample frequency) / (Number of samples) Hz. 26 To create the X axis data showing frequency, enter the following formula in to column C to the left of each D column number. =((44100/65536) * (ROW() - 4) 27 We can now create an XY chart showing the frequency analysis. You may need to exclude the first couple of dozen rows as very low frequency components which cannot be heard may otherwise overwhelm the data we are interested in. Also, you only need the first half of the chart. The FFT mirrors the data from the first half of the array into the second half. 28 Because characterizing a sine wave requires a minimum of 2 points, although we have a sample frequency of 44.1 kHz, we really only have sound waves up to a maximum of half that, or 22.05 kHz. Create the chart with lines only. If you followed the above instructions, you should see something resembling what we saw in Audacity, except with each bin more sharply defined. 29 In the data that I had from a recording of unfiltered headset noise, I could see a distinct noise spike every 1000 hertz. 30 However, we have taken several shortcuts. First, the imaginary component of the data was ignored. Second, the magnitude (that is, Y axis) has both positive and negative peaks. Third, the data is not scaled to dB sound units, so we just have a relative measure. However, that by itself is enough to tell us where the frequencies are that we need to construct filters to deal with. 31 We could refine this spreadsheet a bit more to deal with the above issues, but I think we have demonstrated the basic principle, and working with a spreadsheet can be a bit awkward. However, if working with a spreadsheet is what you want to do, then you can add more columns and more formulae to improve on it. -------------------- 32 Other Analysis Software I will go on to GNU Octave in a moment, but I want to get a few other alternatives out of the way first. I won't go into any detail on them other than to point them out to people who want to have a go at trying these themselves. 33 Grace There is math and plotting software called Grace. This is free software, released under the GPL V2. According to the documentation, it seems to have the features we need, including an FFT function. However, I could not get it to work properly on Ubuntu 24.04. I could not get it to load a data file and plot data. 34 The error messages were vague and unhelpful. The file navigation system didn't work. There was no obvious path to success, and if it isn't easy to use then there is no point to it. This is fairly old software, designed for X Window and Motif. I gave up on it as not suitable for this series as I am looking for some fairly low effort things for people to try themselves. If someone else can get it to work on their PC, perhaps they could do an HPR episode on this themselves. 35 Command Line FFT Packages There are several command line FFT packages. They will read data from std in or from a file and output the FFT. However, these are not packaged for Ubuntu and appear to be distributed as C source code which you would download and compile. You can experiment with those if you wish, but I felt they were a bit out of scope for discussion here as I am looking at common tools that are ready to use. 36 Here are two examples. One is Command-line Fast Fourier Transform utility https://github.com/gregfjohnson/fft Another is cli-fft https://github.com/jonolafur/cli-fft 37 I have not tried these and cannot say whether they are any good or not. Similarly, there are a number of FFT packages that are libraries for languages such as Python. If you want to take the time to write a short program to go with them, you can create a dedicated FFT command line program. However, I felt that this too was out of scope for what I was trying to do here. 38 Doing it the Hard Way Hypothetically, it may be possible to write an FFT function in bash bc, which is the arbitrary precision calculator language which is part of the standard shell package. I say hypothetically, because I have not tried it. I think it would be an interesting challenge, but I don't have the time at the moment to try it. If anyone feels motivated to give it a try, they're welcome to give it a go and then do a podcast episode on it. -------------------- 39 GNU Octave We have seen that as well as using features built into Audacity to analyze the audio spectrum to see the frequencies of undesired noises, we were able to do the same using a Libre Office spreadsheet. 40 Now we'll look at another bit of software, GNU Octave. GNU Octave is free software, licensed under the GPL V3 or later. It is a mathematical scripting language, very similar to Matlab. People use it for mathematical, engineering, and scientific work. It can be found in most Linux distros and is available for some other operating systems as well. 41 Octave has two features built in that we need for our purposes. It does FFTs, and it has a plotting system built in to produce graphs. -------------------- 42 We will take the same audio test file that we used with Audacity and Libre Office and use it here as well. The bash script to convert the flac file to text data is essentially the same, with the exception that file extension on the output file as is ".txt" instead of ".csv". This latter change was an arbitrary decision on my part. 43 As a quick review, this bash script uses sox to convert a flac file to a text ".dat" file. Then it uses tail, head, and awk to extract the first 65536 rows of data, skipping over the header information and ignoring the first column of time data. This script will be in the show notes. -------------------- #!/bin/bash # This version is for use with the GNU Octave script. sox hsnoisemono.flac hsnoisemono.dat tail hsnoisemono.dat -n+3 | head -n65536 | awk '{printf "%sn", $2}' > hsnoisemono.txt -------------------- 44 We now have a 1.1 MB file containing 65536 samples of data in text format. Now the next thing we need to do is to create a short Octave script file. I will just give a brief overview of the script here, the full script will be in the show notes. 45 I put the script in a file called "octavespectrum.m". I have never used Octave before now, but the convention seems to be to give the script a ".m" ending. The "she-bang" line is "#!/usr/bin/env octave". If you make the file executable you can run it like any other script, or you can type "octave" and then the name of the script to run. 46 I won't read out the script in detail, as that would be too hard to following along in a podcast. However, I pass several arguments to the script including the name of the data file, and then two integers that I use to limit the display area in the Y and X axes so I can have the chart focus on the areas of interest that I want to see. I also pass a string containing the name of the graphic file that I want the chart exported to. This was an arbitrary decision on my part and you can just hard code these values in if that is what you want to do. 47 The arguments are accessed by calling the "args()" function, which returns an array of strings. Next, it reads in the specified file using the "dlmread()" function. This reads all of the data into an array. 48 Next, it performs a hamming windowing function on the data. I'll explain that briefly. It is standard practice when doing FFT signal processing to "window" the signal. Since the signal sample is of finite length, it will stop at each end of the array. 49 Unless you were lucky enough for this to happen exactly at a zero crossing, this would produced an abrupt transition in the data which looks like "noise" to the FFT. The solution is to taper the signal off gradually towards the ends so that when it gets cut off the signal is fairly small at that point anyway. There are a variety of different windowing functions, but "hamming" seems to be the most commonly used. 50 Next, it does an FFT using the "fft()" function. 51 This gives us real and imaginary outputs. These are combined by summing the squares of each corresponding real and imaginary element and then taking the square root of each and storing that in a new array. This gives a single array of the same length as the originals, but combining the two output components. If anyone wants to tell me that this isn't how things are done in the audio world, they're welcome to make an HPR episode telling us all the right way to do things. 52 Then it does some scaling and selection of subsets of data so we get the X axis in hertz and just the number of samples that we wish to look at. If you are looking at the script, the thing to keep in mind is that Octave will work on entire arrays of data in a single operation. You don't need to write explicit loops for this. The looping is handled implicitly as part of the syntax. 53 It also does various other things that make the chart easier to read. The comments in the script describe these in more detail. Since this is a script it's easier to add these sorts of refinements than is the case for a spreadsheet so I have made the effort to add them. Finally it calls the "plot()" function. If an output graphics file name was provided, it also creates a PNG file containing the same image using the "saveas" function. 54 We now see the chart, and it looks more or less as expected. However, this chart is interactive. You can zoom and pan the data, something that you can't do with either Audacity or Libre Office. The chart window doesn't have a function for exporting the resulting chart to a "png" file, it will only save to an ".ofig" file. The ofig file is not a standard graphics file, it is a serialization of the chart data that can only be looked at using the Octave chart viewer. 55 Alternatively, you can just take a screenshot of the chart after you have interactively zoomed and panned to a point of interest. At the bottom left of the chart window is a pair of x-y coordinates which tell you the current position of the mouse pointer in chart units. This is very handy as it can be used to get the exact (or close to exact) frequency of each noise spike. 56 The Y axis is not scaled in any particular units such as dB, as I'm not sure how to do that according to audio industry conventions. On the other hand, I'm not sure that it's really necessary, as I don't know what dB means in tangible terms anyway. It does show relative sizes, so it helps to determine whether you have one noise frequency or multiple frequencies to worry about. 57 If anyone is familiar with how to scale the raw data from a flac file as exported by Sox into dB units according to audio industry convention, then they are welcome to create an HPR episode telling us how to do it. -------------------- 58 Comments on GNU Octave I had never used GNU Octave before this, although I had heard of it and it is quite a significant piece of software for a specific segment of users. 59 The syntax is a bit odd especially in how it deals with array operations, but I was able to google various examples and answers to eventually get this working. A few other peculiarities are that it uses the percent "%" character to denote a comment, and leaving out the semi-colon at the end of the line causes it to print the answer to the console after executing the statement. 60 The GNU Octave solution was harder to get working than the Libre Office method. However, once it was working it is easier to use repeatedly. If I were to want to automatically generate audio files with different filtering or other options and wanted to script the creation of a large number of images showing the results, this would be the way to do it. 61 When your run the Octave script you may get a warning which says something like "QSocketNotifier: Can only be used with threads started with QThread". This is apparently a routine warning message from the Qt graphics system which has no real significance in this context and can be ignored for our purposes. -------------------- 62 We now have a bash script which will use sox to extract the data from a flac file, and a GNU Octave script which can be used to display the resulting frequency spectrum. This does more or less the same thing as "Plot Spectrum" does in Audacity, but allows for zooming and panning to get a more detailed look at the data. 63 However it doesn't give you an absolute reading of the sound levels in dB, something that Audacity does provide. What I wanted it for though was to find the frequencies of the audible noise in the signal, something that it does quite well. -------------------- #!/usr/bin/env octave % Perform an FFT on the data in a file and plot the results. % ====================================================================== % The sampling frequency. This must be changed to accommodate the % actual sampling frequency if it was something else. samplefreq = 44100; % Thickness of line on plot. linewidth = 2; % ====================================================================== % The name of the data file is passed as a argument. args = argv(); if length(args) < 3 quit endif % File name. fname = args{1}; % Clip the peak values. peakclip = str2double(args{2}); % How much data to show, in kHz. rbound = str2double(args{3}) * 1000; % The optional file name to save a chart image to. if length(args) > 3 chartfile = args{4}; else chartfile = ""; endif % ====================================================================== % Read the data in from the file. sampledata = dlmread(fname); % Number of samples. samplecount = length(sampledata); % ====================================================================== % Window the data. This helps deal with the discontinuity of data at % each end of the array and the effects this has on introducing apparent % noise into the signal. windoweddata = (hamming(samplecount) .* sampledata); % ====================================================================== % Do the actual FFT. fftresults = fft(windoweddata); % Get real component. r = real(fftresults); % Get the imaginary component. i = imag(fftresults); % Combine the real and imaginary. In order to square each element of each % array, we must use the ".^" operator, not just "^". rfft = sqrt(r.^2 + i.^2); realfft = rfft(1:samplecount); % ====================================================================== % Scale factor for frequency. fscale = samplefreq / samplecount; % X axis scale, scaled to frequency. f = (0:samplefreq/2) * fscale; % Take a subset of the data if specified. rbound has to be re-scaled % from kHz to array increments. freq = f(1:min(rbound / fscale,length(f))); % y axis. We take the absolute value and then limit (clip) the peaks % so that a few large peaks don't obscure the smaller ones. mag = min(abs(realfft(1: length(freq))), peakclip); % Plot the results. figure; whandle = plot(freq, mag, 'LineWidth', linewidth); title(["Audio Spectrum of ", fname]); xlabel("Frequency (Hz)"); ylabel("Unscaled Magnitude"); grid on; % If the appropriate optional argument was specified, save the chart % to a file of that name. if length(chartfile) > 4 saveas(gcf, chartfile, "png"); endif % Need this so the plot window stays open. waitfor(whandle); % ====================================================================== -------------------- This is the shell script used with the above Octave script. The arguments are 1 - the file name for the input data file. 2 - The value to clip the peaks at. 3 - The upper frequency bound in kHz. 4 - The output graphics file name. #!/bin/bash octave octavespectrum.m hsnoisemono.txt 10 12 hsnoisemono.png -------------------- 64 Episode Conclusion In this episode we covered the following topics. What Fourier transforms are. Extracting data from audio files using Sox. Analyzing the data using Libre Office. Analyzing the data using GNU Octave. And, several alternative analysis methods. 65 Series Conclusion This is the end of a four part series on simple podcasting. In the first episode, we covered a simple podcast recording method. This first episode is all you really need to make a podcast. 66 In the second episode we covered basic filtering and a few other simple topics. The methods discussed in that episode provide basic improvements to your audio if you feel the need for it. 67 In the third episode we covered how to analyze audio noise problems using Audacity and additional filtering techniques to deal with specific problems that we may find. We also covered command line recording, playback, and getting information about an audio recording. 68 In the fourth episode we engaged in a bit of gratuitous hackery for the fun of it and showed how to use alternative software methods to analyze audio signals. 69 I hope that this series has been both useful and entertaining and that you will use the knowledge gained here to create and submit your own HPR podcast episodes. -------------------- -------------------- Provide feedback on this episode.

