EMG Voice Restoration

近750万人无法有效发声。现有的增强和替代办法 AAC技术通常通过将AAC转换成音频来为这些个体提供某些功能。 身体姿势、眼睛运动或文本转换成可以声学合成或视觉显示的单词。 然而，这些设备的一个关键限制是它们不涉及语音产生的自然机制 因此作为人类发声系统的替代品可能不太直观。因此，他们可能会遭受 词汇模糊，缺乏情感表达，难以表达意图。仍然有一个未满足的需求 恢复发声障碍者的自然发声机制。为了满足这一需求，我们建议 开发一个首个AAC系统，该系统可以恢复个性化，韵律，近实时的发声， 在声下期间产生的表面肌电（sEMG）信号（即，无声的口）讲话。同相 我们展示了识别正字法内容和对短语之间的重音进行分类的能力 由（n = 4）对照组和（n = 4）喉切除术后参与者默读，单词识别率为96.3%， 应激判别率为91.2%。合成了潜语音语料库转录本 使用每个参与者独有的个性化数字语音转换为韵律语音，然后由天真的 听者（n = 12）。听众一致认为我们基于表面肌电信号的数字语音具有更高的可懂度， 可接受性、重点辨别性和声音亲和力比最先进的电子喉（EL）语音辅助 用于喉切除者。通过对单个短语进行冗长的后处理实现了这些功能， 我现在的目标是在第二阶段通过解决转录的更基本的挑战来推进这项技术 韵律语音和跟踪语调和定时的变化，以近实时地恢复会话 日常生活中的互动。为了实现这一目标，我们的工程师团队在Altec Inc.正在与 世界领先的AAC（VocaliD，Inc）个性化数字化语音提供商，以及世界一流的喉 癌症临床专家（马萨诸塞州总医院）开发用于转录韵律语音的算法 以及追踪叙述、独白和对话中语调和时间的变化（目标1）; 设计近实时移动的使用的MyoVoice ™系统（目标2）;并评估原型系统， 会话效能（目标3）。我们的里程碑是证明在易用性， 使用我们的基于表面肌电图的数字技术， 与他们典型的EL语音助手相比。最终交付的产品将包括一个4触点传感器 单板和跨平台、近实时的移动的软件，可以在AAC平板电脑或移动的设备上运行。 一旦商业化，我们对这种设备未来的愿景是为一个人-谁是面临毁灭性的需要 接受喉切除术--将他们的声音储存起来，并训练声音下的模型， 手术后，他们可以接受定制的MyoVoice ™系统，以恢复他们原来的声音。

Nearly 7.5 million people live without the ability to vocalize effectively. Existing augmentative and alternative communication (AAC) technology provides some function for these individuals, typically by converting physical gestures, eye movements or text into words that can be acoustically synthesized or visually displayed. However, a key limitation of these devices is that they do not involve natural mechanisms of speech production and therefore can be less intuitive as substitutes for the human vocal system. Consequently, they can suffer from lexical ambiguity, lack of emotional expression, and difficulty in conveying intent. There remains an unmet need to restore the natural mechanisms of speech production for the vocally impaired. To meet this need, we propose to develop a first-of-its-kind AAC system that restores personalized, prosodic, near real-time vocalization based on surface electromyographic (sEMG) signals produced during subvocal (i.e., silently mouthed) speech. In Phase I, we demonstrated the ability to recognize orthographic content and categorize emphatic stress between phrases subvocalized by (n=4) control and (n=4) post-laryngectomy participants with a 96.3% word recognition rate and 91.2% emphatic stress discrimination rate, respectively. Subvocal speech corpus transcripts were synthesized into prosodic speech using personalized, digital voices unique to each participant, then evaluated by naïve listeners (n=12). Listeners consistently rated our sEMG-based digital voice as having greater intelligibility, acceptability, emphasis discriminability and vocal affinity than the state-of-the-art electrolarynx (EL) speech aid used by laryngectomees. Having achieved these capabilities with lengthy post-processing of single phrases, we now aim to advance this technology in Phase II by solving the more fundamental challenges of transcribing prosodic speech and tracking variations in intonation and timing in near-real-time to restore conversational interactions in everyday life. To achieve this goal, our team of engineers at Altec Inc. is partnering with the world’s leading provider of personalized digitized voice for AAC (VocaliD, Inc), and world-class laryngeal cancer clinical experts (Massachusetts General Hospital) to develop algorithms for transcribing prosodic speech and tracking variations in intonation and timing throughout narratives, monologues and conversations (Aim 1); design MyoVoice™ system for near real-time mobile use (Aim 2); and evaluate the prototype system for conversational efficacy (Aim 3). Our milestone is to demonstrate within-subject improvements in ease-of-use, functional efficacy, and social reception amongst post-laryngectomy participants using our sEMG-based digital voice when compared to their typical EL speech aid. The final deliverable will consist of a single 4-contact sensor veneer and cross-platform, near-real-time mobile software that can operate on an AAC tablet or mobile device. Once commercialized, our vision for the future of this device is for a person—who is facing the devastating need to undergo laryngectomy—to have their voice banked and subvocal models trained such that immediately following surgery, they can receive a custom MyoVoice™ system to restore their original voice.