Aids for the Deaf: Models of Speech Intelligibility

描述（由申请人提供）：本研究旨在通过对语音清晰度模型的研究项目，改善助听器和人工耳蜗使用者的语音接收能力。目标是开发和实验评估一个强大的物理指标，预测各种变化的语音信号的可理解性分数为听力受损（HI）听众和人工耳蜗（Cl）用户。该指标将是基于语音的语音传输指数（sSTI）的改进，sSTI直接从语音信号和单个听者的特征中计算一个新的指标，并处理传统STI方法无法充分建模的各种非线性失真。我们有四个目标。第一个目标是测量3类听众的语音接收情况：HI听众、Cl用户和听力正常的受试者，通过通道声码器模拟人工耳蜗对4种类型的语音改变（由噪声和混响、带通滤波、幅度压缩和降噪算法引起的声音退化）进行听力处理。第二个目的是表征个体HI听者和Cl使用者的相关基本心理声学能力（在基本灵敏度、动态范围、频谱分辨率和时间分辨率方面）以及他们整合不同语音过滤带的线索的能力。第三个目标是开发基于ssti的语音可理解性指标，并将其应用于用于测试HI和Cl听者的刺激。这些指标将包括个体听者的特征，包括心理声学能力和跨频率整合线索的能力。第四个目标是通过将各种听众和语音处理条件的度量预测与我们在语音接收度量上获得的经验数据进行比较来评估这些度量。在本项目结束时，我们将得到一个适用于HI侦听器和Cl用户的单一指标（扩展到听力正常的侦听器）。该指标将预测噪声、混响、滤波、幅度压缩和降噪算法对语音可理解性的影响，并将在研究和临床环境中有许多应用。

DESCRIPTION (provided by applicant): This research is directed toward improved speech reception for users of hearing aids and cochlear implants through a program of research on models of speech intelligibility. The goal is to develop and experimentally evaluate a robust physical metric that predicts intelligibility scores for a variety of alterations of the speech signal for both hearing-impaired (HI) listeners and Cochlear Implant (Cl) users. This metric will be an adaptation of the speech-based Speech Transmission Index (sSTI) that computes a novel metric from the speech signals directly and the characteristics of individual listeners, and deals with a wide class of nonlinear distortions that are not adequately modeled by traditional STI methods. We have 4 aims. The first aim is to measure speech reception in 3 classes of listeners: HI listeners, Cl users, and normal-hearing subjects listening through a channel-vocoder simulation of cochlear-implant sound processing for 4 types of alterations of speech (acoustic degradations arising from noise and reverberation, band-pass filtering, amplitude compression, and noise-reduction algorithms). The second aim is to characterize the relevant basic psychoacoustic abilities of individual HI listeners and Cl users (in terms of basic sensitivity, dynamic range, spectral resolution, and temporal resolution) and their ability to integrate cues across different filtered bands of speech. The third aim is to develop sSTI-based metrics of speech intelligibility and apply them to the stimuli used to test HI and Cl listeners. The metrics will incorporate the individual listener characteristics, both psychoacoustic abilities and facility at integrating cues across frequency. The fourth aim is to evaluate these metrics by comparing metric predictions for a variety of listeners and speech processing conditions to the empirical data we have obtained on measures of speech reception. At the end of this project, we will have a single metric that is applicable to both HI listeners and Cl users (and by extension to normal-hearing listeners as well). This metric will predict the effects of noise, reverberation, filtering, amplitude compression, and noise reduction algorithms on speech intelligibility and will have a number of applications in research and clinical settings.