The Spectrogram and the Gabor Transform 

Wonderful!

Glad it was helpful!

I'm so glad!

Glad you like it!

Wow, thanks!

SUE RU-vid! You've been scarred for life!

Glad you liked it!

Thanks! Maybe I'll make one on the S-transform sometime.

You can record the video with backwards writing, then mirror the video in an editor afterwards. :)

I can't promise I'll make one, but I will add it to the list.

You are right -- and yes, in control applications, the spectrogram will be computed continuously with a sliding window.

Thank you! Cheers!

I think so. Modern voice recognition uses recurrent neural networks, but the spectrogram can be very useful here too.

Mr Brunton said some a little misleading information. Gabor transform was the first time-frequency representation of signals, it is special case of STFT (because STFT (Short-Time Fourier Transform) can have any sliding window, Gabor transformation is done using only Gaussian window; there is also Triangular, Hamming, Hann, Blackmann and many others). Each of them has advantage and disadvantage - e.g. wider first lobe in frequency means suppressed the others and vice versa. It always depends on the use and purpose of the analysis. For audio signals, the most common window is Hann window (it doesn't have so sharp edges, e.g. like triangular, it is made by harmonic function - cosinus, so it is more smooth but its also wider for the first frequency lobe). The most common spectrogram is computed with STFT (Fourier T. in general), not Gabor transform. Mel-spectrogram is little different because it uses "mels" - Mel is a unit from psychoacoustic for a subjective melody; it also uses cosine transform but in short, it is another time-frequency representation of a signal and it tries to simulate or imitate human hearing and musical perception. Mel-spectrum (and kepstrum) is commonly used for research purposes of MIR (Music Information Retrieval) because the signal representation is usually closer to the subjective aspects of human hearing and thus is better for most of the applications (so far).

@@MrKrvo Ok, I got it. Thanks for your time.

@@ffelixvideos No problem.

Thanks for the great extra information!

@@MrKrvo Thanks for this !

typos will not be dealt with, it to much to read. so guess

I got my answer from the next video. Thank you :)

This is indeed one of the big open challenges that people are working on. Can you imagine if researchers could create an algorithm that would generate new Vivaldi?

@@Eigensteve what exactly is the open challenge? If you can write an algorithm to write mew music from scratch? But it would probsbly just be random stitching together of notes from existing pieces wouldn't it?