Combination of hidden Markov models with dynamic time warping for speech recognition

被引：0
|
作者：
Axelrod, S [1 ]
Maison, B [1 ]
机构：
[1] IBM Corp, Thomas J Watson Res Ctr, Yorktown Hts, NY 10598 USA
来源：
2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PROCEEDINGS: SPEECH PROCESSING | 2004年
关键词：
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
We combine Hidden Markov Models of various topologies and Nearest Neighbor classification techniques in an exponential modeling framework with a model selection algorithm to obtain significant error rate reductions on an isolated word digit recognition task. This work is a preliminary investigation of large scale modeling techniques to be applied to large vocabulary continuous speech recognition.
引用
收藏
页码：173 / 176
页数：4
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