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Factored phrase-based statistical machine translation

机译：基于词组的统计机器翻译

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We describe the results of a short-term SEE-ERAnet project the aim of which was to investigate the feasibility of machine translation (MT) research and development for several South Slavic and Balkan languages. The major tasks of the project were: compilation of a multilingual parallel corpus for the concerned languages, the XML mark-up of the corpus (tokenization, lemmatization, tagging), the sentence and word alignment of the corpus and the building of the statistical translation models. Additionally, based on the created resources and models, we conducted preliminary experiments on building prototype MT systems for Romanian - English, Greek - English and Slovene - English. We argue that by investing efforts in building accurate language resources, larger the better, as well as in fine-tuning of the statistical parameters, the current machine-learning technologies can be successfully used for a quick development of acceptable MT prototypes, valuable starting points in implementing working systems. We substantiate this claim with recent results from a follow-up national project, aiming at the development of a Romanian-English translation system.
机译：我们描述了短期跷跷板项目的结果，其目的是调查机器翻译（MT）的可行性（MT）对几个南斯拉夫和巴尔干语言的研发。该项目的主要任务是：汇编有关语言的多语种并行语料库，语料库的XML标记（令牌化，lemmatization，标记），语料库的句子和词对齐以及统计翻译的建设楷模。此外，根据创建的资源和模型，我们对罗马尼亚语的原型MT系统进行了初步实验< - >英语，希腊语< - >英语和斯洛文和斯莱文< - >英语。我们认为，通过投资努力建立准确的语言资源，更好，更好，以及统计参数的微调，目前的机器学习技术可以成功地用于快速发展可接受的MT原型，有价值的起点实施工作系统。我们用后续国家项目的最新结果证实了这项索赔，旨在发展罗马尼亚语 - >英语翻译系统。

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