Speech-on-speech masking and hearing impairment: Factors affecting variability

语音掩蔽和听力障碍：影响变异性的因素

• 批准号: 9173028
• 负责人: Lauren Calandruccio
• 金额: $ 15.85万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-12-01 至 2018-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9173028
• 关键词: Acoustics; Affect; American; Assessment tool; Attention; Auditory; Auditory system; Clinical Assessment Tool; Communication; Cues; Data; Emotions; Frequencies; Future; Goals; Hearing; Individual; Intervention; Knowledge; Language; Life; Loudness; Masks; Methods; Modeling; Modification; Noise; Performance; Peripheral; Play; Psychophysics; Public Health; Research; Role; Sensorineural Hearing Loss; Signal Transduction; Speech; Speech Perception; Statistical Data Interpretation; Statistical Models; Stimulus; Stream; Testing; Time; Variant; Work; base; expectation; hearing impairment; improved; interest; public health relevance; segregation; selective attention; sex; sound; speech recognition; tool

 DESCRIPTION (provided by applicant): Individuals with hearing loss often struggle to correctly recognize speech when other talkers are competing in the background even after being fitted with appropriate amplification. This listening situation introduces two different type of masking, or challenges to hear and/or understand the speech signal of interest. Energetic masking occurs when the presence of the background speech degrades representation of the target in the peripheral auditory system. Informational masking is an inability to listen selectivey to the target in the context of a perceptually similar masker. The objective of this proposal is to determine the acoustic factors that cause variability in informational masking across different target and masker stimuli for speech-on-speech recognition, with the rationale that the knowledge gained will facilitate future advances in assessment and intervention, and eventually support technological advances to improve speech-on-speech recognition for listeners with hearing loss. It has been argued that the most important determinant of informational masking in natural speech, where the content is inherently uncertain, is target/masker similarity. While some of the acoustic features underlying similarity for speech-on-speech recognition are known [e.g., differences in fundamental frequency (F0)], we do not yet understand what all the important features are, or how they interact. Further, acoustic cues that increase target salience are known to reduce informational masking, so similarity is not the only determinant of informational masking. In Aim 1 the variability in informational masking across different target and one- or two-talker masker speech combinations will be assessed for normal-hearing and hearing-impaired listeners. Acoustic analyses of the target and masker speech will allow us to assess how similarity between the acoustic features of target and masker stimuli impact a listener's ability to segregate competing auditory streams. Aim 2 will focus on informational masking for stimuli produced with either normal or exaggerated prosody for both normal-hearing and hearing-impaired listeners. Exaggerated prosody is often used to draw the listener's attention to the speech signal. Comparing normal and exaggerated prosody will allow for an expanded range of acoustic variables, so we can more clearly see their effects. In addition, it will test the hypothesis that target salience, not just target/masker similarity, is critical for speech-on-speech masking. The same acoustical analyses used in Aim 1 will be conducted on the stimuli employed in Aim 2. Both Aims will utilize an ideal-binary mask as a way to quantify informational masking across the different stimulus conditions. Multilevel statistical modeling wil use the acoustic features of the target and masker speech to predict informational masking for different speech-on-speech listening conditions. The possibility that different acoustic features are predictive for different listener groups will be explored and tested in all models.

 描述（由申请人提供）：听力损失的个人通常很难正确识别语音时，其他说话者在背景中竞争，即使在安装了适当的放大。这种收听情况引入了两种不同类型的掩蔽，或者对收听和/或理解感兴趣的语音信号的挑战。当背景语音的存在降低了目标在外周听觉系统中的表示时，发生能量掩蔽。信息掩蔽是在感知相似的掩蔽者的上下文中无法选择性地倾听目标。这项建议的目的是 确定导致不同目标和掩蔽刺激的信息掩蔽变异性的声学因素，以便进行语音识别，其基本原理是所获得的知识将促进评估和干预的未来进展，并最终支持技术进步，以改善听力损失听众的语音识别。有人认为，最重要的决定因素的信息掩蔽在自然语音，其中的内容是固有的不确定性，是目标/掩蔽相似性。虽然语音对语音识别的相似性的基础声学特征中的一些是已知的[例如，虽然我们不知道基频（F0）的差异，但我们还不知道所有重要的特征是什么，或者它们如何相互作用。此外，已知增加目标显著性的声学线索可以减少信息掩蔽，因此相似性不是信息掩蔽的唯一决定因素。在目标1中，将评估听力正常和听力受损的听众在不同目标和一个或两个谈话者掩蔽语音组合的信息掩蔽的变化。声学分析的目标和掩蔽语音将使我们能够评估目标和掩蔽刺激的声学特征之间的相似性如何影响听者的能力，以隔离竞争的听觉流。目标2将集中在信息掩蔽的刺激产生的正常或夸张的韵律正常听力和听力受损的听众。夸张韵律常被用来吸引听者对语音信号的注意。比较正常和夸张的韵律将允许扩大范围的声学变量，所以我们可以更清楚地看到他们的影响。此外，它将测试的假设，目标显着性，而不仅仅是目标/掩蔽相似性，是至关重要的语音对语音掩蔽。将对目标2中采用的刺激进行目标1中使用的相同声学分析。两个目标都将利用理想二进制掩码作为量化不同刺激条件下信息掩蔽的一种方式。多级统计模型将使用目标和掩蔽语音的声学特征来预测不同语音对语音收听条件下的信息掩蔽。将在所有模型中探索和测试不同声学特征对不同听众群体的预测可能性。