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Short-term projects, long-term benefits: Four student NLP projects for low-resource languages

机译:短期项目,长期福利:4个学生NLP项目,用于低资源语言

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This paper describes a local effort to bridge the gap between computational and documentary linguistics by teaching students and young researchers in computational linguistics about doing research and developing systems for low-resource languages. We describe four student software projects developed within one semester. The projects range from a front-end for building small-vocabulary speech recognition systems, to a broad-coverage (more than 1000 languages) language identification system, to language-specific systems: a lemmatizer for the Mayan language Uspanteko and named entity recognition systems for both Slovak and Persian. Teaching efforts such as these are an excellent way to develop not only tools for low-resource languages, but also computational linguists well-equipped to work on endangered and low-resource languages.
机译:本文介绍了通过在计算语言学中的学生和年轻研究人员对低资源语言进行研究和开发系统的计算语言学中的学生和年轻研究人员来展示当地的努力。我们描述了在一个学期内开发的四个学生软件项目。该项目范围从前端建立小词汇语音识别系统,以广泛的覆盖范围(超过1000种语言)语言识别系统,以语言特定的系统:玛雅语言uspanteko和命名实体识别系统的lemmatizer对于斯洛伐克和波斯语来说。这些教学努力,这些是不仅开发低资源语言的工具的绝佳方式,而且还有能力康复和低资源语言的计算语言学家。

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