Improving automatic speech recognizer of voice search using system combination

Authors:
Ta Li;Weiqun Xu;Jielin Pan;Yonghong Yan
Affiliations:
ThinkIT Speech Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, P.R. China;ThinkIT Speech Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, P.R. China;ThinkIT Speech Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, P.R. China;ThinkIT Speech Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, P.R. China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
Year:
2009

Citing 3
Cited 0

Fundamentals of speech recognition

Fundamentals of speech recognition
The forward-backward search algorithm

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A One-Pass Real-Time Decoder Using Memory-Efficient State Network

IEICE - Transactions on Information and Systems

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Abstract

Voice search is the technology that enables users to access information using spoken queries. Automatic speech recognizer (ASR) is one of the key modules for voice search systems. However, the high error rate of the state-of-the-art large vocabulary continuous speech recognition (LVCSR) is the bottleneck for most voice search systems. In this paper, we first build a baseline system using language model (LM) with domain-specific information. To improve our system, we propose a forward-backward LVCSR system combination method to decrease the search errors in speech recognition. Experiment results show that our proposed method improves the performance of speech recognition by 5.7% relative character error rate (CER) reduction.