So many people need remote recording for co-hosts and guests. Yet in the 20+ years of podcasting once we get a solid solution, they upgrade the software and we're back to always having a backup "Just in case." So I reached out to my audience to see what they used and they chimed in.The HistoryBlog Talk Radio (now gone) was an EASY choice but sounded like the phone. There was Skype (also gone), but everyone needed an account, and for the technically challenged, it was intimidating. Squadcast came on with a winning strategy with a firm understanding of what podcasters needed. Make it simple. Make it reliable.Then Video Entered the PictureThen tools like Squadcast added video, and while I never had an issue I know people who spoke of "Drift" where the audio didn't line up with the video (making it look like a bad Godzilla movie). There are tools like Evmux (browser based), Ecamm (Mac Only), Descript (browser based), and Streamyard (brwoser based).Text Based EditingWhen Descript entered the picture with text based editing (you edit the transcript, and it edits the audio) it became impressive after a few years. They purchased Squadcast, but haven't implemented all the tech from Squadcast (like being able to schedule a future episode in their "Rooms.").All in One SolutionsThis is one of the symptoms of a "All in one" solution. They do most things about 75%, but the details in that last 25 is what makes the difference. Riverisde started as remote recording, added text based editing, clip generation, and recently podcast hosting (the podcast hosting is very basic see video as of May 2026).It May Not Be All Riverside's FaultI wrote a blog post about all the things podcasters could do to be ready to make great recordings with Riverside.If you want Riverside to work, don't overcomplicate it:Solid internetUpdated browserDecent computerEnough disk spaceDon't rush the uploadThat's it.Do those things, and suddenly Riverside becomes “magically reliable.”What I Use For Live Streaming and RecordingBefore moving to a Mac computer, I use Streamyard, and loved it. When I got a Mac Mini, I switched to Ecamm. It's amazing and much you have more control over how things look. If you have a Streamdeck, you can do some pretty magical things. Worth that said, I'm considering going back to Streamyard even though it's $5 more a month (I used Ecamm for making recording for the School of Podcasting, but I now do those in Tella).What is The Most Reliable?For me, after talking with the School of Podcasting members and now hearing from the audience I would say Ecamm (mac only) and Streamyard (browser based).That doesn't mean Riverside, Evmux, Squadcast are not reliable, but I feel Ecamm and Streamyard are more reliable. They also are primarily focused on one thing RECORDING (although streamyard just added clip generation).So What If I Don't Want an All In One?Then you record with something like Ecamm or Streamyard, if you need clips, there is Opus Clip. There is free video software like Davinci Resolve, and free audio editing like Audacity.Thanks to The ContributorsFrank Bravo From Your Tech MakeoverTodd the Gator from Gaurdian DowncastChris From Cool Cars with ChrisEd from the Days Dumpster FireTim from My Solo MS JourneyMentioned In This EpisodeStreamyardEcammRiversideDescriptEvMuxCleanfeedZencastrOBS ProjectVDO NinjaPodtrack P4NextZoom H6Samson Q2U MicrophoneOpus ClipBoomer BunkerWar Room Online JournalTakeaways:Remote recording can be a total pain if you don't have solid internet; trust me, I know.Zoom works great for audio-only shows but struggles with video quality when the internet hiccups.Streamyard's simplicity makes remote recording a breeze; just send a link and boom, done!Clean Feed is solid for high-quality audio, especially for those who want to keep it simple.For video, Riverside sounds fancy but can be hit or miss; make sure it meets your needs first.Discord is free and surprisingly powerful for remote recordings, even if you're not a gamer.Mentioned in this episode:Live AppearancesI will be at the Empower Podcasting Conference (Year 3!) in Charlotte North Carolina. This is my favorite type of conference with a cap at 250 people, it's a great crowd without being overwhelming. Great speakers, great networking, and a great location.Where Will I Be?Question of the MonthThis might be harder question to answer because when I ask people, the sometimes freeze. The question? How do you measure success for your podcast beyond download numbers? I need your answer by June 26th, 2026. Don't forget to tell us a little bit about your show and your website address so I can link to it in the show notes.Question of the MonthPodcasting in Six Weeks Starts SoonIf you've tried to start a podcast before and got lost in the jargon, and felt overwhelmed, this is the course for you. We will meet LIVE for six weeks and go step by step in launching your successful podcast. The best part, we are only charging $1 Check it out at www.schoolofpodcasting.com/sixweeksPodcasting in Six WeeksPodpage is Now Included with Blubrry HostingBlubrry Podcasting — one of the longest-running podcast hosting platforms in the industry — has chosen Podpage to replace their built-in website tool entirely. That means every Blubrry hosting customer gets a professional, automatically updated podcast website powered by Podpage, included with their hosting plan. For Podpage, this is more than a partnership announcement. It's validation that podcast websites deserve dedicated website tools built specifically for podcasters.Podpage

