课题基金 / 基金详情

Collaborative Research: Language Documentation with an Artificial Intelligence (AI) Helper

Collaborative Research: Language Documentation with an Artificial Intelligence (AI) Helper
协作研究:使用人工智能 (AI) 助手进行语言文档记录
批准号:
2109709
负责人:
David Chiang
金额:
$21.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-01 至 2025-02-28

项目摘要

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中文摘要
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英文摘要
Documentation of languages, especially endangered languages, is crucial for conserving humanity’s knowledge and cultural heritage, as well as for advancing an understanding of human language. Traditional documentation methods produce invaluable materials such as grammars, dictionaries, and annotated texts, but require more time than can be afforded to keep up with current language extinction rates. The most constructive response to this crisis is to complement documentation efforts by collecting data for as many languages as possible now and to make them accessible and interpretable so that they can be studied later by both linguists and members of the language communities. Digital technologies make it practical to obtain many hours of recordings in an endangered language along with translations. This project advances technologies for analyzing the recordings at the sub-word, word, and clause level so that they become accessible for a wide variety of documentary purposes.The project makes the information in digital recordings more interpretable for further linguistic analysis in three ways. First, the team is devising computational methods to automatically derive a basic phonological understanding and produce phonetic representations for languages, even if they do not have an established writing system. Second, the team is developing methods to automatically analyze the internal structure of words in languages where this structure is highly complex. Third, the team uses knowledge of more widely spoken languages to analyze related endangered languages. The resulting tool, the AI-helper toolbox, will be packaged with software that is currently widely in use by linguists and language communities in the language documentation process. All tools will be accessible through a web-based interface and the source code will be publicly available through GitHub.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(5)
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会议论文
形態論情報付き日本語 Universal Dependencies
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DOI: --
发表时间: 2023
期刊: 言語処理学会 第29回年次大会 (29th Annual Meeting of the ANLP
影响因子: --
作者: [田口智大, 宮川創]
通讯作者: 田口智大, 宮川創
Introducing Morphology in Universal Dependencies Japanese
引入普遍依赖关系日语中的形态学
DOI: --
发表时间: 2023
期刊: GURT/SyntaxFest 2023
影响因子: --
作者: [Chihiro Taguchi, David Chiang]
通讯作者: David Chiang
Mermaid Constructions in Lexical Functional Grammar
词汇功能语法中的美人鱼结构
DOI: --
发表时间: 2022
期刊: Lexical-Functional Grammar Conference
影响因子: --
作者: [Chihiro Taguchi]
通讯作者: Chihiro Taguchi
DOI: --
发表时间: 2023
期刊: Interspeech
影响因子: --
作者: [Chihiro Taguchi, Yusuke Sakai]
通讯作者: Chihiro Taguchi, Yusuke Sakai
RI: Small: Learning to Retrieve Structured Information for Summarization and Translation of Unstructured Text
  • 批准号:
    2137396
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2022
  • 负责人:
    David Chiang
  • 依托单位:
Collaborative Research: RI: Small: NL(V)P:Natural Language (Variety) Processing
  • 批准号:
    2125948
  • 项目类别:
    Standard Grant
  • 资助金额:
    $16.52万
  • 财政年份:
    2021
  • 负责人:
    David Chiang
  • 依托单位:
Collaborative Research: FMitF: Track I: Differentiable Probabilistic Programming with Recursive Structured Models
  • 批准号:
    2019291
  • 项目类别:
    Standard Grant
  • 资助金额:
    $37.53万
  • 财政年份:
    2020
  • 负责人:
    David Chiang
  • 依托单位:
RI: Small: Language Induction meets Language Documentation: Leveraging bilingual aligned audio for learning and preserving languages
  • 批准号:
    1423406
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $47.0万
  • 财政年份:
    2014
  • 负责人:
    David Chiang
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)