February 2020
Intermediate to advanced
328 pages
8h 19m
English
Content preview from Deep Learning with R Cookbook
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In the Getting ready section of this recipe, we used STFT to transform a sound wave into its frequency-amplitude representation. Further transformations can be applied to the wave spectrogram in order to compute the Mel-Frequency Cepstral Coefficients (MFCC). The Mel-Frequency Cepstrum (MFC) is used to represent sound in a short-term power spectrum. Mel-Frequency Cepstral Coefficients (MFCCs) make up an MFC that represents the spectral energy distribution of an audio signal. MFCC works on similar frequencies that can be captured by the human ear.
This is how MFCCs are calculated:
- An input signal is segmented into several frames, usually in the range of 20-40 ms.
- Then, for each frame, the power spectrum is calculated by the ...
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