RI: Small: Language Induction meets Language Documentation: Leveraging bilingual aligned audio for learning and preserving languages

RI：小：语言归纳遇见语言文档：利用双语对齐音频来学习和保存语言

• 批准号: 1464553
• 负责人: David Chiang
• 金额: $ 47万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1464553&HistoricalAwards=false
• 关键词: RI; Small; Language; Induction; meets

Thousands of the world's languages are in danger of dying out before they have been systematically documented. Many other languages have millions of speakers, yet they exist only in spoken form, and minimal documentary records are available. As a consequence, important sources of knowledge about human language and culture are inaccessible, and at risk of being lost forever. Moreover, it is difficult to develop technologies for processing these languages, leaving their speech communities on the far side of a widening digital divide. The first step to solving these problems is language documentation, and so the goal of this project is to develop computational methods based on automatic speech recognition and machine translation for documenting endangered and unwritten languages on an unprecedented scale.To be successful, any approach must guarantee both the sufficiency and interpretability of the documentation it produces. This project ensures sufficiency by using a combination of community outreach, crowdsourcing techniques, and mobile/web technologies to collect hundreds of hours (millions of words) of speech. The interpretability is enabled by augmenting original speech recordings with careful verbatim repetitions along with translations into a well-resourced language. Finally, computational models are developed to automate transcription of recordings and alignment with translations, resulting in bilingual aligned text. The result is a kind of digital Rosetta Stone: a large-scale key for interpreting the world's languages even if they are not written, or no longer even spoken.

世界上成千上万的语言在被系统地记录下来之前就有灭绝的危险。许多其他语言有数以百万计的人，但他们只存在于口头形式，和最低限度的文件记录。因此，有关人类语言和文化的重要知识来源无法获取，并有可能永远消失。此外，很难开发处理这些语言的技术，使他们的语言社区处于日益扩大的数字鸿沟的遥远一边。解决这些问题的第一步是语言文档，因此本项目的目标是开发基于自动语音识别和机器翻译的计算方法，以前所未有的规模记录濒危和非书面语言。要取得成功，任何方法都必须保证其产生的文档的充分性和可解释性。该项目通过使用社区外展、众包技术和移动的/网络技术相结合的方式来收集数百小时（数百万字）的语音，以确保充分性。可解释性是通过增加原始的讲话录音与仔细的逐字重复沿着翻译成一个资源丰富的语言。最后，开发计算模型来自动化录音的转录和与翻译的对齐，从而产生双语对齐文本。其结果是一种数字罗塞塔石碑：一个大规模的关键解释世界上的语言，即使他们不是书面的，甚至不再说。