Prosodic Event Annotation and Detection in Three Varieties of English

三种英语韵律事件标注与检测

• 批准号: 2316030
• 负责人: Jonathan Howell
• 金额: $ 50.71万
• 依托单位: Montclair State University
• 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: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2316030&HistoricalAwards=false
• 关键词: Prosodic; Event; Annotation; Detection; Three

English speakers constantly and effortlessly use prosody, such as accent and phrasing, to communicate beyond the meaning of individual words. Yet our understanding of prosody, and its integration in speech technologies, have lagged behind, particularly so for language varieties that are already underrepresented. While millions of Americans speak African American English (AAE) or Latinx English (LE), these language varieties remain underrepresented in basic and applied research, with negative consequences for speech therapy, education, criminal justice, and employment. This research will result in a corpus of AAE, LE and European American English speech data annotated for prosody, which will be used to improve our scientific understanding of prosody and to create tools for automatic detection of accent and phrase boundaries. A team of 7 students from diverse backgrounds will receive training that will provide a gateway to careers in language and technology.The corpus will include pairs of same-dialect speakers recorded in a map task, a method used to elicit spontaneous, naturalistic speech. The data will be transcribed using automatic speech recognition and hand correction, and automatically segmented into words and individual sounds using forced alignment software. Both trained and untrained coders will annotate the data for sentence accent and boundary using Rapid Prosody Transcription, an established method designed for fast, intuitive prosodic annotation by non-experts. Acoustic information, including duration, pitch, and intensity, will be extracted and used with the annotations to train a machine learning detection model, and to test previous findings about the frequency, distribution, acoustics and perception of accent and boundary in the three English language varieties.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.

说英语的人经常毫不费力地使用韵律，如口音和措辞，来传达个别单词的含义。然而，我们对韵律的理解，以及它在语音技术中的整合，已经落后了，特别是对于已经代表性不足的语言种类。虽然数百万美国人说非洲裔美国人英语（AAE）或拉丁英语（LE），但这些语言变体在基础和应用研究中的代表性仍然不足，对语言治疗，教育，刑事司法和就业产生了负面影响。这项研究将产生一个语料库的AAE，LE和欧美英语语音数据注释的韵律，这将被用来提高我们的韵律的科学理解，并创建工具，自动检测的口音和短语边界。一个由7名来自不同背景的学生组成的团队将接受培训，这将为语言和技术领域的职业生涯提供一个门户。语料库将包括在地图任务中记录的相同方言的说话者对，这是一种用于引发自发的自然主义演讲的方法。这些数据将使用自动语音识别和手动校正进行转录，并使用强制对齐软件自动分割成单词和单个声音。经过训练和未经训练的编码人员都将使用快速韵律转录来注释句子重音和边界的数据，这是一种为非专家快速，直观的韵律注释而设计的既定方法。声学信息，包括持续时间，音高和强度，将被提取并与注释一起用于训练机器学习检测模型，并测试先前关于频率，分布，该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准。