Speech Feature Extraction Using Gammatone Filters
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Resource Overview
GFCC (Gammatone Frequency Cepstral Coefficients) employs gammatone filterbanks for speech feature extraction, implementing auditory-inspired frequency analysis through optimized filter design and spectral processing.
Detailed Documentation
The GFCC technique utilizes gammatone filters for speech feature identification and extraction. This methodology plays a crucial role in obtaining significant information from speech signals through the GFCC algorithm, which applies gammatone filters to capture and analyze various acoustic characteristics. Implementation typically involves creating a gammatone filterbank with center frequencies spaced according to the Equivalent Rectangular Bandwidth (ERB) scale, followed by spectral analysis and cepstral coefficient calculation. Key processing steps include: designing filters with impulse responses mimicking human cochlear processing, computing energy outputs from each filter channel, applying logarithmic compression, and performing Discrete Cosine Transform (DCT) to decorrelate the features into final GFCC vectors.
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