| Paper: | SLP-P19.8 | ||
| Session: | Model-based Robust Speech Recognition | ||
| Time: | Friday, May 19, 10:00 - 12:00 | ||
| Presentation: | Poster | ||
| Topic: | Speech and Spoken Language Processing: Confidence Measures and Rejection algorithms | ||
| Title: | AN IMPROVED MANDARIN KEYWORD SPOTTING SYSTEM USING MCE TRAINING AND CONTEXT-ENHANCED VERIFICATION | ||
| Authors: | JiaEn Liang, Meng Meng, XiaoRui Wang, Peng Ding, Bo Xu, Chinese Academy of Sciences, China | ||
| Abstract: | 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. | ||
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