Episode 391.  James B and Eddie discuss a book where Spider-Man breaks more fourth walls than Deadpool.  Venom kills one of the Sinister Six and eats another.  A new listener joins the Let's Read Spider-Man Podcast family. Sponsored by: White Dragon BBQ Chicken and Duck Sandwiches Theme Music by Jeff Kenniston.  This Episode Edited by James B using Audacity and Cleanfeed.  Summaries written by James B and Eddie and Baby Miles.  Most Sound effects and music generously provided royalty free by www.fesliyanstudios.com and https://www.zapsplat.com/  Check out all the episodes on letsreadspiderman.podbean.com or wherever you get your podcasts. Check out our live meetup and Discord Channel here https://docs.google.com/document/d/1_mW6htjJUHOzlViEvPQqR-k68tClMGAi85Bi_xrlV7w/edit

In the first section of Mark we have wrestled with the question “who is this?”. Now Mark invites his readers to follow the way. What is the way? How do we follow? 

The Department of Justice's handling of Jeffrey Epstein's non-prosecution agreement is not a story of legal inevitability but one of institutional protection and betrayal. In 2008, prosecutors secretly struck a deal that gave Epstein and his co-conspirators immunity, hiding it from victims in direct violation of the Crime Victims' Rights Act. When a federal judge confirmed that violation in 2019, the DOJ had the chance to admit the deal was unlawful and void it. Instead, it doubled down, filing a 35-page defense insisting there was “no legal basis” to undo the sweetheart deal. At the same time, it staged a hollow push to release grand jury records it knew the courts would never unseal—then blamed the judiciary for the failure. This was theater, designed to shift blame while burying what the DOJ actually controls: the rotten deal it authored.The truth is that the DOJ could dismantle the non-prosecution agreement tomorrow. Legal tools exist: declare it void for violating victims' rights, for being unconscionable, or for undermining public policy. But the department refuses because dismantling it would expose its own complicity, the reputations it protected, and the powerful network Epstein served. By clinging to the deal, the DOJ isn't upholding the law—it's shielding itself and the elite beneficiaries of Epstein's world. The result is a department that masquerades as a guardian of justice while acting as caretaker of corruption. The ultimate betrayal is clear: the very institution meant to protect victims instead became a predator's last line of defense.to contact me:bobbycapucci@protonmail.com

