文章基本信息

标题：Weighted Finite State Transducer-Based Endpoint Detection Using Probabilistic Decision Logic
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作者：Chung, Hoon ; Lee, Sung Joo ; Lee, Yun Keun 等
期刊名称：ETRI Journal
印刷版ISSN：1225-6463
电子版ISSN：2233-7326
出版年度：2014
卷号：36
期号：5
页码：714-720
DOI：10.4218/etrij.14.2214.0030
语种：English
出版社：Electronics and Telecommunications Research Institute
摘要：In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.
关键词：Endpoint detection;speech recognition;Weighted Finite State Transducer