Auditory processing of reverberation: perceptual and computational investigations

描述(申请人提供)：人类通常会遇到混响的声音，为了准确地解释声学数据，混响处理必须是人类听力的一个基本方面。然而，人们对人类听觉系统如何检测混响并随后处理混响信号知之甚少。此外，与健康的人类听众相比，最先进的计算去混响算法的表现很差。听力受损的听者，无论是否植入人工耳蜗，在混响环境中往往表现出理解能力下降。 人类对混响的感知将通过两种实验方法来探索：(1)系统地测量真实世界空间中的混响特性。这将测量人类经常遇到的混响过滤器特性的分布。(2)用合成源或合成混响滤光器进行知觉实验。志愿者听众将判断合成声音是“混响的”还是“干燥的”，并尝试匹配信号源和过滤器。假设听觉系统必须对信号源和/或过滤器做出假设，以便在感知上将两者分开，如果合成的信号源/过滤器违反这些假设，则收听者从混响录音中正确识别它们的能力将降低。 这项工作的更广泛的目标是对声音信号中的数量变化如何影响人类听者的感知声音和空间感有一个基本的了解。这些工作将为未来的听力实验、人工耳蜗植入、大型混响空间的公告系统和人机接口的自动语音识别系统的设计提供信息。

DESCRIPTION (provided by applicant): Humans commonly encounter reverberant sounds and, in order to accurately interpret acoustic data, reverberation processing must be a fundamental aspect of human audition. However, little is known about how the human auditory system detects reverberation, and subsequently processes reverberant signals. In addition, state-of- the-art computational dereverberation algorithms perform poorly compared with healthy human listeners. Hearing-impaired listeners, with and without cochlear implants, often show decreased comprehension in reverberant environments. Human perception of reverberation will be explored via two experimental methods: (1) Systematic measurement of reverberation properties in real-word spaces. This will measure the distribution of reverberation filter properties that humans regularly encounter. (2) Perceptual experiments with synthetic sources or synthetic reverberation filters. Volunteer listeners will judge synthetic sounds as "reverberant" or "dry" and attempt to match sources and filters. It is hypothesized that the auditory system must make assumptions about the source and/or filter to perceptually separate the two and if the synthetic source/filter violates these assumptions, listener's ability to correctly identify them from reverberant recordings will degrade. The broader objective of this work is to gain a basic understanding of how quantitative changes in an acoustic signal, affect both the perceived sound and sense of space in human listeners. Such work will inform the design of future audition experiments, cochlear implants, public-announcement systems for large reverberant spaces and automated voice-recognition systems for human-computer-interfaces.