EAGER: Identifying and Producing Code-Switching in Languages from Spoken, Lexical and Socio-linguistic Features

EAGER:根据口语、词汇和社会语言特征识别和产生语言中的语码转换

基本信息

  • 批准号:
    2327564
  • 负责人:
  • 金额:
    $ 10.89万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-06-15 至 2024-05-31
  • 项目状态:
    已结题

项目摘要

This Early Grant for Exploratory Research investigates conversations between the vast number of persons in our world who speak multiple languages and who frequently switch back and forth between those languages in what is called “code-switching”. It is important for speech dialogue systems and voice assistants to not only be able to identify when, why, and to what effect code-switching occurs, but also to correctly interpret what is said and to be able to generate similarly code-switched responses when interacting with such users. Advances in speech technology in recent years have resulted in widespread use of voice assistants such as Siri, Google Assistant and Alexa. They enable vast improvement in information access by voice for languages such as English, French, German, Cantonese, Mandarin, and Spanish. However, such access is limited to monolingual speech, which for many multilingual speakers is not the most natural form of speech production. Thus, code-switched speech is rarely understood correctly and is never able to be produced in assistant responses. A major barrier to enabling naturalistic and comfortable communication for these speakers is the lack of speech technology that can not only understand code-switched input but also produce similar human-like output. This project addresses these issues by examining how spoken and written code-switching interacts with other aspects of language communication. It will explore research questions not yet studied in code-switching research including (1) whether speakers entrain, speak more similarly, on pronunciation and other strategies of code-switching in speech; (2) whether there is a quantifiable relationship between code-switching and empathy in speech, where empathy is a speaker's intention to convey that they understand another's problems and want to help address them; (3) whether the presence of named entities, such as names or geographical locations, primes code-switching; (4) which dialogue acts, such as questions or statements or backchannels, tend to be produced most often in code-switched speech; and (5) how speakers produce intonational contours when they code-switch (via choosing their intonation production to match either of the languages they are producing or by being different from both?) Statistical and machine-learning techniques will both be used to address these questions in the context of spoken and lexical-feature-tagged code-switched speech in Standard American English, Spanish, Mandarin Chinese, and Hindi. By identifying new aspects of code-switching, the project will seed further exploration of this phenomenon by the research community.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.
这项早期探索性研究资助调查了世界上大量讲多种语言的人之间的对话,这些人经常在这些语言之间来回切换,这对于语音来说很重要。对话系统和语音助手不仅能够识别语码转换发生的时间、原因和效果,而且能够正确解释所说的内容,并在与此类用户交互时能够类似地生成语码转换响应。近年来语音技术的进步使得Siri、Google Assistant 和 Alexa 等语音助手的广泛使用极大地改善了英语、法语、德语、粤语、普通话和西班牙语等语言的信息访问。对于许多多语言说话者来说,这并不是最自然的语音产生形式,因此,语码转换语音很少能被正确理解,并且永远无法在助理响应中产生,这是这些说话者实现自然和舒适沟通的主要障碍。是缺乏语音技术不仅可以理解语码转换输入,还可以产生类似人类的输出,该项目通过研究口语和书面语码转换如何与语言交流的其他方面进行交互来解决这些问题。转换研究包括(1)说话者是否会在语音中的发音和其他语码转换策略上表现得更加相似;(2)语码转换和言语中的同理心之间是否存在可量化的关系,其中同理心是说话者的能力;意图表达他们理解他人的问题并希望帮助解决这些问题;(3) 命名实体(例如姓名或地理位置)的存在是否会引发语码转换;(4) 哪些对话会起作用,例如问题或陈述或反向通道,往往在语码转换语音中产生;以及(5)说话者在语码转换时如何产生语调轮廓(通过选择其语调产生来匹配他们正在产生的语言或通过与他们所产生的语言不同)两者?)统计和机器学习技术将用于在标准美式英语、西班牙语、普通话和印地语的口语和词汇特征标记的语码转换语音的背景下解决这些问题。该项目将促进研究界对这一现象的进一步探索。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Julia Hirschberg其他文献

