Vector quantization based Gaussian modeling for speaker verification
| Data(s) |
2000
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|---|---|
| Resumo |
Gaussian mixture models (GMMs) have become an established means of modeling feature distributions in speaker recognition systems. It is useful for experimentation and practical implementation purposes to develop and test these models in an efficient manner particularly when computational resources are limited. A method of combining vector quantization (VQ) with single multi-dimensional Gaussians is proposed to rapidly generate a robust model approximation to the Gaussian mixture model. A fast method of testing these systems is also proposed and implemented. Results on the NIST 1996 Speaker Recognition Database suggest comparable and in some cases an improved verification performance to the traditional GMM based analysis scheme. In addition, previous research for the task of speaker identification indicated a similar system perfomance between the VQ Gaussian based technique and GMMs |
| Formato |
application/pdf |
| Identificador | |
| Publicador |
IEEE |
| Relação |
http://eprints.qut.edu.au/45585/1/c45585P.pdf DOI:10.1109/ICPR.2000.903543 Pelecanos, J., Myers, S., Sridharan, S., & Chandran, V. (2000) Vector quantization based Gaussian modeling for speaker verification. In Proceedings of the 15th International Conference on Pattern Recognition, 2000, IEEE, pp. 294-297. |
| Direitos |
Copyright 2000 IEEE Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
| Fonte |
Faculty of Built Environment and Engineering; School of Engineering Systems |
| Palavras-Chave | #probability #speaker recognition #vector quantisation #Gaussian mixture models #NIST 1996 Speaker Recognition Database #feature distributions #speaker identification #speaker recognition systems #speaker verification #vector quantization based Gaussian modeling |
| Tipo |
Conference Paper |
