ESCA Workshop on Automatic Speaker Recognition, Identification, and Verification
At present, most speaker identification systems use cepstral or linear prediction (IP) based features. The performance of these systems degrades significantly with the presence of noise in the training and/or the testing speech. To improve this performance, higher order statistics (HOS) or cumulant-based LF features are proposed. Using these features and singular value decomposition (SVD), it is shown that the performance of a speaker identification system can be improved considerably in the presence of additive white or colored Gaussian noise.
Bibliographic reference. Trent, Larry J. / Rader, Charles M. / Reynolds, Douglas A. (1994): "Using higher order statistics to increase the noise robustness of a speaker identification system", In ASRIV-1994, 221-224.