![]() We also compare their performance by newly proposed windowing techniques and conventional single-taper technique. This study shows investigations on reducing variance for the classification of two different voice qualities (normal voice and disordered voice) using multitaper MFCC features. However, MFCC features are usually calculated from a single window (taper) characterized by large variance. ![]() ![]() The Mel Frequency Cepstral Coefficients (MFCCs) are widely used in order to extract essential information from a voice signal and became a popular feature extractor used in audio processing.
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