Abstract
Pitch information is known to be partially conveyed in Mel cepstral features that are commonly used for speaker recognition. In particular, for high pitched female speakers, and whenever average pitch varies significantly between enrollment and testing, the fine spectral structure introduced by the fundamental frequency was shown to degrade speaker recognition performance. This paper introduces a signal processing procedure termed depitch that attempts to remove pitch information from the speech signal. Recognition experiments carried out on the female subset of the NIST 2002 Speaker Recognition Evaluation show that by combining scores from a conventional and a depitched system, a substantial improvement in equal error rate is obtained for high pitched speakers and pitch-mismatched trials. Performing pitch/depitch score fusion is also shown to help alleviate the well-known problem of goat speakers.
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