MATEC Web Conf.
Volume 336, 20212020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|Number of page(s)||6|
|Section||Artificial Recognition and Application|
|Published online||15 February 2021|
Selection of acoustic modeling unit for Tibetan speech recognition based on deep learning
1 College of Computer Science and Technology, Qinghai Normal University, Qinghai Xining 810016, China
2 School of Computer Science and Technology, Southwest Minzu University, Sichuan Chengdu 610041, China
3 Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province, Qinghai Xining 810008, China
4 Key Laboratory of Tibetan Information Processing, Ministry of Education, Qinghai Xining 810008, China
* Corresponding author: firstname.lastname@example.org
The selection of the speech recognition modeling unit is the primary problem of acoustic modeling in speech recognition, and different acoustic modeling units will directly affect the overall performance of speech recognition. This paper designs the Tibetan character segmentation and labeling model and algorithm flow for the purpose of solving the problem of selecting the acoustic modeling unit in Tibetan speech recognition by studying and analyzing the deficiencies of the existing acoustic modeling units in Tibetan speech recognition. After experimental verification, the Tibetan character segmentation and labeling model and algorithm achieved good performance of character segmentation and labeling, and the accuracy of Tibetan character segmentation and labeling reached 99.98%, respectively.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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