Classification of discourse functions of affirmative words in spoken dialogue
口语对话中肯定词的话语功能分类
  • DOI:
    10.21437/interspeech.2007-450
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Agustin Gravano;S. Benus;Julia Hirschberg;Shira Mitchell;Ilia Vovsha
  • 通讯作者:
    Ilia Vovsha
Varying input segmentation for story boundary detection in English, Arabic and Mandarin broadcast news
用于英语、阿拉伯语和普通话广播新闻中故事边界检测的不同输入分段
  • DOI:
    10.21437/interspeech.2007-687
  • 发表时间:
    2024-09-14
  • 期刊:
  • 影响因子:
    0
  • 作者:
    A. Rosenberg;Mehrbod Sharifi;Julia Hirschberg
  • 通讯作者:
    Julia Hirschberg
Characterization of the Biomedical Query Mediation Process
生物医学查询调解过程的表征
Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts
根据社交媒体帖子自动检测和预测精神病住院情况
Spatial Relations in Text-to-Scene Conversion
文本到场景转换中的空间关系
  • DOI:
    10.7916/d8902c78
  • 发表时间:
    2024-09-14
  • 期刊:
  • 影响因子:
    0
  • 作者:
    R. Sproat;Robert Coyne;Julia Hirschberg
  • 通讯作者:
    Julia Hirschberg

Julia Hirschberg的其他文献

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{{ truncateString('Julia Hirschberg', 18)}}的其他基金

RI: Small: Creating Text-to-Speech Synthesis for Low Resource Languages
RI:小型:为低资源语言创建文本到语音合成
  • 批准号:
    1717680
  • 财政年份:
    2017
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant
EAGER: Creating Speech Synthesizers for Low Resource Languages
EAGER:为低资源语言创建语音合成器
  • 批准号:
    1548092
  • 财政年份:
    2015
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant
Using Computational Tools to Facilitate Corpus Collection and Language Use in Arrernte (aer)
使用计算工具促进 Arrernte (aer) 中的语料库收集和语言使用
  • 批准号:
    1160700
  • 财政年份:
    2012
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant
IGERT: From Data to Solutions: A New PhD Program in Transformational Data & Information Sciences Research and Innovation
IGERT:从数据到解决方案:一个新的转型数据博士项目
  • 批准号:
    1144854
  • 财政年份:
    2012
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Continuing Grant
Collaborative Research: CI-P: Reciprosody - A Repository for Prosodically Annotated Material
合作研究:CI-P:Reciprosody - 韵律注释材料存储库
  • 批准号:
    1205450
  • 财政年份:
    2012
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant
EAGER: Using Social Media and Crowdsourcing to Create a New Affect Dictionary
EAGER:利用社交媒体和众包创建新的情感词典
  • 批准号:
    1145505
  • 财政年份:
    2011
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant
CI-P: Collaborative Research: Summarizing Opinion and Speaker Attitude in Speech
CI-P:协作研究:总结观点和演讲者在演讲中的态度
  • 批准号:
    1059260
  • 财政年份:
    2011
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant
RI: Medium: Collaborative Research: From Text to Pictures
RI:媒介:协作研究:从文本到图片
  • 批准号:
    0904361
  • 财政年份:
    2009
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant
RI-Medium: Collaborative: Corpus-Based Studies of Lexical, Acoustic-Prosodic, and Discourse Entrainment in Spoken Dialogue
RI-Medium:协作:基于语料库的口语对话中的词汇、声学韵律和话语夹带研究
  • 批准号:
    0803148
  • 财政年份:
    2008
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant
Doctoral Consortium at The Human Language Technology Conference - North American chapter of the Association for Computational Linguistics annual meeting (NAACL HLT) 2007.
人类语言技术会议博士联盟 - 计算语言学协会年会 (NAACL HLT) 2007 年北美分会。
  • 批准号:
    0707305
  • 财政年份:
    2007
  • 资助金额:
    $ 10.89万
  • 项目类别:
    Standard Grant

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