Title: Chinese question speech recognition integrated with domain characteristics

Authors: Shengxiang Gao; Dewei Kong; Zhengtao Yu; Yang Luo; Jianyi Guo; Yantuan Xian

Addresses: School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China ' School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China ' School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China ' School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China ' School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China ' School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China

Abstract: Aiming at domain adaptation in speech recognition, we propose a speech recognition method for Chinese question sentence based on domain characteristics. Firstly, by virtue of syllable association characteristics implied in domain term, syllable feature sequences of domain terms are used to construct the domain acoustic model. Secondly, in decoding process of domain-specific Chinese question speech recognition, we utilise domain knowledge relationship to optimise and prune the speech decoding network generated by language model, to improve continuous speech recognition. The experiments on tourist domain corpus show that the proposed method gets the accuracy of 80.50% on Chinese question speech recognition and the accuracy of 91.50% on domain term recognition.

Keywords: Chinese question speech recognition; domain characteristic; acoustic model library; domain terms; language model; domain knowledge library.

DOI: 10.1504/IJCSE.2019.101342

International Journal of Computational Science and Engineering, 2019 Vol.19 No.3, pp.325 - 333

Received: 10 Aug 2016
Accepted: 06 Feb 2017
Published online: 05 Aug 2019 *

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