EAGER: Automatic Speech Recognition for Uyghur

EAGER：维吾尔语自动语音识别

• 批准号: 1519164
• 负责人: Arienne Dwyer
• 金额: $ 2.73万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-02-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1519164&HistoricalAwards=false
• 关键词: EAGER; Automatic; Speech; Recognition; Uyghur

Advances in speech engineering now allow audio to be transcribed as text, even for languages for which there are few computational resources. Automating text transcription for more languages allows public, community, and researcher access to previously inaccessible materials. This project uses several thousand hours of radio broadcasts in an under-resourced language as a test case to improve rapid audio-to-text development techniques, which are applicable to any language. The project allows speech engineers to apply technology to new languages, to learn about the characteristics of new languages and their impact on speech recognition performance, and how to overcome them with the goal of building better speech recognition systems. It also enables communities to preserve their language, distribute tools and data, and overall, improve the current extreme resource limitations of their language. The project encourages students to work and think across the fields of speech engineering, linguistics and journalism.In this EAGER project, the Uyghur language (ISO 639-3: uig), a severely under-resourced Turkic language of Xinjiang in Central Asia with about 11 million speakers, is used to test the rapid development of an Automatic Speech Recognition (ASR) system with the long-term vision of creating web-based speech and language services including pronouncing dictionary generation, audio and text data archiving, and part-of-speech tagging. The project is exploratory because the language is devoid of computationally tractable resources, yet bootstrapping through a related language (Turkish) promises rapid ASR development. The project can serve as a model for such development for any language, large or small, and is potentially transformative -- first because so many of the world's languages are like Uyghur in having few available computational resources., and second because so many documentary linguists still rely entirely on non-automated methods.

语音工程的进步现在允许将音频转录为文本，即使是对于计算资源很少的语言。自动化文本转录更多的语言允许公众，社区和研究人员访问以前无法访问的材料。这个项目以一种资源不足的语文进行几千小时的无线电广播，作为一个试验案例，以改进适用于任何语文的音频到文字的快速发展技术。该项目允许语音工程师将技术应用于新语言，了解新语言的特征及其对语音识别性能的影响，以及如何克服这些问题，以构建更好的语音识别系统。它还使社区能够保护他们的语言，分发工具和数据，并从总体上改善他们的语言目前极端的资源限制。该项目鼓励学生在语音工程、语言学和新闻学领域工作和思考。在这个EAGER项目中，（ISO 639-3：维吾尔语是中亚新疆的一种突厥语族语言，资源严重不足，约有1100万人使用，用于测试自动语音识别（ASR）系统的快速开发，其长期愿景是创建Web，基于语音和语言的服务，包括发音词典生成、音频和文本数据存档以及词性标注。该项目是探索性的，因为该语言缺乏计算上易处理的资源，但通过相关语言（土耳其语）引导有望快速ASR开发。该项目可以作为任何语言（无论大小）的此类开发的模型，并且具有潜在的变革性-首先是因为世界上许多语言都像维吾尔语一样，几乎没有可用的计算资源。第二，因为许多文献语言学家仍然完全依赖于非自动化的方法。