Utterance partitioning with acoustic vector resampling for GMM–SVM speaker verification-Reference-Cited by-同舟云学术

Utterance partitioning with acoustic vector resampling for GMM–SVM speaker verification

Published:2011-01 Issue:1 Volume:53 Page:119-130
ISSN:0167-6393
Container-title:Speech Communication
language:en
Short-container-title:Speech Communication

Author:

Mak Man-Wai,Rao Wei

Publisher

Elsevier BV

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Linguistics and Language,Language and Linguistics,Communication,Modeling and Simulation,Software

Reference37 articles.

1. Effectiveness of linear prediction characteristics of the speech wave for automatic speaker identification and verification;Atal;J. Acoust. Soc. Amer.,1974

2. Score normalization for text-independent speaker verification systems;Auckenthaler;Digital Signal Process.,2000

3. Bar-Yosef, Y., Bistritz, Y., 2009. Adaptive individual background model for speaker verification. In: Interspeech, pp. 1271–1274.

4. Guide to Biometrics;Bolle,2004

5. Bolle, R.M., Ratha, N.K., Pankanti, S., 1999. Evaluating authentication systems using bootstrap confidence intervals. In: Proc. AutoID’99, pp. 9–13.

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