Spectral Shape Factors as Acoustic Invariants for Speech Perception (Computer and Information Science)

频谱形状因子作为语音感知的声学不变量（计算机和信息科学）

• 批准号: 8702649
• 负责人: Stephen Zahorian
• 金额: $ 12.4万
• 依托单位: Old Dominion University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-07-15 至 1990-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8702649&HistoricalAwards=false
• 关键词: Spectral; Shape; Factors; Acoustic; Invariants

This research is aimed at investigating a perceptual model for representing information in speech based on spectral shape factors of short-time speech spectra. Spectral shape factors are defined as the low-ordered components of a cosine basis vector expansion of speech spectra. The primary objective of the proposed research is to determine whether spectral shape factors are fundamental information-bearing parameters for speech, or whether they are merely a convenient method for encoding speech spectra. For both vowels and stop consonants, a perceptual model which is based on spectral shape factors will be directly contrasted with a perceptual model which is based primarily on the peaks in the spectrum. In both cases experiments will be conducted to determine the extent to which coustic invariance in the speech signal can be represented by spectral shape factors. This research will not only contribute to a fundamental understanding of the information-encoding process in speech, but also has the potential for aiding automatic speech recognition research and work in the area of sensory substitution for the hearing impaired.

本研究旨在研究一种基于短时语音频谱形状因子的语音信息感知模型。频谱形状因子被定义为语音频谱的余弦基向量展开的低阶分量。提出的研究的主要目的是确定频谱形状因子是否是语音的基本信息承载参数，或者它们是否仅仅是语音频谱编码的一种方便方法。对于元音和停辅音，基于频谱形状因子的感知模型将与主要基于频谱峰值的感知模型进行直接对比。在这两种情况下，将进行实验以确定语音信号中的库斯不变性可以在多大程度上由频谱形状因子来表示。这项研究不仅有助于从根本上理解语音中的信息编码过程，而且有可能为自动语音识别的研究和听力障碍者感觉替代领域的工作提供帮助。