Emotional data mining and DTW algorithms in English speech teaching recognition

被引:0
|
作者
Wang, Ning [1 ]
机构
[1] Xingtai Medical College, Xingtai, Hebet,054000, China
来源
Engineering Intelligent Systems | 2019年 / 27卷 / 03期
关键词
End-point detection methods - English phonetics - Operational efficiencies - Person recognition - Real-time software - Recognition algorithm - Speech recognition systems - Teaching efficiencies;
D O I
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中图分类号
学科分类号
摘要
The main research focus of this paper is the non-specific English spoken speech recognition method under the PC system. At the same time, this paper improves the detection method of speech endpoints, improves the recognition algorithm of speech recognition under PC, and uses the DTW algorithm to match the template, as it is easy to implement In addition, the endpoint detection method proposed in this paper improves the efficiency of speech recognition. Many English consonants are clear consonants but, when disturbed by noise, they are easily drowned. In the specific person recognition system, the recognition rate is higher. In the non-specific person recognition system, the recognition rate is lower. This paper explores the teaching of English phonetics recognition based on emotional data mining and dynamic time integration algorithm. In the actual application of speech recognition systems, there is a strong demand for real-time software functions, which requires improving the operational efficiency and running time of the system. Such a system can help to improve oral recognition and teaching efficiency in the English classroom. © 2 0 1 9 CRL Publishing Ltd
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页码:103 / 109
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