Utterance verification based on support vector machine

被引：0
|
作者：
Yan, BF [1 ]
Zhu, XY [1 ]
机构：
[1] Tsinghua Univ, State Key Lab Intelligent Technol & Syst, Beijing, Peoples R China
来源：
IC-AI '04 & MLMTA'04 , VOL 1 AND 2, PROCEEDINGS | 2004年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we present an approach to recognition confidence scoring and techniques for integrating confidence scores to make final decision in speech recognition. The measure is useful for rejecting utterances that contain out-of-vocabulary words. We derive a feature vector consisting of the filler-based posterior probability parameters. An accept/reject classifier is trained to produce a single confidence score for a hypothesis. We train and test a support vector machine (SVM) classifier, then compare the results with other statistical classification methods in the experiments.
引用
收藏
页码：1033 / 1036
页数：4
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