Audio Signal Processing for Machine Learning

In this series, you'll learn how to process audio data and extract relevant audio features for your machine learning applications.

First, you'll get a solid theoretical understanding of key audio digital signal processing topics such as the Fourier Transform, Mel-Spectrograms, and sound waves. You'll also get your hands dirty by processing audio data with the industry-standard library for audio/music processing.

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[araaudio]

When I found your Channel I found a great treasure. When you choose a subject you are playing on my soul strings. Really I am grateful.

[normalperson]

This is exactly what I was thinking of working on as a machine learning project. Thanks.

[chukypedro]

It took me 3*10*8 secs to subscribe to your channel because you are a lifesaver. exactly what I needed for my side project at this point.

[tyhuffman]

Love it! I'm a vibration analyst, we listen to machines. Thank you for putting this together.

[suyashramteke]

I would like to thank you and appreciate for all the effort that you are taking to make these videos. I am a graduate student who is passionate about signal processing and machine learning in audio and your content is the best so far I have found. Since there are very less resources these are all the more helpful

[NierChristopher]

Thanks very much for this series. Your code example and patient explanation really helped me a lot for getting started in the field of AI audio signal processing

[rafaelsetyan]

I have just finished the series and I am telling you if you started, go until the end. Thanks a lot Valerio

[D]

Wow, thank you for putting this together! Though I'm a musician, I don't have a background in audio signal processing and it's been a struggle to find a good compiled source of information for deep learning specific to audio domain problems.

[vadimshatov]

I just found an incredible YouTube channel. Thank you so much!

[proyectosinformatica]

Wow, I was watching the main series of Audio classification with Python you made. And when you explained the MFCCs passing as input to a CNN in your example you put this [100, 13, 1] as an input shape and you said the 100 came from the samples in the audio file (51200) / the hop length of 512 and I was about to ask where did the 51200 come from. Maybe with this series I'll be able to understand that and also the Mel Spectrogram which is something that I wanted to know about for the longest time from a non-so mathematical perspective, but rather a more code applicable one. Greetings to you and thank you very much

[BirnieMac]

Thank you for this series chief; I'd been looking at trying to build a detection algorithm using a fourier transform to produce spectrograms and the theory refresher has been super
super useful


Plus confirmation that I wasn't barking up the wrong tree into how to approach it is always nice

[anthonychianain]

Thank you very much for the course... have been looking for something like this for a long time

[hamidmojarrad]

Your channel sounds exactly what I was looking for as an ASR researcher. Thank you for these informative videos.
Do you have tutorials on Montreal Forced Alignment too?

[TheElfurio]

Thanks a lot for your great series, Valerio! This helps me a lot with my current signal processing project.

[frostvision]

Very excited for this Valerio! Your videos have helped me immensely at understanding audio and ML/DL in general.

Quick question: Do you have any recommendations or resources or plan to contribute some discussion about adding environmental noise to audio? I would love to talk about data augmenting with noise / other sound files into existing signals with proper RMS and SNR as to not overpower the desired signal. I'd love to see how to add radio static / random noises into audio for purpose of simulating target radio speech data.

Thanks for everything!

[BorisGrishenco]

You are amazing!. Super interesting topics including regarding how to publish a paper.

[apidas]

thank you Valerio, a lot of knowledge in this series. I'd donate superchat to this video but you don't have them enabled.

[shubh]

I am working on a project and man this is reall helpful. Thankew so much

[frapastique]

Awesome, you’re covering the topics that I need for my actual project. Thank you and keep it up

[smilebig]

I was desperately waiting for this series. 😀