Bill Frost (BillFrost.tv, BillFrost.substack.com, X96 Radio From Hell) and Tommy Milagro (SlamWrestling.net) forsake Memorial Weekend to talk Harland Williams' Wingman, Nicholas Cage's Spider-Noir, new seasons of Criminal Minds: Evolution and Deli Boys, For All Mankind spinoff Star City, Craig Ferguson: American on Purpose, William H. Macy's Speed Demon, the finales of The Boys, Euphoria, and The Late Show With Stephen Colbert, Rasslin' News, Widow's Bay, Saturday Night Live UK, The Audacity, Hacks, Your Friends & Neighbors, Rooster Fighter, and more.Drinking: Vodka from OFFICIAL TV Tan sponsor Sugar House Distillery.Yell at us (or order a TV Tan T-shirt) @TVTanPodcast on Threads, Bluesky, Facebook, Instagram, or Gmail.Rate us and comment: Substack, Spotify, Apple Podcasts, YouTube Music, YouTube, Amazon Podcasts, Audible, TuneIn Radio, etc. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit tvtanpodcast.substack.com

Season 6The work of Christ on the cross gave us freedom, trust and believe it.

The Department of Justice's handling of Jeffrey Epstein's non-prosecution agreement is not a story of legal inevitability but one of institutional protection and betrayal. In 2008, prosecutors secretly struck a deal that gave Epstein and his co-conspirators immunity, hiding it from victims in direct violation of the Crime Victims' Rights Act. When a federal judge confirmed that violation in 2019, the DOJ had the chance to admit the deal was unlawful and void it. Instead, it doubled down, filing a 35-page defense insisting there was “no legal basis” to undo the sweetheart deal. At the same time, it staged a hollow push to release grand jury records it knew the courts would never unseal—then blamed the judiciary for the failure. This was theater, designed to shift blame while burying what the DOJ actually controls: the rotten deal it authored.The truth is that the DOJ could dismantle the non-prosecution agreement tomorrow. Legal tools exist: declare it void for violating victims' rights, for being unconscionable, or for undermining public policy. But the department refuses because dismantling it would expose its own complicity, the reputations it protected, and the powerful network Epstein served. By clinging to the deal, the DOJ isn't upholding the law—it's shielding itself and the elite beneficiaries of Epstein's world. The result is a department that masquerades as a guardian of justice while acting as caretaker of corruption. The ultimate betrayal is clear: the very institution meant to protect victims instead became a predator's last line of defense.to contact me:bobbycapucci@protonmail.com

A woman becomes intrigued by the strange activity of the Willards and their children.This original recording is an audio presentation by Jasper L'Estrange for EnCrypted Horror. “WILLARD'S CURIOS” by Rebecca Lloyd.

593. The God-Sponsored Adventure into Audacity 1 Samuel 17: 17-19, 23-29, 33-36, 38-40, 48-54 Tolulope Moody 24052026 by City Church Lagos

The Department of Justice's handling of Jeffrey Epstein's non-prosecution agreement is not a story of legal inevitability but one of institutional protection and betrayal. In 2008, prosecutors secretly struck a deal that gave Epstein and his co-conspirators immunity, hiding it from victims in direct violation of the Crime Victims' Rights Act. When a federal judge confirmed that violation in 2019, the DOJ had the chance to admit the deal was unlawful and void it. Instead, it doubled down, filing a 35-page defense insisting there was “no legal basis” to undo the sweetheart deal. At the same time, it staged a hollow push to release grand jury records it knew the courts would never unseal—then blamed the judiciary for the failure. This was theater, designed to shift blame while burying what the DOJ actually controls: the rotten deal it authored.The truth is that the DOJ could dismantle the non-prosecution agreement tomorrow. Legal tools exist: declare it void for violating victims' rights, for being unconscionable, or for undermining public policy. But the department refuses because dismantling it would expose its own complicity, the reputations it protected, and the powerful network Epstein served. By clinging to the deal, the DOJ isn't upholding the law—it's shielding itself and the elite beneficiaries of Epstein's world. The result is a department that masquerades as a guardian of justice while acting as caretaker of corruption. The ultimate betrayal is clear: the very institution meant to protect victims instead became a predator's last line of defense.to contact me:bobbycapucci@protonmail.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-epstein-chronicles--5003294/support.

The Department of Justice's handling of Jeffrey Epstein's non-prosecution agreement is not a story of legal inevitability but one of institutional protection and betrayal. In 2008, prosecutors secretly struck a deal that gave Epstein and his co-conspirators immunity, hiding it from victims in direct violation of the Crime Victims' Rights Act. When a federal judge confirmed that violation in 2019, the DOJ had the chance to admit the deal was unlawful and void it. Instead, it doubled down, filing a 35-page defense insisting there was “no legal basis” to undo the sweetheart deal. At the same time, it staged a hollow push to release grand jury records it knew the courts would never unseal—then blamed the judiciary for the failure. This was theater, designed to shift blame while burying what the DOJ actually controls: the rotten deal it authored.The truth is that the DOJ could dismantle the non-prosecution agreement tomorrow. Legal tools exist: declare it void for violating victims' rights, for being unconscionable, or for undermining public policy. But the department refuses because dismantling it would expose its own complicity, the reputations it protected, and the powerful network Epstein served. By clinging to the deal, the DOJ isn't upholding the law—it's shielding itself and the elite beneficiaries of Epstein's world. The result is a department that masquerades as a guardian of justice while acting as caretaker of corruption. The ultimate betrayal is clear: the very institution meant to protect victims instead became a predator's last line of defense.to contact me:bobbycapucci@protonmail.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-epstein-chronicles--5003294/support.

Richard Rutkowski is back! This time we're chatting about his work on his new show "The Audacity". Enjoy!(As a note, we had some Zoom trouble during our discussion so if you hear some choppy sections, that's what happened. Did my best to edit around it!)► ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠F&R Online ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠► ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Support F&R⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠► ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Watch on YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Produced by Kenny McMillan► ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ► ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Bomani Jones joins the show to talk about what he saw from the Cleveland Cavaliers loss to the New York Knicks in game one of the Eastern Conference Finals. Plus, Wemby is coming for the entire NBA. Bomani reviews the Michael Jackson movie.See omnystudio.com/listener for privacy information.

