SIRCE: A Sensor Image Based Room-Centered Equalization System for Hearing Aids

摘要 混响空间给听力受损的听众带来了很大的问题。混响 降低了这些听众的声音质量和语音的可懂度，特别是如果他们 助听器（HA）用户此外，混响降低了许多其他方法的有效性， 有用的信号处理方法，如语音增强算法，因为 混响引入了额外的虚拟源和背景噪声， 这种算法必须克服的声学信号的复杂性。 我们提出了一种称为SIRCE的新方法，该方法可以“均衡”（即去混响）语音 以及包含多个音频信号的复杂的真实世界声学环境中的其它音频信号 未知声源SIRCE的设计是为了兼容和集成 美国国立卫生研究院的开放语音平台计划。 SIRCE的设计包括三个关键的创新特征：以房间为中心， 基于图像，并且听众感知。以房间为中心意味着 系统被嵌入在声学空间本身中，而不是驻留在用户的耳朵中（ 助听器（Hearing Aid）放置传感器（麦克风）和处理有很多优点 在房间里而不是耳朵里的组件：降低成本，提高处理能力，轻松的形式 因素限制，实际部署两个以上的麦克风，并易于共享 处理能力和用户之间的计算结果。以房间为中心的设计， 这对于均衡系统特别有意义，因为混响本身是房间特定的。 基于传感器图像意味着SIRCE计算每个活动的声学图像 每个传感器中的源。传感器图像提取（“SIX”）是我们对 盲源分离（Blind Source Separation，BSS）传感器图像提取决定了 每个麦克风的响应将是孤立的每个源，即使当多个源 它们总是同时活动。SIX计算每个声音的多个独立图像 源（每个麦克风一个），而典型的BSS算法只生成一个 估计每一个来源。这很重要，因为最有效的去混响方法 是多通道算法，需要来自多个 麦克风。 监听感知意味着我们的系统使用来自监听者的HA内部的信号， 麦克风、特定于患者的敏锐度简档以及特定于患者的感兴趣源 （“目标”），以确定该目标是否是听觉可听的听众;是否其他 源是声学可听的;最佳处理策略和最佳传感器图像， 呈现给听众。(When目标远离收听者并且靠近房间麦克风， 听医管局内部麦克风的回应往往不是最佳选择！） 在这个第一阶段的项目中，我们建议验证传感器图像SIRCE计算，量化 其均衡混响语音的能力，并估计语音的整体改善 SIRCE提供的可理解性。 SIRCE系统将帮助助听器用户更好地理解复杂的语音 混响空间

Abstract Reverberant spaces create major problems for hearing impaired listeners. Reverberation reduces the sound quality and intelligibility of speech for such listeners, especially if they are hearing aid (HA) users. Moreover, reverberation reduces the effectiveness of many otherwise useful signal processing methods, such as speech enhancement algorithms, because reverberation introduces additional virtual sources and background noise that increase the complexity of the acoustic signals such algorithms must grapple with. We propose a novel method called SIRCE that “equalizes” (that is, dereverberates) speech and other audio signals in complex real-world acoustic environments containing multiple unknown acoustic sources. SIRCE has been designed for compatibility with, and integration into, NIH’s Open Speech Platform initiative. SIRCE’s design comprises three critical innovative features: it is room-centric, sensor image based, and listener aware. Room-centric means that important components of the system are embedded in the acoustic space itself, rather than residing in the user’s ear (the hearing aid). There are many advantages to placing sensors (microphones) and processing components in rooms rather than ears: reduced cost, increased processing power, relaxed form factor constraints, practical deployment of more than two microphones, and easy sharing of processing power and computational results between users. A room-centric design makes particular sense for an equalization system, because reverberation itself is room-specific. Sensor image based means that SIRCE calculates the acoustic image of each active source in each sensor. Sensor image extraction (“SIX”) is our innovative contribution to the active field of blind source separation (“BSS”). Sensor image extraction determines what the response of each microphone would be to each source in isolation even when multiple sources are always active simultaneously. SIX computes multiple independent images of each acoustic source (one for each microphone), whereas typical BSS algorithms only generate a single estimate for each source. This is important because the most effective dereverberation methods are multi-channel algorithms that require solo or source-separated inputs from multiple microphones. Listener aware means that our system employs the signals from the listener’s HA-internal microphones, a listener-specific acuity profile, and the listener-specified source of interest (“target”) to determine whether that target is acoustically audible to the listener; whether other sources are acoustically audible; and the optimal processing strategy and best sensor image to present to the listener. (When a target is far from the listener and close to a room microphone, listening to the HA internal mic response is often not the optimal choice!) In this Phase I project we propose to validate the sensor images SIRCE computes, quantify its ability to equalize reverberant speech, and estimate the overall improvement in speech intelligibility SIRCE delivers. The SIRCE system will help hearing aid users understand speech better in complex reverberant spaces.