An improved Mandarin keyword spotting system using mce training and context-enhanced verification

被引：0
|
作者：
Liang, JiaEn [1 ]
Meng, Meng [1 ]
Wang, XiaoRui [1 ]
Ding, Peng [1 ]
Xu, Bo [1 ]
机构：
[1] Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
来源：
2006 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-13 | 2006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：
The task of keyword spotting is to detect a set of keywords in the input continuous speech. The main goal of this work is to develop an improved mandarin keyword spotting (KWS) system for conversational telephone speech (CTS). In this paper, we propose an efficient online-garbage model based KWS system, which integrated with a word-level minimum classification error (MCE) training method and a novel context-enhanced verification method. Experiment showed that the proposed methods can reduce the Equal-Error-Rate (EER) of the system by 13.8% in relative.
引用
收藏
页码：1145 / 1148
页数：4
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