This paper describes the Machine Translation (MT) system submitted by the NLPRL team lor the Tamil - English Indie Task at WAT 2019. We presented the Neural Machine Translation (NMT) system based on the Transformer approach. Training and performance of the model are evaluated on the En-Tam corpus (An English-Tamil Parallel Corpus) collected by researchers at UFAL (Institute of Formal and Applied Linguistics). The evaluation of the model done using Adequacy, BLEU, RIBES, and AM-FM scores, and the model improves translation in terms of Adequacy, RIBES and AM-FM as compared to the baseline.
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机译:本文介绍了NLPRL Team Lor提交的机器翻译(MT)系统在Wat 2019年提交的Tamil - 英语Indie任务。我们基于变压器方法提出了神经机翻译(NMT)系统。 该模型的培训和性能是在UFAL(正式和应用语言学研究所)收集的en-Tam语料库(英国泰米尔并联语料库)上进行评估。 使用充足性,BLEU,REBES和AM-FM分数进行模型的评估,并且该模型与基线相比,在充足性,肋骨和AM-FM方面提高了平移。
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