NDLI: High performance Chinese Spoken Term Detection based on term expansion

Content Provider	IEEE Xplore Digital Library
Author	Wei Li Ji Wu Ping Lv
Copyright Year	2010
Description	Author affiliation: Dept. Electronic Engineering, Tsinghua University, Beijing, China (Wei Li; Ji Wu; Ping Lv)
Abstract	This paper mainly focuses on improving the performance of Chinese Spoken Term Detection (S TD) systems using words as searching units. These systems are designed to find instances of particular phrases (called Terms) in voices. Terms are usually segmented into word sequences and searched with voices' recognition results. Mismatches between recognition results and word-segmentation might affect their performance. To solve this problem, two algorithms are designed to expand the searching spaces. Th e exp anded algorithms improve systems' performance while lead to a side-effect for its efficiency. To speed up the retrieval tasks, the Finite State Automation (FSA) is used. A token-passing algorithm is the n developed for fast search. Experiments have shown that the proposed term expansion method could effectively improve the STD system's performance. And using FSA with token-passing algorithm to search could effectively improve searching efficiency.
Starting Page	430
Ending Page	434
File Size	113067
Page Count	5
File Format	PDF
ISBN	9781424462445
e-ISBN	9781424462469
DOI	10.1109/ISCSLP.2010.5684852
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-29
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis term expansion word segmentation Text recognition Finite State Automation Conferences Redundancy Chinese Spoken Term Detection Speech recognition token passing Speech Minimization
Content Type	Text
Resource Type	Article

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