Semantic Scholar Open Access 2020 7 sitasi

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

Zheng Zeng

Abstrak

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 English-Chinese 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.

Topik & Kata Kunci

Penulis (1)

Z

Zheng Zeng

Format Sitasi

Zeng, Z. (2020). Implementation of Embedded Technology-Based English Speech Identification and Translation System. https://doi.org/10.32604/csse.2020.35.377

Akses Cepat

Lihat di Sumber doi.org/10.32604/csse.2020.35.377
Informasi Jurnal
Tahun Terbit
2020
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.32604/csse.2020.35.377
Akses
Open Access ✓