Emotional Data Mining and DTW Algorithms in English Speech Teaching Recognition

Authors

  • Ning Wang Xingtai Medical College, Xingtai, Hebei 054000, China

Abstract

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.

Keywords: Emotional data mining; Dynamic time integration algorithms; Speech recognition; Operational efficiency

Cite As

N. Wang, "Emotional Data Mining and DTW Algorithms in English Speech Teaching Recognition", Engineering Intelligent Systems, vol. 27 no. 3, pp. 103-109, 2019.


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Published

2019-09-01

Issue

Vol. 27 No. 3 (2019): International Journal of Engineering Intelligent Systems

Section

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