Visual Speech Articulation Training Aid

视觉言语清晰度训练辅助工具

• 批准号: 9411607
• 负责人: Stephen Zahorian
• 金额: $ 18.8万
• 依托单位: Old Dominion University Research Foundation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-09-01 至 1998-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9411607&HistoricalAwards=false
• 关键词: Visual; Speech; Articulation; Training; Aid

9411607 Zahorian The research proposed in this project is to investigate and optimize methods for extracting speaker-independent acoustically- based speech parameters that signal the phonetic content of speech and to determine transformations which can display these features in an articulation training aid for the hearing impaired. The proposed project is a continuation and extension of research previously funded by the NSF. A major component of the effort will be to coordinate the collection of a large data base of speech samples from both normally-hearing and hearing- impaired listeners, which will be required not only for the proposed work, but which will also facilitate other research efforts in the field. Extensive experiments will be conducted to optimize the conversion of speech parameters to display parameters so that phonemes and distinctive features of phonemes, produced either in isolation or syllabic contexts, can readily be discriminated and identified based on their display characteristics. A combination of nonlinear/linear transform will convert acoustic measurements of auditory stimuli to a visual display representation. Acoustic features will be extracted from global spectral shape, fundamental frequency, and short-time energy. The feature extraction/classification process will be individually optimized for every pair of phones in English. ***

9411607 Zahorian本项目中提出的研究是调查和优化方法，用于提取与说话者无关的基于声学的语音参数，这些参数表示语音的语音内容，并确定可以在听力受损者的发音训练辅助器中显示这些特征的转换。 拟议的项目是以前由NSF资助的研究的延续和延伸。 这项工作的一个主要组成部分将是协调从听力正常和听力受损的听众那里收集大量的语音样本数据库，这不仅是拟议的工作所需要的，而且也将促进这一领域的其他研究工作。 将进行广泛的实验，以优化语音参数转换为显示参数，以便音素和音素的区别特征，无论是在隔离或音节的上下文中产生的，可以很容易地区分和识别的基础上，他们的显示特性。 非线性/线性变换的组合将听觉刺激的声学测量转换为视觉显示表示。 声学特征将从全局频谱形状、基频和短时能量中提取。 特征提取/分类过程将针对英语中的每对音素进行单独优化。 ***