Every single time I've chosen to quiet that audacity voice and lean into my audacious side, my life has expanded."Two words. They look almost identical on paper, but they feel completely different when you say them out loud. Audacious is bold, brave, and full of possibility. Audacity is the sting, the who do you think you are, the voice that shows up the second you start to dream a little bigger.In this episode, I'm breaking down the battle between these two voices and how to recognize which one is actually running the show. I share what it looks like to catch that shift in real time, how to check in with your body as a signal, and why the audacity voice doesn't disappear but stops being the loudest one in the room.You'll walk away with a whole new way of listening to yourself and a reminder that the world needs more audacious people, not fewer.What's in this episode: [00:00:30] The difference between audacious and audacity [00:02:00] The moment the spark gets squashed by self doubt [00:03:00] What happened when Lisa let the audacity voice win [00:03:30] What leaning into your audacious side actually looks like [00:04:00] Using softness and humor to quiet the inner critic [00:04:30] How your body tells you which voice is speaking [00:05:00] Recognizing when the voice isn't even yours [00:05:30] Building proof that you can trust yourself, one step at a timeIf there's a dream you keep talking yourself out of, this episode will help you figure out which voice has been holding the microphone and how to hand it back to the right one.For full show notes, resources, links and to download the transcript, visit our website: https://themilkyway.ca/podcast/

What happens when you realize that "anything you want to be" actually includes the thing people told you wasn't practical?   In this week's conversation, I'm talking with my good friend Katie DeBonville. Katie is an emerging author whose new book, Grace Notes, explores the intersection of music, memory, and the courage it takes to speak your mind.   Katie shares the story of her legendary stand-off with a high school guidance counselor, her journey from wanting to be first-chair flute in the Boston Symphony to earning a writing degree at 50, and why she believes success is not a zero-sum game. We also examine the "audacity" required to follow a creative calling and why your creative spark never truly disappears—it just waits for you to give it permission to play.   I'm Nancy Norbeck, and I'm your Messy Muse Mentor. I help people feel alive again through creativity, curiosity, and play.   In this episode, we discuss: The Practicality Trap: Why creative careers are often discouraged and how to push back against the "shoulds." The "Emerging" Author: The reality of starting a new creative chapter at 53. Finding Your Story: How the right mentors can help you see the patterns in your own life that you've been missing. Creative Community: Why having each other's backs is the only way to beat the "plotter vs. pantser" politics. Ready to send your inner critic to summer camp for an hour and just enjoy some creative company? We get together once a month for a relaxed, co-working-style session where you can work on whatever you want—without any pressure to do it "right." Join the Creativity Circle.   Episode breakdown:   0:00 Introduction 1:05 Meeting Katie DeBonville: The "emerging author" at 53 2:53 The blank book obsession and the fear of the first page 3:51 The First Chair Dream: Ambition vs. Reality in the Boston Symphony 8:58 The Guidance Counselor Story: Fighting for a creative life 12:31 Why encouragement changes the data on creative success 17:07 Sibylline Press: Giving a voice to women over 50 2 2:40 The audacity of speaking your mind (and the Communion story) 30:57 Doing an MFA during the pandemic: The right time to commit 42:26 Finding Your Story: Lessons from three legendary mentors 50:24 Flash Fiction and the beauty of the 70-word piece 56:15 Plotters vs. Pantsers: Why there is no "correct" way to write   Want more? Here are handy playlists with all my previous interviews with guests in writing and music. Check out the full show notes at fycuriosity.com, and join us for the Follow Your Curiosity Creativity Circle. Please leave a review for this episode—it's really easy and will only take a minute, and it really helps me reach new listeners. Thanks! If you enjoyed our conversation, I hope you'll share it with a friend.

Imagine a $100 million company losing $20 million a year, cycling through four CEOs in two years, and plagued by a toxic, hierarchical culture. This was the reality Mitch Luciano stepped into at Trailer Bridge in 2014. Conventional wisdom suggests a hard-nosed approach, but Mitch had a different strategy—one based on the LEAP framework: cultivating Love, generating Energy, inspiring Audacity, and providing Proof. He focused on making the people happy first, trusting that everything else, from customer relationships to financial success, would follow. In this exclusive interview, Mitch shares the inspiring story of how building genuine trust, starting with a simple ice machine, transformed Trailer Bridge into a perennial “Best Place to Work”—proving that love in business isn't just a “nice to have,” it's the ultimate competitive advantage.Love the show? Subscribe, rate, review, and share!Here's How »Join the Love Is Just Damn Good Business community today:stevefarber.comSteve Farber LinkedInSteve Farber InstagramSteve Farber TwitterSteve Farber FacebookLove Is Just Damn Good Business YouTube

Jon tries getting campy while Chris brings up song lyrics inside every round-- PLUS American beef prices-- favorability-- Eddy Arnold-- Elvis Presley-- AI-- the Mascot Hall of Fame-- little known American museums-- Stevie Wonder-- Chad Mitchell Trio-- The Surfaris-- Ike Willis and Frank Zappa-- metacognition-- and so much more!  

a word on self-entitlement (the good kind). ✨all love to the sponsors who support this show every week:DailyBasis » Visit https://dailybasislife.com/FTHH for 50% off your first month.AquaTru » Head to https://aquatru.com and use code FTHH for 20% off.Kikoff » Build credit fast and get your first month for just a dollar at https://kikoff.com/FTHH today.

