Computes mel frequency cepstral coefficient (MFCC) features from a given speech signal. The speech signal is first preemphasised using a first order FIR filter with preemphasis coefficient. The preemphasised speech signal is subjected to the short-time Fourier transform analysis with a specified frame duration, frame shift and analysis window function. This is followed by magnitude spectrum computation, followed by filterbank design with M triangular filters uniformly spaced on the mel scale between lower and upper frequency limits. The filterbank is applied to the magnitude spectrum values to produce filterbank energies (FBEs). Log-compressed FBEs are then decorrelated using the discrete cosine transform to produce cepstral coefficients. Final step applies sinusoidal lifter to produce liftered MFCCs that closely match those produced by HTK. Demo scripts are included.
Kamil Wojcicki (2021). HTK MFCC MATLAB (https://www.mathworks.com/matlabcentral/fileexchange/32849-htk-mfcc-matlab), MATLAB Central File Exchange. Retrieved .
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