HTK MFCC MATLAB
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.
Citation pour cette source
Kamil Wojcicki (2024). HTK MFCC MATLAB (https://www.mathworks.com/matlabcentral/fileexchange/32849-htk-mfcc-matlab), MATLAB Central File Exchange. Récupéré le .
Compatibilité avec les versions de MATLAB
Plateformes compatibles
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- Signal Processing > Signal Processing Toolbox > Transforms, Correlation, and Modeling > Transforms > Discrete Fourier and Cosine Transforms >
- Signal Processing > Signal Processing Toolbox > Transforms, Correlation, and Modeling > Transforms > Cepstral Analysis >
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Inspiré par : Triangular Filterbank, File I/O for Cell Arrays, Framing Routines
A inspiré : Classification of musical genres using HMM.
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