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Implementation of Embedded Technology-Based English Speech Identification and Translation System

Zheng Zeng

Chengdu Technological University, Chengdu, Sichuan 611730, China

* Corresponding Author: Zheng Zeng, email

Computer Systems Science and Engineering 2020, 35(5), 377-383. https://doi.org/10.32604/csse.2020.35.377

Abstract

Due to the increase in globalization, communication between different countries has become more and more frequent. Language barriers are the most important issues in communication. Machine translation is limited to texts, and cannot be an adequate substitute for oral communication. In this study, a speech recognition and translation system based on embedded technology was developed for the purpose of English speech recognition and translation. The system adopted the Hidden Markov Model (HMM) and Windows CE operating system. Experiments involving English speech recognition and EnglishChinese translation found that the accuracy of the system in identifying English speech was about 88%, and the accuracy rate of the system in translating English to Chinese was over 85%. The embedded technology-based English speech recognition and translation system demonstrated a level of high accuracy in speech identification and translation, demonstrating its value as a practical application. Therefore, it merits further research and development.

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APA Style
Zeng, Z. (2020). Implementation of embedded technology-based english speech identification and translation system. Computer Systems Science and Engineering, 35(5), 377-383. https://doi.org/10.32604/csse.2020.35.377
Vancouver Style
Zeng Z. Implementation of embedded technology-based english speech identification and translation system. Comput Syst Sci Eng. 2020;35(5):377-383 https://doi.org/10.32604/csse.2020.35.377
IEEE Style
Z. Zeng, "Implementation of Embedded Technology-Based English Speech Identification and Translation System," Comput. Syst. Sci. Eng., vol. 35, no. 5, pp. 377-383. 2020. https://doi.org/10.32604/csse.2020.35.377

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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