Collaborative Research: The Individual Differences Corpus: A resource for testing and refining hypotheses about individual differences in speech production

协作研究：个体差异语料库：用于测试和完善有关言语产生个体差异的假设的资源

• 批准号: 2234096
• 负责人: Jason Bishop
• 金额: $ 20.31万
• 依托单位: CUNY College of Staten Island
• 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 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2234096&HistoricalAwards=false
• 关键词: Collaborative; Research; Individual; Differences; Corpus

Speaking is a surprisingly personal activity. When humans articulate the vowels and consonants that make up words, or produce the rhythm and melody of a sentence, they do so in ways that differ from each other – even from others who speak the same language. And while some of the differences in a person’s pronunciation reflect the specific region they come from or the social group they belong to, most of the variation in people’s speech remains poorly understood. This lack of understanding presents challenges to society – surprisingly practical ones, such as how speech and language disorders can be diagnosed (for example, which kinds of differences are pathological and which kinds aren’t?) as well as how technological applications such as automatic speech recognition operate (for example, which kinds of differences cause problems for a speech recognition system and which ones don’t?). The goal of this project is to produce a corpus of speech data – the first-ever publicly-available corpus of its kind – that can be used to explore the ways and reasons that people differ in their speech patterns. The corpus – the Individual Differences Corpus – includes tens of thousands of words produced by hundreds of native English speakers, providing researchers with the data needed to test scientific hypotheses about how a range of mental skills (e.g., memory, attention) and personality characteristics (e.g., autistic traits, empathy) influence people’s speech, with implications for how researchers approach speech-related differences in social, educational, technological and clinical contexts. Speech signals are rife with variation. Some of this variation derives from the form of the message itself (i.e., effects of phonetic and/or phonological context), while some derives instead from the speaking context (e.g., the need to produce faster, clearer or less ambiguous speech). However, some of the variation found in speech has its origins in speakers themselves – i.e., individual differences. But what aspects of speakers and listeners cause them to vary, and what can they tell us about the language and speech production systems? The present research aims to create the Individual Differences Corpus, a publicly-available corpus resource designed for approaching questions about individual differences in speech production. The corpus is unique in that it pairs (1) thousands of words of connected speech produced by hundreds of native English speakers with (2) a large battery of measurement of all speakers’ cognitive and social profiles, including psychometrically valid measurements along several dimensions of cognitive control (e.g., working memory, processing speed, inhibition), cognitive processing styles (e.g., autistic traits, empathy) and more. The theoretical and empirical potential of the corpus is demonstrated in two psychometric studies of speech production planning that investigate planning from both prosodic and segmental perspectives.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.

说话是一项令人惊讶的个人活动，当人类发出构成单词的元音和辅音，或产生句子的节奏和旋律时，他们的发音方式彼此不同——甚至与说同一种语言的其他人也不同。虽然一个人发音的一些差异反映了他们来自的特定地区或所属的社会群体，但人们对语音的大多数差异仍然知之甚少，这种缺乏理解给社会带来了令人惊讶的实际挑战，例如。言语和语言障碍是如何发生的可以诊断（例如，哪些类型的差异是病理性的，哪些类型不是？）以及自动语音识别等技术应用程序如何运行（例如，哪些类型的差异会给语音识别系统带来问题，哪些类型的差异是病理性的？）该项目的目标是生成一个语音数据语料库，这是同类中第一个公开可用的语料库，可用于探索人们言语模式不同的方式和原因。语料库——个体差异语料库– 包括数百名以英语为母语的研究人员产生的数万个单词，以及测试有关一系列心理技能（例如记忆力、注意力）和人格特征（例如自闭症特征、同理心）如何影响的科学假设所需的数据人们的言语，对研究人员如何处理社会、教育、技术和临床环境中与言语相关的差异具有影响。言语信号充满了变化，其中一些变化源于信息本身的形式（即语音的影响）。和/或语音环境），而有些则源自说话环境（例如，需要产生更快、更清晰或更少歧义的语音）。然而，语音中发现的一些变化源于说话者本身——即个体。但是，说话者和听者的哪些方面导致了他们的差异，以及他们能告诉我们关于语言和语音生成系统的什么信息？本研究旨在创建个体差异语料库，这是一个旨在接近的公开语料库资源。该语料库的独特之处在于，它将（1）由数百名英语母语者产生的数千个相连的语音单词与（2）对所有说话者的认知和社会概况进行的大量测量相结合，包括认知控制测量（例如，工作记忆、处理速度、抑制）、认知处理风格（例如，自闭症特征、同理心）等多个维度的心理测量有效测量。该语料库的理论和经验潜力在两个心理测量中得到了证明。语音制作规划研究从韵律和分段的角度研究规划。该奖项反映了 NSF 的法定使命，并且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。