SPEAKER RECOGNITION USING SYLLABLE-BASED CONSTRAINTS FOR CEPSTRAL FRAME SELECTION

被引：14

作者：

Bocklet, Tobias ^{[1
]}

Shriberg, Elizabeth ^{[2
]}

机构：

[1] Univ Erlangen Nurnberg, D-8520 Erlangen, Germany

[2] SRI Int, Menlo Pk, CA 94025 USA

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS | 2009年

关键词：

Speaker recognition; higher-level features; GMMs; cepstral features; MFCCs; syllables;

D O I：

10.1109/ICASSP.2009.4960636

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

We, describe a new GMM-UBM speaker recognition system that uses standard cepstral features, but selects different frames of speech for different subsystems. Subsystems, or "constraints", are based on syllable-level information and combined at the score level. Results on both the NIST 2006 and 2008 test data sets for the English telephone train and test condition reveal that a set of eight constraints performs extremely well, resulting in better performance than other commonly-used cepstral models. Given the still largely-unexplored world of possible constraints and combinations, it is likely that the approach can be even further improved.

引用

页码：4525 / +

页数：2

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