Hear What I Want: an Acoustically Smart Personalized Common Room

摘要 带有多个有源声源的嘈杂房间给听力受损的听众带来了问题。不需要的 掩蔽声音降低了听众，尤其是听众想要听到的讲话的质量和可理解性 有听力障碍。我们提出了一种新的辅助听力系统HWIW(“我想听什么”) 将噪声和其他不需要的音频成分从复杂的现实世界环境中清除(即移除) 包含多个声源的。HWIW是为融入NIH的开放演讲而设计的 助听器和其他个人音频设备的平台倡议。HWIW将利用STAR公司的多项 可插拔声分离信号的算法源分离(MASS)应用框架 处理模块。MASS与开放语音平台兼容，并可在GitHub上使用。 HWIW是一个以房间为中心的系统，通过用户的智能手机向用户提供特定于听众的音频。 HWIW使用分布在房间周围的多个麦克风，并连接到特定于房间的专用 服务器。初始HWIW设置程序用于命名房间中永久放置的“噪音制造器” 例如扬声器和电器，并表征它们的声辐射和反射模式。HWIW 房间服务器处理来自多个HWIW麦克风的音频信号，以消除噪音器产生的声音 从听者选择监听的房间中的任何一个麦克风。同时支持多个监听器- 小莉。每个听众使用HWIW Listener App来指定要监听感兴趣的声音的麦克风以及 已知的要擦拭的噪音器。HWIW房间服务器计算个性化的擦除音频流 并将其无线传输到他们的收听者App。监听器应用程序将该音频流输出到 听者的助听器、个人音频设备或耳塞作为标准线路电平或蓝牙音频信号。 HWIW以房间为中心、基于传感器图像、延迟优化和监听器感知。重要系统 部件被嵌入到声学空间本身，而不是用户的耳朵(助听器)。硬件硬件 计算传感器响应混合体中掩蔽声音的声学图像，以便不需要的图像 声音可以删除。它计算其信号处理的延迟并平衡以下各项的质量优势 更长的延迟抵消了更快的响应时间的感知优势。HWIW雇佣了监听者- 特定的敏锐度轮廓，关于每个听者的助听器或耳朵的隔音特性的信息 片段，以及侦听器指定的掩蔽声音，以确定在给定 听众的敏锐度；因此，对该听众来说，最佳的噪音清除策略是什么。 在第一阶段，我们将实现三个HWIW海量擦除模块，以及一个监听器App的原型。 我们将客观地测量擦洗模块从麦克风响应中擦除噪声的能力， 根据感知的残留噪声校准这些测量，并评估Listener App的可用性。 HWIW系统将帮助听力受损的听众在嘈杂的房间里更清楚地听到他们想要的东西。

Abstract Noisy rooms with multiple active sound sources create problems for hearing-impaired listeners. Unwanted masking sounds reduce the quality and intelligibility of speech that listeners want to hear, especially listeners with hearing deficits. We propose a novel assistive listening system called HWIW (“Hear What I Want”) that “scrubs” (i.e., removes) noise and other unwanted audio components from complex real-world environments containing multiple acoustic sources. HWIW has been designed for integration into NIH’s Open Speech Platform initiative for hearing aids and other personal audio devices. HWIW will leverage STAR Corp’s Multiple Algorithm Source Separation (MASS) application framework of “pluggable” acoustic separation signal processing modules. MASS is compatible with the Open Speech Platform and available on GitHub. HWIW is a room-centric system that delivers listener-specific audio to users through their smartphones. HWIW employs multiple microphones distributed around a room and connected to a room-specific dedicated server. An initial HWIW setup procedure is used to name permanently positioned “noisemakers” in the room such as speakers and appliances and characterize their acoustic radiation and reflection patterns. The HWIW Room Server processes audio signals from multiple HWIW mics to scrub the noisemaker-generated sounds from any microphone in the room a listener chooses to monitor. Multiple listeners are supported simultaneous- ly. Each listener uses a HWIW Listener App to specify which mic to monitor for sounds of interest and which of the known noisemakers to scrub. The HWIW Room Server computes an individualized scrubbed audio stream for each listener and transmits it wirelessly to their Listener App. The Listener App outputs this audio stream to the listener’s hearing aid, personal audio device, or earbuds as a standard line level or Bluetooth audio signal. HWIW is room-centric, sensor image-based, latency-optimized, and listener-aware. Important system components are embedded in the acoustic space itself, rather than in the user’s ear (the hearing aid). HWIW calculates the acoustic image of masking sounds in sensor response mixtures so that images of unwanted sounds can be removed. It computes the latency of its signal processing and balances the quality benefits of longer-latency scrubbing against the perceptual advantages of faster response times. HWIW employs listener- specific acuity profiles, information about the sound-isolating properties of each listener’s hearing aid or ear piece, and the listener-specified masking sounds to determine whether which maskers are audible given the listener’s acuity; and thus what the optimal noise scrubbing strategy is for that listener. In Phase I, we will implement three HWIW MASS scrubbing modules, and a prototype of the Listener App. We will objectively measure the ability of the scrubbing modules to scrub noise from microphone responses, calibrate those measurements against perceived residual noise, and evaluate Listener App useability. The HWIW system will help hearing impaired listeners hear what they want more clearly in noisy rooms.