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학술지 Weighted Finite State Transducer-Based Endpoint Detection Using Probabilistic Decision Logic
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저자
정훈, 이성주, 이윤근
발행일
201410
출처
ETRI Journal, v.36 no.5, pp.714-720
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.14.2214.0030
협약과제
14MS1500, 모바일 플랫폼 기반 대화모델 적용 자연어 음성인터페이스 기술 개발, 이윤근
초록
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.
키워드
Endpoint detection, Speech recognition, Weighted finite state transducer
KSP 제안 키워드
Based Approach, Cascaded decision, Data-Driven, Decision Knowledge, Decision logic, End Point Detection(EPD), Failure Rate, Finite state transducer, Frame-level, Knowledge-based, Non-speech