Human-computer Interactive Oral Translation Methods and Related Issues

Nowadays, machine translation technology has penetrated into daily life and is a commonly used auxiliary tool for cross-language communication. Therefore, the translation for spoken language is particularly important. In addition to its scientific and engineering significance, oral translation also contains rich economic and social benefits. The purpose of this paper is to study human-machine interactive spoken language translation methods and related issues. Firstly, the concept of interpreting and related work at home and abroad are introduced, and then the machine translation system and interpreting system, which are important components of interpreting, are introduced respectively. The acoustic model and statistical language model based on HMM are established. In the process of creating a statistical language model, in order to solve the problem of sparse data, we adopted a modeling method combining word-based language model and part-of-speech-based language model. Finally, the system is tested by use cases, and the correct rate of oral translation is above 90%.