基于查询扩展的中文语音高效检索

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摘要中文语音检索系统用于快速准确地在中文语音文档中定位用户查询。典型实现方案对语音文档进行识别后建立索引，对查询串进行分词并以分词结果检索。检索过程中出现的查询分词与识别结果不匹配将影响系统性能。为解决该问题，产生多种查询分词结果，并对其进行前后缀扩展后检索。为解决因扩展带来的检索内容过多，用时较长的问题，引入有穷自动机压缩扩展，在此基础上设计基于令牌的搜索算法高效检索。实验证明，对查询的多分词与前后缀扩展可以使检索EER相对提升50%~70%，引入FSA可压缩检索空间，使得检索速度提升近30倍。

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关键词 ：中文语音检索, 分词, 查询扩展, 有穷自动机, 基于令牌的搜索

Abstract：The aim of Chinese voice retrieval systems is to locate query texts in audio files fast and precisely. In a typical implementation of the system, voice files are recognized and stored in index. The system segments each query into a word sequence and uses the sequence to search. The mismatch between query segmentation and recognition can influence systems performance. To solve this problem, multiple segmentation results and prefix-suffix expansions have been used to broaden the original query. The retrieval process is on the basis of the expansions outputs. Query expansion generates a lot of outputs, which slows down the retrieval speed. In order to increase the systems efficiency, the Finite State Automata (FSA) is introduced to compress query expansions. And a Token-based search algorithm is used for fast search. Experimental results show that the query expansion leads the systems EER to improve about 50%~70% relatively. The FSA compresses the retrieval space, and raises the retrieval speed nearly 30 times.

Key words： Chinese Speech Retrieval Word Segmentation Query Expansion Finite State Automata (FSA) Token-based Search

收稿日期: 2010-09-25

ZTFLH:

TP319.3

作者简介: 李伟，男，1981年生，博士，主要研究方向为面向内容的语音搜索。E-mail:w-li-06@mails。tsinghua。edu。cn。吴及，男，1973年生，副教授，主要研究方向为语音识别、多媒体信息处理。吕萍，女，1974年生，副研究员，主要研究方向为语音信号处理。

引用本文:

李伟吴，吕萍. 基于查询扩展的中文语音高效检索[J]. 模式识别与人工智能, 2011, 24(4): 561-566. LI Wei, WU Ji, L Ping. Query Expansion Based High Performance Chinese Voice Retrieval. , 2011, 24(4): 561-566.

链接本文:

http://manu46.magtech.com.cn/Jweb_prai/CN/ 或 http://manu46.magtech.com.cn/Jweb_prai/CN/Y2011/V24/I4/561

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