The Perception and Cognition of Sound Texture

声音质感的感知和认知

• 批准号: 2240406
• 负责人: Joshua McDermott
• 金额: $ 53.39万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2240406&HistoricalAwards=false
• 关键词: Perception; Cognition; Sound; Texture

The environments in which we live are filled with noise. Noise makes speech and other sounds of interest harder to hear, but also conveys information about the world around us, telling us how hard it is raining, whether the room next to us is full of people, or how close a kettle may be to boiling. Humans excel both at separating other sounds from background noise and at recognizing the causes of the noise in the world. Understanding these abilities could enable more effective hearing aids, cochlear implants, and speech-based machine systems such as those in our phones. Here the investigators propose to study human abilities to hear in noisy conditions.The proposed work will jointly pursue three goals. First, the investigators will develop a computational framework to understand the properties of noise that underlie human perception. This will involve assembling a large data set of environmental noises and measuring their statistical properties. These properties will then be related to human perception by synthesizing sounds that have the same properties and asking whether they are realistic and recognizable to humans. Second, the investigators will measure the ability of human listeners to perceptually separate noise from other sounds. They will then build models that can predict the conditions in which such separation should succeed or fail. Third, the investigators will measure the ability of human listeners to remember different noises and develop a model to explain why some sounds are better remembered than others.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

我们生活的环境充满了噪音。噪音会让我们的讲话和其他有趣的声音听起来更难，但也会传递关于我们周围世界的信息，告诉我们雨下得有多大，我们旁边的房间里是否挤满了人，或者水壶离沸腾有多近。人类擅长将其他声音从背景噪音中分离出来，并识别世界上噪音的原因。了解这些能力可以使更有效的助听器，人工耳蜗植入物和基于语音的机器系统，如我们的手机。在这里，研究人员提出研究人类在嘈杂环境中的听觉能力。首先，研究人员将开发一个计算框架，以了解人类感知的噪声特性。这将涉及收集大量的环境噪音数据集并测量其统计特性。然后，这些属性将通过合成具有相同属性的声音并询问它们是否真实并可被人类识别来与人类感知相关。第二，研究人员将测量人类听众从其他声音中感知分离噪音的能力。然后，他们将建立模型，可以预测这种分离成功或失败的条件。第三，研究人员将测量人类听众记忆不同声音的能力，并开发一个模型来解释为什么有些声音比其他声音更容易被记住。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。