论文信息 - Speaker recognition based on source coding approaches

Speaker recognition based on source coding approaches

The use of nonmemoryless source coders in speaker recognition problems is studied, and the effects of source variations, including speaking inconsistency and channel mismatch, in source coder designs for the intended application are discussed. It is found that incorporation of memory in source coders in general enhances the speaker recognition accuracy but that more remarkable improvements can be accomplished by properly including potential source variations in the coder design/training. An experiment with a 100-speaker database shows a 99.5% recognition accuracy.<<ETX>>

Biing-Hwang Juang | Frank K. Soong

[1] Robert M. Gray,et al. An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[2] A. Gray,et al. Long-term feature averaging for speaker recognition , 1977 .

[3] Biingh-Wang Juang. Design and performance of trellis vector quantizers for speech signals , 1988, IEEE Trans. Acoust. Speech Signal Process..

[4] Biing-Hwang Juang,et al. A vector quantization approach to speaker recognition , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5] D. Wong,et al. Very low data rate speech compression with LPC vector and matrix quantization , 1983, ICASSP.

[6] Aaron E. Rosenberg,et al. Evaluation of a vector quantization talker recognition system in text independent and text dependent modes , 1987 .