Design and Development of College Tourism English Training System Based on Speech Recognition Technology
- 10.2991/978-94-6463-012-1_9How to use a DOI?
- Speech Recognition Technology; Tourism English; Practical Training System; Multi-Dimensional Evaluation
Based on language recognition technology, the author uses Web Audio API interface technology and Microsoft voice service to complete the construction of college tourism English training system in ASP.NET CORE environment. The practical training function of the system can simulate various sections in tourism activities and provide oral dialogue training in different situations, so as to facilitate the students majoring in tourism English to complete the corresponding knowledge and skills learning and listening, speaking and reading dialogue exercises. In addition, under the system evaluation function, voice recognition technology is used to convert the voice signals of students’ users into digital information, which is evaluated layer by layer from sentences, words and phonemes, and students’ English pronunciation is accurately analyzed and diagnosed from multiple dimensions such as pronunciation, intonation and fluency, and corresponding scores and guidance are given to facilitate students’ improvement. The construction of practical training system can solve the problem that students majoring in tourism English in colleges and universities can’t directly participate in teaching practice activities under the current epidemic situation. With the help of online practical training, it can break through the limitations of space and time, ensure that students can get more practical opportunities, and enhance their professional ability.
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Cite this article
TY - CONF AU - Wenyu Xu PY - 2022 DA - 2022/12/09 TI - Design and Development of College Tourism English Training System Based on Speech Recognition Technology BT - Proceedings of the 2022 International Conference on Educational Innovation and Multimedia Technology (EIMT 2022) PB - Atlantis Press SP - 66 EP - 75 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-012-1_9 DO - 10.2991/978-94-6463-012-1_9 ID - Xu2022 ER -