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A Model for Determining Consonantal Features in Speech

确定语音辅音特征的模型

基本信息

批准号：
6894722
负责人：
KENNETH N STEVENS
金额：
$ 50.32万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
1996
资助国家：
美国
起止时间：
1996-05-01 至 2007-01-15
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/6894722
关键词：
behavioral /social science research tag biological models clinical research cues hearing disorders human subject model design /development neural information processing noise phonology sound sound perception speech speech disorders speech recognition vocabulary

项目摘要

The long-range goal of this project is to develop a model that simulates the human perception of the words in spoken language. The immediate goal in the present project is to achieve one part of this task: the identification of the distinctive features of consonants in spoken syllables, words and sentences. Key ideas in our approach are that the speech signal contains reliable acoustic cues to the articulation implemented by the speaker even when surface phonetics are variable, and that the articulation is governed by abstract contrastive phonological representations. Identification of the consonant features proceeds by first performing an acoustic analysis of the speech to establish the locations of landmarks or discontinuities in the sound where consonant closures and releases are formed. The sound in the vicinity of those landmarks is then subjected to further detailed analysis to establish the underlying features of the consonant that generates each landmark, including the place of articulation, the voicing feature, the nasal feature etc. This further analysis involves extracting from the sound a number of attributes that provide cues for each of the underlying consonant features. The selection of these attributes is guided by the requirement that they be closely related to the articulatory shapes and movements that produced the speech. In the proposed work, our current understanding of the combination of attributes that most effectively reveal the articulation and its governing features and segments will be expanded and refined, through detailed theory-driven acoustic measures, perceptual experimentation and appropriate statistical analysis. The robustness of the model will be evaluated using various kinds of utterances, from citation forms to running speech. The performance of the model will also be tested in speech that has been contaminated with noise, and the errors made by the model will be compared with those made by human listeners. The model has application in the study of speech perception by listeners with impaired hearing or by listeners in an environment in which speech is degraded. Understanding of these processes of speech perception can lead to improved approaches to the remediation of disorders of speech perception and production.

这个项目的长期目标是开发一个模型来模拟人类对口语单词的感知。当前项目的直接目标是完成这项任务的一部分：识别口语音节、单词和句子中辅音的独特特征。我们的方法的关键思想是，即使表面语音是可变的，语音信号也包含可靠的声音线索，以表明说话者所实现的发音，并且发音是由抽象的对比语音表征控制的。辅音特征的识别首先要对语音进行声学分析，以确定辅音中形成闭合和释放的标志或不连续性的位置。然后对这些标志附近的声音进行进一步的详细分析，以确定产生每个标志的辅音的潜在特征，包括发音位置、发声特征、鼻音特征等。这种进一步的分析包括从声音中提取一些属性，这些属性为每个潜在的辅音特征提供线索。这些属性的选择是根据它们与产生语音的发音形状和动作密切相关的要求来指导的。在提出的工作中，我们目前对最有效地揭示发音及其控制特征和片段的属性组合的理解将通过详细的理论驱动的声学测量，感知实验和适当的统计分析来扩展和完善。模型的鲁棒性将使用各种话语来评估，从引用形式到运行语音。在被噪声污染的语音中测试模型的性能，并将模型的错误与人类听众的错误进行比较。该模型可应用于听力受损的听者或处于言语退化环境中的听者的言语感知研究。理解这些言语感知的过程可以导致改进的方法来补救言语感知和生产障碍。