End-To-End Algorithm Optimization and Implementation Based on Speech Translation

Zheng Yang
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Abstract

Speech translation is the process of automatically translating the commands from the speech signals of the source language into the text of the specified language by using machine completion instructions. The main operation method now is to associate speech recognition with machine translation. Because speech recognition, machine translation and speech translation are essentially the transformation from one sequence to another, and the end-to-end architecture can also be applied to speech recognition and machine translation, the researchers studied end-to-end speech translation. Because the integration of speech recognition and machine translation into one model modeling makes the input sequence and output sequence more difficult and cumbersome, it is necessary to carry out more difficult training on the model and analyze more training data. On this basis, this paper studies end-to-end speech translation and related training methods respectively.
基于语音翻译的端到端算法优化与实现
语音翻译是利用机器补全指令将源语言的语音信号中的命令自动翻译成指定语言文本的过程。现在主要的操作方法是将语音识别与机器翻译相关联。由于语音识别、机器翻译和语音翻译本质上是一个序列到另一个序列的转换,端到端架构也可以应用于语音识别和机器翻译,因此研究人员研究了端到端语音翻译。由于将语音识别和机器翻译集成到一个模型建模中,使得输入序列和输出序列变得更加困难和繁琐,因此需要对模型进行更困难的训练,分析更多的训练数据。在此基础上,本文分别对端到端语音翻译和相关训练方法进行了研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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