Implementation of Minority Language Translation System Based on Android

Autor: Xiao su Tan, Wei Xiang, Yu Quan Mu
Rok vydání: 2019
Předmět:
Zdroj: 2019 4th International Conference on Computational Intelligence and Applications (ICCIA).
DOI: 10.1109/iccia.2019.00025
Popis: This paper designs a minority language translation system based on Android, which combines the development technology of TensorFlow building neural network. In addition, the Python-based flask framework helps us achieve data transmission, so that the translation of minority languages into Chinese or Chinese into minority languages, and in the form of deep learning, the above system can be used in practical applications to solve the communication barriers between ethnic minority areas and language lovers. We try to use the LSTM algorithm to realize the background translation of the system, and by comparing the translation results with the original text, we find that the translation results have a certain quality improvement over the traditional machine translation, rather than rigid mechanical translation. Therefore, it is hoped that a good translation system of minority languages can be realized.
Databáze: OpenAIRE