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.

语言代码切换（LCS）是双语或多语言扬声器共享语言之间来回切换的做法。这种现象在具有语言边界的地理区域或有大型移民群体的地方尤为普遍。 LC在不同语言对和/或类型的LCS中可能与各种语言（语音，形态学，句法，语义和话语形式）有关。当输入包含LCS时，接受过单语言训练的计算算法很快就会分解。计算语言学（CL）研究LCS研究的主要障碍是缺乏大型，准确的LCS数据语料库。在该项目中，收集了大量的LCS数据存储库，并开发了大量注释基础架构。它始终以不同的方式（语音和文本），各种语言粒度以及反映不同语言类型的不同语言对（标准阿拉伯语和阿拉伯语，阿拉伯语 - 英语，西班牙语英语，中文 - 英语，印度英语）的不同语言对进行注释。努力的重点是端态LC。本基础架构和统一的大型LCS数据资源被CL研究社区急切地等待，因为注释的LCS数据为适应性学习算法提供了自然测试床，用于处理不同的数据源，以及用于真实多种语言的框架。这也将对社会语言和理论语言研究人员有益，并为协作跨学科研究提供了一个平台。最后，对LCS的研究有助于克服对多语言说话者的偏见，通过证明这类演讲者的创造力在利用其口头曲目时的创造力。这种结果对于在美国各种移民人口的美国教育和测试政策中尤其重要。