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A Hybrid Approach For Hindi-English Machine Translation

机译:印地语 - 英语机器翻译的混合方法

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摘要

In this paper, an extended combined approach of phrase based statisticalmachine translation (SMT), example based MT (EBMT) and rule based MT (RBMT) isproposed to develop a novel hybrid data driven MT system capable ofoutperforming the baseline SMT, EBMT and RBMT systems from which it is derived.In short, the proposed hybrid MT process is guided by the rule based MT aftergetting a set of partial candidate translations provided by EBMT and SMTsubsystems. Previous works have shown that EBMT systems are capable ofoutperforming the phrase-based SMT systems and RBMT approach has the strengthof generating structurally and morphologically more accurate results. Thishybrid approach increases the fluency, accuracy and grammatical precision whichimprove the quality of a machine translation system. A comparison of theproposed hybrid machine translation (HTM) model with renowned translators i.e.Google, BING and Babylonian is also presented which shows that the proposedmodel works better on sentences with ambiguity as well as comprised of idiomsthan others.
机译:本文提出了基于短语的统计机器翻译(SMT),基于示例的MT(EBMT)和基于规则的MT(RBMT)的扩展组合方法,以开发一种新型混合数据驱动的MT系统,该系统能够胜过基线SMT,EBMT和RBMT系统简而言之,在获得了由EBMT和SMT子系统提供的部分候选翻译后,基于规则的MT指导了提出的混合MT过程。先前的工作表明,EBMT系统能够胜过基于短语的SMT系统,而RBMT方法具有生成结构和形态上更准确的结果的优势。这种混合方法提高了流利性,准确性和语法精度,从而提高了机器翻译系统的质量。还提出了建议的混合机器翻译(HTM)模型与著名的翻译人员(即Google,BING和巴比伦)的比较,这表明建议的模型在含歧义的句子以及由成语组成的句子上效果更好。

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