课题基金 / 基金详情

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

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:
1205475
负责人:
Thamar Solorio
金额:
$36.43万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2014-11-30

项目摘要

项目成果

Thamar Solorio的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
IRES Track I: US-Mexico Collaboration on Multimodal Detection of Objectionable Content in Online Videos in Spanish and English
  • 批准号:
    2106892
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.97万
  • 财政年份:
    2021
  • 负责人:
    Thamar Solorio
  • 依托单位:
Workshop on desiderata for a multimodal dataset for objectionable content detection
  • 批准号:
    2036368
  • 项目类别:
    Standard Grant
  • 资助金额:
    $4.4万
  • 财政年份:
    2020
  • 负责人:
    Thamar Solorio
  • 依托单位:
RI: Small: Robust Models for Sequence Labelling in Social Media Data
  • 批准号:
    1910192
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.79万
  • 财政年份:
    2019
  • 负责人:
    Thamar Solorio
  • 依托单位:
CAREER: Authorship Analysis in Cross-Domain Settings
  • 批准号:
    1462141
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $46.96万
  • 财政年份:
    2014
  • 负责人:
    Thamar Solorio
  • 依托单位:
海外基金