僧伽罗语-泰米尔语系统的统计机器翻译

S. Sripirakas, A. Weerasinghe, D. Herath
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引用次数: 13

摘要

统计翻译方法是最有前途和领先的机器翻译策略之一。它甚至适用于结构不同的语言对,证实了它在大文本翻译中的适用性。几十年来,对僧伽罗语和泰米尔语之间自动翻译的需求不断上升。统计方法是解决有关语言的机器翻译工具不可用性的最佳选择。由于语言的相似性,统计方法可以很好地发展,而不需要更多地关注语言知识。一个基本的翻译系统已经在本研究中建模和实施,并从议会命令文件中准备平行语料库。本文仅展示了研究的初步系统运行,缺乏各种参数的细化和实际的设计和评估策略。语言模型、翻译模型和解码器配置均与近期文献一致。为了提高输出质量,采用MERT技术对解码器进行调优。为了避免完全依赖BLEU,另外两个自动指标即TER和NIST用于不同方面的评估。此外,还对未来的研究方向进行了确认,并为该系统的改进指明了方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical machine translation of systems for Sinhala - Tamil
One of the most promising and leading machine translation strategies would be Statistical Translation Approach. Being pertinent even to structurally dissimilar language pairs, it has confirmed its suitability for large text translation. Rising demand is present for automatic translation between Sinhala and Tamil for quite a lot of decades. Statistical approach is the best preference to resolve the unavailability of a machine translation tool for the languages concerned. Because of language similarity, statistical approach could thrive agreeably, exclusive of more concern on linguistic knowledge. A basic translation system has been modelled and implemented in this research, with the preparation of parallel corpora from parliament order papers. This paper demonstrates only the preliminary system runs of the research, devoid of various parameter refinements and actual design and evaluation strategies. Language Model, Translation Model and Decoder Configurations are done consistent with recent literature. To facilitate the improvement of output quality, MERT technique is integrated to tune the decoder. To stay away from sole dependence on BLEU, two other automatic metrics namely TER and NIST are utilised for the evaluation in different aspects. In addition, directions to future research are also recognized and specified for the refinements of this system.
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