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

 描述(申请人提供)：听力受损的人经常在其他说话者在背景中竞争时难以正确识别语音，即使在安装了适当的扩音器后也是如此。这种收听情况引入了两种不同类型的掩蔽，或对收听和/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围听觉系统中的再现时，能量掩蔽就发生了。信息掩饰是指在知觉相似的掩蔽者的背景下，不能选择性地倾听目标的声音。这项建议的目的是 确定在语音-语音识别的不同目标和掩蔽刺激下导致信息掩蔽变化的声学因素，理由是所获得的知识将促进未来评估和干预方面的进步，并最终支持技术进步，以改善听力损失听者的语音-语音识别。有人认为，在自然言语中，信息掩蔽最重要的决定因素是目标/掩蔽者的相似性，因为自然言语的内容本身是不确定的。虽然语音对语音识别的一些潜在相似性的声学特征是已知的[例如，基频(F0)的差异]，但我们还不了解所有重要特征是什么，或者它们是如何相互作用的。此外，众所周知，增加目标显著程度的声学线索可以减少信息掩蔽，因此相似性并不是信息掩蔽的唯一决定因素。在目标1中，我们将评估听力正常和听力受损的听者在不同目标和一个或两个说话者掩蔽者言语组合上的信息掩蔽的变异性。对目标和掩蔽者语音的声学分析将使我们能够评估目标和掩蔽者刺激的声学特征之间的相似性如何影响收听者分离竞争听觉流的能力。目标2将专注于对正常或夸张韵律产生的刺激进行信息掩蔽，以供听力正常和听力受损的听众使用。夸张的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声学变量的范围，因此我们可以更清楚地看到它们的影响。此外，它还将检验这样一种假设，即目标的显著程度，而不仅仅是目标/掩蔽者的相似性，对语音对语音掩蔽至关重要。目标1中使用的声学分析将对目标2中使用的刺激进行相同的声学分析。两个目标都将利用理想二元掩模作为一种方法来量化不同刺激条件下的信息掩蔽。多层统计建模将使用目标和掩蔽语音的声学特征来预测不同的语音对语音收听条件下的信息掩蔽。不同的声学特征对不同的听众群具有预测性的可能性将在所有模型中进行探索和测试。

 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.