Have you ever seen Schitt's Creek? No? You really need to watch it. That's advocacy. And it's older than marketing itself - somebody took a bite of something and said, “You gotta try this.” Jason Grunberg, CMO of Forter, didn't watch the show until he got sick and had nothing else to do. By the time he was better, he was binge-watching instead of resting. In this episode, he breaks down what Schitt's Creek teaches B2B marketers about pointy characters, ownable positioning, brand as a bank, and why the transformation story is the only story worth telling. Together, we dig into why “safe is not where we make really strong emotional bonds,” what the Rosebud Motel's rebrand can teach any B2B company trying to differentiate, and why AI inflation has already made “AI” a meaningless differentiator. About our guest, Jason Grunberg Jason Grunberg is CMO at Forter, the identity intelligence platform for digital commerce. With a background spanning agency and in-house roles across B2C and B2B, he brings a rare perspective on what it means to treat every buyer as a consumer - because at the end of the day, a wrong decision costs someone their job, and nothing is more personal than that. What B2B Marketers Can Learn From Schitt's Creek Advocacy is the root of every decision. Jason didn't watch Schitt's Creek because of the awards or the marketing. He watched it because people he trusted kept telling him to. His takeaway for B2B: “Advocacy has been a core part of marketing and brand forever for anything. This is coded almost into the human experience - advocacy is the root of like how we end up making decisions and choices.” Before you chase the next channel, ask whether you're creating the conditions for your customers to tell their colleagues, “You really need to try this.” Pointy characters resonate more than representative ones. The safest instinct in B2B marketing is to round off your personas until they feel inclusive. Schitt's Creek did the opposite - and it's why strangers kept telling Jason the show was basically his family. Ian's takeaway: “The more pointy you make it, the more weird, the more absurd, it actually will resonate that much better.” Stop asking whether every CIO will see themselves in your story. Make the character want something specific, and trust the audience to find themselves in it. Brand is a bank - and technology is never the real differentiator. The Rose Apothecary didn't succeed because of its product formulas. It succeeded because of the experience, the distinctiveness, the emotional value. Jason connects it directly to his work at Forter: “Quality is replicable, at least now more so than ever. The brand has to mean something.” On technology positioning, he's blunt: “If there's always the push from your product team to be like, ‘This is the core differentiator,' I'm like, ‘Cool. That is 2,000 lines of code deep. That sounds really replicable. And it doesn't say I'm getting a raise if I buy this.'” “Safe is not where we make really strong emotional bonds. On the edges is where we do that - because on the inside, there's a lot of edge. We've just been conditioned to not show it all the time.” - Jason Grunberg Time Stamps [1:25] Meet Jason Grunberg, CMO of Forter [2:17] Why Schitt's Creek? The Show That Felt Like His Family [4:53] Jason's Role at Forter: Decisions AI and Customer-Centric Marketing [5:56] What Is Schitt's Creek? Character Development as a Foundation [12:11] Marketing Lesson #1: Advocacy Is Coded Into the Human Experience [15:56] Marketing Lesson #2: Pointy Characters Win — Stop Regressing to the Mean [23:14] B2B Is Still Consumer: Everyone Is a Person Making a Personal Decision [26:35] Marketing Lesson #3: Brand Experience — Rose Apothecary and the Bank Analogy [29:11] Marketing Lesson #4: The Rosebud Motel and the Power of Positioning [32:18] The Name, the Pun, and the Juxtaposition of Lowbrow and Highbrow [36:21] The Audacity of the Arc: Why Schitt's Creek Ended on Purpose [39:07] Final Thoughts and Takeaways Links Connect with Jason on LinkedIn Learn more about Forter About Remarkable! Remarkable! is created by the team at Caspian Studios, the premier B2B Podcast-as-a-Service company. Caspian creates both nonfiction and fiction series for B2B companies. If you want a fiction series check out our new offering - The Business Thriller - Hollywood style storytelling for B2B. Learn more at CaspianStudios.com. In today's episode, you heard from Ian Faison (CEO of Caspian Studios) and Meredith Gooderham (Head of Production). Remarkable was produced this week by Meredith Gooderham, edited by Jon Goldberg, and our theme song is “Solomon” by FALAK. Create something remarkable. Rise above the noise. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Seeking shelter from the run, a courting couple find themselves in an apparently abandoned "Waxworks" and become startled by its chamber of horrors...This original recording is an audio presentation by Jasper L'Estrange for EnCrypted Horror. “WAXWORKS” by W. L. George, 1922.

Episode 390.  James B and Eddie talk about MJ's death and Peter caught making out with Spider-Woman. Sponsored by: Tourism Department of Latveria Theme Music by Jeff Kenniston.  This Episode Edited by James B using Audacity and Cleanfeed.  Summaries written by James B and Eddie and Drooling Morris Maxwell.  Most Sound effects and music generously provided royalty free by www.fesliyanstudios.com and https://www.zapsplat.com/  Check out all the episodes on letsreadspiderman.podbean.com or wherever you get your podcasts. Check out our live meetup and Discord Channel here https://docs.google.com/document/d/1_mW6htjJUHOzlViEvPQqR-k68tClMGAi85Bi_xrlV7w/edit

The guys recap their Denver beer trip, including Coors, Prost, Bierstadt Lagerhaus, Left Hand, and a few memorable side quests. Then Tori Bleher joins the show to talk about Burgeon's origin story, their commitment to community and sustainability since 2016, their growing list of collaborations and partnerships, and how they keep releasing so many fresh beers without losing their identity. The episode also covers Burgeon's Pink Boots collaboration, The Audacity, their Carlsbad Firefighters Association beer, Stay Stoked, and the rotating Adventure Series IPA, Mountain Mode. Plus, Tori takes on the ILB lightning round!

In this episode of Gifts of the Wyrd, I'm joined by Jane Matthews, creator of Ogham: Divining the Celtic Way published by Weiser Books. We talk about the Celtic roots of ogham and Jane shares insights into why she created the deck. We discuss it as a divination tool, working with ogham in everyday practice, and connecting with them for meditation, guidance, and magical work. We also talk about some similarities between ogham and runes — how both were used as writing systems, are used as tools of magic and divination, and developing a deeper spiritual connection with them.  The deck comes with a detailed book with Jane's insights to help you learn or gain a different perspective of the ogham. The book includes meanings, spreads, and insights on some specific topics such as relationships, work, and health. Have a listen and get to know Jane and the ogham.  Ogham, Divining in the Celtic Way deck can be ordered from Weiser Books, your local metaphysical or book store, or online seller.  For more about Jane and her work, see https://www.janematthewsmedium.com/ ; Instagram @janematthewsmedium; Facebook @janematthewsmediumship You can find out about Jane's Ogham, Rune, mediumship, and other workshops at the World Divination Association (WDA) and all the cool things going on there at www.worlddivinationassociation.com # # # This deck was sent to me by the publisher. I have not been compensated for this interview or review, and my opinions are my own.  Create your podcast today! #madeonzencastr Subscribe to Substack: https://giftsofthewyrd.substack.com/ Instagram: @wyrdgifts1 Facebook: @GiftsoftheWyrd Email: giftsofthwyrd@gmail.com Order The Christmas Oracle Deck created by me and artist Vinnora at https://feniksshop.etsy.com follow FB/IG: @thechristmasoracle Rune sets also available at the etsy shop.  Music. Royalty free music from https://www.fesliyanstudios.com  Intro: Land of 8 Bits. Outro: JPOP.   Gifts of the Wyrd Logo Created by Xan Folmer.  Logo based on the Vanic boar created by Vanatru Priestess Ember of the Vanic Conspiracy. Studio recordings using Zencastr and Audacity.

Season 6Trust God's process.

