Robust speaker verification by combining MFCC and entrocy in noisy conditions
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DOI: 10.11591/eei.v10i4.2957
Abstract: Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used… read more here.
Keywords: speaker; robust speaker; speaker recognition; noisy conditions ... See more keywords