CAREER: Representations of phonetic reduction and dialect variation in speech production and perception

职业：语音生成和感知中语音还原和方言变化的表征

• 批准号: 1056409
• 负责人: Cynthia Clopper
• 金额: $ 40.13万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-15 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1056409&HistoricalAwards=false
• 关键词: CAREER; Representations; phonetic; reduction; dialect

Human speech is inherently highly variable: no two utterances of the same word produced by the same talker are acoustically identical. The sources of this variability include properties of individual words, such as how often they occur in spoken language; properties of the context in which a word is uttered, such as the predictability of a word given the previous word; properties of the conversational setting, such as formality; and properties of the talker, such as gender or regional background. Most previous research in this area has focused on one or two sources of variation at a time. However, recent advances in statistical analysis make possible the examination in this study of many variables simultaneously. The two specific hypotheses that will be tested are that the variation due to linguistic and social factors is highly systematic and that this systematicity can facilitate speech processing. Thus, the first goal of this project is to determine how much of the variability in speech can be accounted for by these kinds of linguistic and social factors. To achieve this goal, speech produced by native speakers of American English will be recorded and analyzed in a series of production experiments that manipulate different combinations of these sources of variability. The second goal of the project is to determine how these sources of variability affect the perception and representation of the linguistic and social information that is carried by speech. To achieve this goal, word recognition, word processing, and dialect identification tasks using the recordings collected in the production experiments will be conducted. In addition to substantially contributing to our understanding of variation in speech production and perception, the results of this project have the potential to inform research on language acquisition, language processing in autism spectrum disorders, and speech technology, including automatic speech recognition.

人类的语言本质上是高度可变的：同一个说话者发出的同一个单词的两个发音在声学上是不一样的。这种变异性的来源包括单个单词的属性，例如它们在口语中出现的频率;说出单词的上下文的属性，例如给定前一个单词的单词的可预测性;会话设置的属性，例如正式性;以及说话者的属性，例如性别或区域背景。以前在这一领域的大多数研究都集中在一个或两个变异来源的时间。然而，统计分析的最新进展使得在这项研究中同时检查许多变量成为可能。两个具体的假设，将被测试的是，由于语言和社会因素的变化是高度系统性的，这种系统性可以促进语音处理。因此，这个项目的第一个目标是确定言语中的变异性有多少可以被这些语言和社会因素所解释。为了实现这一目标，由美国英语的母语者产生的语音将被记录和分析在一系列的生产实验，操纵这些可变性的来源的不同组合。该项目的第二个目标是确定这些可变性来源如何影响言语所携带的语言和社会信息的感知和表征。为了实现这一目标，单词识别，文字处理和方言识别任务，使用在生产实验中收集的录音将进行。除了大大有助于我们理解语音产生和感知的变化，该项目的结果有可能为语言习得，自闭症谱系障碍的语言处理和语音技术（包括自动语音识别）的研究提供信息。