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Word sense-based approach for Hindi to Tamil machine translation using English as pivot language

机译:以英语为中心语言的基于词义的印地语到泰米尔语机器翻译方法

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摘要

Machine translation is defined as the translation of source text to a desired target text. As there is resource availability in different languages in the internet world, there is need to share the knowledge to a different set of audience who knows only their native language. The proposed system is aimed to build a word sense-based statistical machine translation system (Hindi to Tamil). Since there is a lack of resources in these languages, there is need of some other intermediate pivot language which has high resource availability and English language is chosen as one. Initially, the Hindi text is subjected to pre-processing phase where the text is morphologically and syntactically analysed. After analysis, the senses of the words are identified using latent semantic analysis (LSA) in order to provide a meaningful translation. Once these analyses are done, the sentence is subjected to statistical translation from source to target language through the intermediate pivot language. This system has an improved efficiency when compared with the system that does not have sense identification and pivot language.
机译:机器翻译定义为源文本到所需目标文本的翻译。由于互联网世界中使用不同语言提供资源,因此需要将知识共享给仅了解其母语的另一组受众。拟议的系统旨在建立一个基于词义的统计机器翻译系统(印地语到泰米尔语)。由于这些语言缺乏资源,因此需要其他一些具有较高资源可用性的中间枢轴语言,因此选择英语为其中一种。最初,印地语文本经过预处理阶段,在此阶段对其进行形态和句法分析。经过分析,使用潜在语义分析(LSA)识别单词的含义,以提供有意义的翻译。完成这些分析后,将通过中间枢轴语言对句子进行从源语言到目标语言的统计翻译。与没有感觉识别和枢轴语言的系统相比,该系统具有改进的效率。

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