# Feature Engineering

1. Fourier transform
   1. [youtube](https://www.youtube.com/watch?v=7Tk6BAJ3mm8)
2. [Read this first](https://jonathan-hui.medium.com/speech-recognition-feature-extraction-mfcc-plp-5455f5a69dd9), by Jonathan Hui - a/d, boost, Mel-frequency cepstral coefficients (MFCC), Perceptual Linear Prediction (PLP), Hanning vs Hamming, window, discrete fourier transform (DFT), IDFT.
3. Learning from Audio Series by mlearnere
   1. [Learning from Audio: Wave Forms](https://towardsdatascience.com/learning-from-audio-wave-forms-46fc6f87e016)
   2. [Learning from Audio: Time Domain Features](https://towardsdatascience.com/learning-from-audio-time-domain-features-4543f3bda34c)
   3. [Learning from Audio: Fourier Transformation](https://towardsdatascience.com/learning-from-audio-fourier-transformations-f000124675ee)
   4. [Learning from Audio: The Mel Scale, Mel Spectrograms, and Mel Frequency Cepstral Coefficients](https://towardsdatascience.com/learning-from-audio-the-mel-scale-mel-spectrograms-and-mel-frequency-cepstral-coefficients-f5752b6324a8)
   5. [Learning from Audio: Pitch and Chromagrams](https://towardsdatascience.com/learning-from-audio-pitch-and-chromagrams-5158028a505)
4. Spectrogram
   1. [Understanding the Mel Spectrogram](https://medium.com/analytics-vidhya/understanding-the-mel-spectrogram-fca2afa2ce53), [2](https://towardsdatascience.com/getting-to-know-the-mel-spectrogram-31bca3e2d9d0), [3](https://medium.com/hacking-media/beginner-guide-to-visualizing-audio-as-a-spectogram-in-python-65dca2ab1e61), [4](https://importchris.medium.com/how-to-create-understand-mel-spectrograms-ff7634991056), [delta deltas](https://www.youtube.com/watch?v=zxEnuPolylY)
5. Mel-frequency cepstral coefficients (MFCC) 
   1. [youtube](https://www.youtube.com/watch?app=desktop\&v=SJo7vPgRlBQ)


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