"What ultimately happened to flight KL1760 Bremen-Paris...?"You hear the flight announcement at the airport, but things quickly spiral out of control. You also hear a reworking of the sound in the Musique Concrete style. A reporter's voice covering an attack in Paris, cinematic sound, and music building to a climax. A lingering Big Bang strikes the listener deep in the ears."The whole piece was composed in "old tape style" using a few microphones, a homemade oscillator bank, a piezo soundbox, a trumpet, and a violin."Mixed and remastered in the box in Audacity and Fluss."Bremen airport soundscape reimagined by La Chambre Sonore.

CONNECT, GROW, GIVE at https://theassembly.org/

A bored barrister, stranded by rain in a lonely mountain inn, meets the oddly persistent Mr Tallent who proceeds to read to him. Years later, a death, a will, and a box of interminable manuscripts draw the narrator back into Tallent's orbit, where questions of legacy, obsession, and a strangely lingering presence begin to surface. A wry, quietly uncanny tale about the burdens of bad art and the ghost it can leave behind.This original recording is an audio presentation by Jasper L'Estrange for EnCrypted Horror. “MR TALLENT'S GHOST” by Mary Webb, 1926.

Send us Fan MailAs Maygann continues, Dylan is joined by J.R., Matt and Jon from Strangers in Space to look at two Matthew Jacobs releases. First it's the documentary 'Doctor Who Am I'  Directed byVanessa Yuille & Matthew Jacobs, then they look at 'Puccini and the Doctor' featuring the Eighth Doctor, Charley & Audacity.

In this episode, Paul Andrews breaks down the essential steps for beginner guitarists to start recording themselves. He addresses common fears, explains why self-recording is one of the best ways to improve, and shares low-cost and easy ways to get started. Whether you're looking to track your progress or participate in Beginner Guitar Academy's Movie May challenge, this episode is packed with actionable advice and encouragement.Key Topics Covered1. Why Recording Yourself MattersRecording acts as a “mirror” for your playing, exposing timing, technique, and areas for growth (04:05).It's an effective way to track progress and stay motivated (04:44).Helps combat the slow, granular nature of guitar progress that often leads to people quitting.2. Overcoming the Fear of RecordingPerfection is not required—your first recordings will likely feel awkward, and that's okay (09:33).Growth comes through repetition, not perfection; authenticity beats flawlessness (11:29).3. Getting Started: Use Your PhoneYou don't need fancy gear—modern smartphones are more than capable (06:21).Practical tips:Position your phone at chest height for the best angle (07:38).Use natural lighting by facing a window (08:12).For electric guitar, keep amp volume low to avoid distortion; listen back and adjust as needed (08:45).4. Making Better Videos (Without Breaking the Bank)Simple improvements: camera angle, lighting, and clear audio (08:33).Backing tracks make your recordings more musical and enjoyable (12:00).Use headphones when playing along with backing tracks (12:29).Record multiple takes—don't expect to nail it on the first try (12:40).Watch yourself back with curiosity, not criticism—look for ways to improve (13:32).5. Stepping Up: Basic Recording GearWhen you're ready, consider an audio interface (Focusrite Scarlett Solo, etc.) and a simple USB mic (15:02).DAW (Digital Audio Workstation) software suggestions: GarageBand, Audacity, Reaper (17:03).Start with what you have; don't get stuck in “gear acquisition syndrome” (18:59).6. Building Confidence & The Value of RecordingRegular recording boosts confidence, reduces nerves about playing for others, and gets you comfortable making mistakes (19:18).Community HighlightsMovie May Challenge: Record and post yourself playing in the Beginner Guitar Academy community for a chance to win a $50 Guitarshirts voucher! (20:13)Goal: Build confidence, document progress, and encourage each other—NOT to create perfect performances.Paul Andrews's Main Takeaway“Start simple: use your phone, record short clips, do not chase perfection, and just document the journey.” (19:43)Resources MentionedBeginner Guitar Academy Community: Sign up for a 14-day trial for just $1 to access workshops and get feedback.New Workshop: Learn to play 5 classic Rolling Stones riffs (02:01).Recommended Entry-Level Audio Interfaces: Focusrite Scarlett Solo, Scarlett 2i2, Personas Audiobox.Free Recording Software: GarageBand, Audacity, Reaper.Backing Tracks: Search YouTube for “12 bar blues backing track” or “acoustic jam backing track”.Call to ActionChallenge for listeners: Grab your phone, record yourself playing, and (if you like) share it in the community—or keep it for yourself to track progress (20:43).ConnectFor feedback, questions, or to join the Beginner Guitar Academy, visit the community and connect with Paul Andrews.

What if the thing standing between you and your next level… isn't strategy? What if it's audacity? In this episode of YES, WOMAN, Carina dives into the conditioning that keeps women quiet, careful, "humble," and afraid to fully claim what they want. From money, purpose, and visibility… to dancing wildly at a wedding without caring who's watching… this conversation is about what becomes possible when a WOMAN stops shrinking herself to make other people comfortable. This is the episode for the WOMAN who knows she's meant for more, but still hears the voice asking: "Who do you think you are?" Powerful Moments From This Episode "If there's one thing we as women need to get better at in order to fulfill our dreams… it's audacity." "What you want wants you." "What's riskier? Being thought of as rude for asking… or dying knowing you never tried?" "If you're not full of yourself, who's going to be full of you?" "The audacity to ask is the difference between women who achieve their dreams and women who don't."   If this episode moved you, send it to the WOMAN in your life who's ready to stop waiting and start claiming what she truly wants. And if you haven't already, subscribe to YES, WOMAN for weekly conversations on feminine power, purpose, joy, audacity, and becoming fully alive. ✨ Ready to stop watching your life from the sidelines and start becoming the WOMAN who goes for it? Join MORE: 21 Days of Audacity - carinrockind.com/audacity 

A look into how Mother's Day illustrates the effective strategy to absorb and negate threats to the status quo. Then, how a recent decision by the majority of the United States Supreme Court Justices to deem Section 2 of The Voting Rights Act of 1965 "unconstitutional" is the latest step in a decades-long effort to compromise votes from minorities. Why the scariest thing about the Andes strain of the Hantavirus is how vulnerable the U.S. is with anti-vax, roadkill obsessed idiots in charge, and learning more about a road-tripping reality show starring our current Secretary of Transportation that highlights how tone deaf and indifferent this administration is as gas prices continue to soar. Lastly, how a new golden statue offers more grim insight into the Epstein files and the boldness of men who benefitted from sex trafficking.Check your voter registration, find your polling location, or contact your representatives via USA.GOV, VOTE.GOV, and/or the "5 Calls" app.All opinions are personal and not representative of any outside company, person, or agenda. This podcast is hosted by a United States citizen, born and raised in a military family that is proud of this country's commitment to free speech. Information shared is for entertainment purposes only and is cited via published articles, legal documents, press releases, government websites, executive orders, public videos, news reports, and/or direct quotes and statements, and all may be paraphrased for brevity, presented satirically, and in layman's terms.“I love America more than any other country in the world and, exactly for this reason, I insist on the right to criticize her perpetually.” - James Baldwin Hosted on Acast. See acast.com/privacy for more information.

