Neural Machine Translation for English-Assamese Language Pair using Transformer

Rudra Dutt, Tarun Aditya Kusupati, Akshat Srivastava, Basab Nath
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Abstract

Machine translation is a computer-based translation process that receives a set of words from a particular humanreadable language as input and outputs a second set of words in the intended human-readable language. Machine translation has assisted linguists and sociologists all across the world. A machine translation model may be statistical, rule-based, or based on neural networks. The Neural Machine Translation (NMT) model was introduced in response to the numerous drawbacks of rule- based and statistical-based machine translation models. This study adds a parallel corpus of Assamese and English and develops the NMT system, a transformer model with a self- attention mechanism. For translation from English to Assamese, the system received a higher bilingual evaluation understudy (BLEU) score of 7.6, and for translation from Assamese to English,a BLEU score of 23.2.
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基于Transformer的英语-阿萨姆语对神经网络机器翻译
机器翻译是一种基于计算机的翻译过程,它从一种特定的人类可读语言中接收一组单词作为输入,并以预期的人类可读语言输出第二组单词。机器翻译帮助了世界各地的语言学家和社会学家。机器翻译模型可以是统计的、基于规则的或基于神经网络的。神经机器翻译(NMT)模型是针对基于规则和基于统计的机器翻译模型的诸多缺陷而提出的。本研究增加了阿萨姆语和英语的平行语料库,并开发了NMT系统,这是一个具有自注意机制的变形模型。从英语到阿萨姆语的翻译,该系统获得了更高的双语评估替补分数(BLEU) 7.6分,从阿萨姆语到英语的翻译,BLEU得分为23.2分。
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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