Computer-Based Speech Training for the Hearing Impaired

针对听障人士的基于计算机的言语训练

• 批准号: 9977260
• 负责人: Stephen Zahorian
• 金额: $ 26.1万
• 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: 1999
• 资助国家: 美国
• 起止时间: 1999-09-15 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9977260&HistoricalAwards=false
• 关键词: Computer; Based; Speech; Training; Hearing

9977260ZahorianThe objectives of the proposed research are to investigate and optimize methods for extracting speaker-independent acoustically-based speech parameters that signal the phonetic content of speech and to convert these parameters to a visual display for use as 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 collect and annotate a large database of speech samples from both normally-hearing and hearing-impaired listeners, for use with the proposed work and also to facilitate other research efforts in this 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, syllabic contexts, or as part of continuous speech, can readily be discriminated and identified based on their display characteristics. Automatic speech recognition algorithms will be developed and refined to create a visual display representation. Acoustic features will be extracted from the peak envelope spectrum, fundamental frequency, and short-time energy. Several recognition strategies, all using neural networks as a key building block, will be investigated. Visual displays will be developed and tested for several speech training exercises at various levels of complexity-ranging from distinctive features for phones produced in isolation to phonetic displays for continuous speech. One display mode will be developed which provides a continuous relationship between articulatory features for vowel and consonant production and displayed patterns, and will show both degree and directions of any needed corrections in articulation. Additionally, discrete displays, such as bargraphs or games, will indicate the closeness of a production to a "normal" production. The emphasis of the research is to improve automatic phonetic recognition to the level that the feedback given by the algorithm is as accurate and consistent as that which would be possible by an expert experienced listener. Controlled evaluation experiments will be conducted to determine the extent to which "new" speech articulation patterns can be learned on the basis of the feedback given from the various displays. Speech articulation training exercises will also be conducted with hearing-impaired children to assess the usefulness of the visual display in improving speech production and to help determine methods to improve it.

9977260Zahorian拟议研究的目标是调查和优化用于提取非特定说话人的基于声学的语音参数的方法，这些参数发出语音内容的信号，并将这些参数转换为视觉显示，以用作听力障碍者的发音训练辅助工具。拟议中的项目是之前由美国国家科学基金会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收集和注释来自听力正常和听力受损的听者的言语样本的大型数据库，以用于拟议的工作，并促进这一领域的其他研究工作。将进行广泛的实验，以优化语音参数到显示参数的转换，以便可以根据音素的显示特性容易地区分和识别在孤立的音节上下文中产生的音素和音素的独特特征，或者作为连续语音的一部分。将开发和改进自动语音识别算法，以创建可视显示模式。声学特征将从峰值包络频谱、基频和短时能量中提取。将研究几种识别策略，它们都使用神经网络作为关键的构建块。将为不同复杂程度的几项语音训练练习开发和测试视觉显示器--从单独生产的电话的独特功能到连续语音的语音显示器。将开发一种显示模式，它提供元音和辅音产生的发音特征与显示模式之间的连续关系，并将显示发音中任何所需校正的程度和方向。此外，离散显示，如条形图或游戏，将表明生产的接近“正常”的生产。研究的重点是将自动语音识别提高到这样的水平，即该算法给出的反馈与有经验的专家听众可能提供的反馈一样准确和一致。将进行受控评估实验，以根据从各种显示器给出的反馈来确定可以在多大程度上学习“新的”语音发音模式。还将为听力受损儿童进行语音清晰度训练，以评估视觉显示在改善言语产出方面的作用，并帮助确定改进方法。