CI-ADDO-NEW: Collaborative Research: A Repository for Annotating Multilingual Code Switched Data

CI-ADDO-NEW：协作研究：用于注释多语言代码交换数据的存储库

• 批准号: 1343530
• 负责人: Mona Diab
• 金额: $ 40万
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-02-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1343530&HistoricalAwards=false
• 关键词: CI; ADDO; NEW; Collaborative; Research

Linguistic code switching (LCS) is the practice of switching back and forth between the shared languages of bilingual or multilingual speakers. This phenomenon is particularly prevalent in geographic regions with linguistic boundaries or where there are large immigrant groups. Various levels of language (phonological, morphological, syntactic, semantic and discourse-pragmatic) may be implicated in LCS in different language pairs and/or genres. Computational algorithms trained for a single language quickly break down when the input includes LCS. A major barrier to research on LCS in computational linguistics (CL) has been the lack of large, accurately annotated corpora of LCS data. In this project, a large repository of LCS data is collected and a large annotation infrastructure is developed. It is consistently annotated in different modalities (speech and text), at various levels of linguistic granularity, and across different language pairs reflecting different linguistic typologies (Standard Arabic and Dialectal Arabic, Arabic-English, Spanish-English, Chinese-English, Hindi-English). The focus of the effort is on intra-sentential LCS.This infrastructure and unified large LCS data resource is eagerly awaited by the CL research community, since annotated LCS data provides a natural test-bed for adaptive learning algorithms and the handling of diverse data sources, as well as a framework for genuine multilingual processing. It will also be of benefit to sociolinguistic and theoretical linguistic researchers, and provide a platform for collaborative interdisciplinary research. Finally, research on LCS helps overcome biases against multilingual speakers by demonstrating the creativity of such speakers in exploiting their verbal repertoires. Such a result is particularly important for K-12 education and testing policies in the USA with its diverse immigrant population.

语言代码转换(LCS)是在双语或多语种说话者的共享语言之间来回切换的实践。这种现象在有语言边界的地理区域或有大量移民群体的地区尤为普遍。在不同的语言组合和体裁中，不同层次的语言(语音、形态、句法、语义和语篇-语用)可能牵涉到LCS。当输入包括LC时，为一种语言训练的计算算法很快就会崩溃。计算语言学研究的一个主要障碍是缺乏大量准确标注的词汇化语料库。在这个项目中，收集了大型LCS数据存储库，并开发了大型注释基础设施。它以不同的形式(语音和文本)、不同的语言粒度和反映不同语言类型的不同语言对(标准阿拉伯语和方言阿拉伯语、阿拉伯语-英语、西班牙语-英语、汉语-英语、印地语-英语)进行了一致的注释。这一基础设施和统一的大型LCS数据受到了CL研究界的热切期待，因为带标注的LCS数据为自适应学习算法和处理不同数据源提供了一个天然的试验台，也为真正的多语言处理提供了一个框架。它还将有利于社会语言学和理论语言学的研究，并为跨学科合作研究提供一个平台。最后，对LCS的研究有助于克服对多语种说话者的偏见，因为它展示了这些说话者在利用他们的言语能力时的创造力。这样的结果对于移民人口多元化的美国的K-12教育和考试政策尤为重要。