This week The Tiny Stage is on-location from The Audacity Music Festival. Audacity was founded and produced by Thunderbolt Productions and held at Town River Landing in Bridgewater on Saturday, May 9. Featured acts/interviews include Gracie Grace and All The Good Boys, Nate Ramos, Laroy Streat, Total Strangers, Highwater Haulers, and Never Gonna Make It. Audacity was also held to raise awareness of The Fire For Effect foundation in Bridgewater whose mission is to honor and empower veterans, first responders, and their families by providing essential resources, support, and community-building initiatives that foster resilience, restore hope, and strengthen the fabric of our community. Learn more at https://www.ffefinc.org. 

Zach Galifianakis was on the road to become a huge blockbuster actor. At the height of his fame he kind of did the unexpected – he moved to a small rural town in Canada. He has kept working in showbiz, but lately has more important things to do like tend to his garden. Zach joins us to talk about his latest projects The Audacity and This is a Gardening Show. Plus, what it's like to be raising his kids in Canada and how his neighbors react to his fame. Spoiler: they could not care less and he likes it that way.See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

Episode 389.  James B and Eddie discuss whether Peter should divorce MJ and how much the 1999 comics should cover the hearings.  Plus Eddie makes some big changes by considering two new jobs and finally bringing in a sponsor to the podcast. Sponsored by Big Bald Boss Cream Theme Music by Jeff Kenniston.  This Episode Edited by James B using Audacity and Cleanfeed.  Summaries written by James B and Eddie and Hulk.  Most Sound effects and music generously provided royalty free by www.fesliyanstudios.com and https://www.zapsplat.com/  Check out all the episodes on letsreadspiderman.podbean.com or wherever you get your podcasts. Check out our live meetup and Discord Channel here https://docs.google.com/document/d/1_mW6htjJUHOzlViEvPQqR-k68tClMGAi85Bi_xrlV7w/edit

Audacity

In this episode, we're getting back to a BIG conversation....big moves! Big AUDACIOUS moves! Like, stepping into a version of you who doesn't wait to feel ready, doesn't ask for permission, & doesn't overthink if it will work… you just MOOOVE. And that's how things start moving with you. When I really look back at my life, every major shift came from that type of audacity. NOT from certainty. NOT from having it all figured out before I dove in. Just from going and being brave. I had so much fun recording this episode and reminiscing. This episode is really about that shift - choosing the version of you who just goes for it, even while fear is still very much present. Because spoiler: fear doesn't go away. You just stop letting it be in charge!!  May is AUDACITY MONTH in Dreamaway. (Schedule below)   ⭐️  Join us in the premier Dreamaway Membership for so many resources including 40+ Dreamaway-exclusive tapping sessions (90 minutes of deep-dive subconscious rewiring/EFT tapping), visualizations, 40+ tapping "Money Dates" (abundance programming), daily tapping videos, weekly energy readings, astrological updates, and so much more! https://haleyhoffmansmith.com/dreamaway   @dreamawaymembership on IG   Try a Taste of Dreamaway for FREE: https://www.haleyhoffmansmithprograms.com/offers/y5bMkDqb/checkout   Order my book, You Have the Magic:  https://youhavethemagic.com/  @haleyhoffmansmith on IG/TikTok   90 MIN SESH: AUDACITY. SATURDAY, MAY 23RD 11AM-12:30PM ET. MEOW!!! This session is a full reset around how boldly you show up to your life and those BIG DREAMS. We're clearing the hesitation, self-doubt, overthinking, and that subtle feeling of "am I allowed to do this?" at the root. Because it's NOT a lack of ambition - you know what you want!!!… it's a lack of permission & full throttle confidence to do the bold, WOW thing. We'll install a new baseline where boldness feels natural, action feels exciting, and going after what you want feels like a given…like, shut your laptop, and you're off to the races! Time to send that cold email, promote yourself boldly, make the ask, share the thing, and put yourself fully in the running. 

Episode 388  James B and Eddie go crazy for Vampires and Mobsters with the Kingpin and Morbius. Plus and a whole host of special guests appear while Jill Stacy and Peter continue their flirtmance and MJ and Peter's marriage continues to struggle. Sponsored by: Marc Spector and Associates Theme Music by Jeff Kenniston.  This Episode Edited by James B using Audacity and Cleanfeed.  Summaries written by James B and Eddie and Mutt.  Most Sound effects and music generously provided royalty free by www.fesliyanstudios.com and https://www.zapsplat.com/  Check out all the episodes on letsreadspiderman.podbean.com or wherever you get your podcasts. Check out our live meetup and Discord Channel here https://docs.google.com/document/d/1_mW6htjJUHOzlViEvPQqR-k68tClMGAi85Bi_xrlV7w/edit

Megan Thee Stallion and Klay Thompson has been all over everyone's socials, and I am giving my opinion on the whole thing.  We talk to some callers weighing in on the matter too, and then we go on a run of calls which truly puts the audacity of men on full display. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Simon Helberg talks about early career auditions, as well as his new show “The Audacity” on AMC. Johhhana Goines is back, talking about signs, milk, concrete, and her other side hustles. And train conductor Mr. Toots warns of impending doom on Kushtopia! Don't forget to check out the Comedy Bang! Bang! Action Figures at shop.figurecollections.com and go to actionfigurecellar.com for international purchases. If you want more great episodes of Comedy Bang! Bang! become a subscriber at comedybangbangworld.com. We have all of the past episodes from the archives, every live show, ad-free new episodes, and original shows like CBB Presents and Scott Hasn't Seen. Find more great Comedy Bang! Bang! merch at https://www.podswag.com/collections/comedy-bang-bang Get access to all the podcasts you love, music channels and radio shows with the SiriusXM App! Get 3 months free using this show link: https://siriusxm.com/cbb Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

President Trump attacks Pope Leo as "weak on crime" in a long social media screed before posting an AI-generated photo of himself as Christ healing the sick. JD Vance fails to broker a peace deal with Iran, Trump announces plans to reopen the Strait of Hormuz by blockading it, a horrifying scandal upends the race for California governor, and Democrats' Senate hopes show signs of life. Then, LA councilmember Nithya Raman stops by the studio to talk about her campaign for LA mayor and how she plans to tackle the city's most pressing crises: housing and homelessness.For a closed-captioned version of this episode, click here. For a transcript of this episode, please email transcripts@crooked.com and include the name of the podcast.