NSF Convergence Accelerator Track H: An Inclusive, Human-Centered, and Convergent Framework for Transforming Voice AI Accessibility for People Who Stutter

在一个越来越多地通过语音激活人工智能（voice AI）导航的社会中，口吃者——代表300多万美国人和全球大约8000万人——面临着一个主要障碍：现有的语音人工智能技术经常无法识别不流利的语音模式，导致在可访问性、就业和社会包容方面的一系列不利因素。该项目通过将语音人工智能转变为一个理解和尊重人类语言多样性的包容性平台，解决了这一紧迫问题。通过从口吃者的角度重新构想语音人工智能，该项目不仅为历史上被边缘化的群体的事业提供了支持；它还增强了每个人的语音技术，因为所有的说话者在某种程度上都是不流利的。与NSF的使命一致，这些进步通过拥抱和理解不同的语言模式来促进科学进步，促进国家福利，并为一个更具包容性的社会做出贡献。实施以人为本和融合的范例，该项目旨在实现四个关键的协同目标：(1)培养一个多学科和多部门的利益相关者网络，以引导有影响力的结果；(2)阐明以用户为中心的语音人工智能的整体愿景；(3)设计一套全面的自适应语音人工智能解决方案，并建立评估测试平台；(4)起草管理相关语音人工智能风险的指导方针。利用尖端的人工智能技术，该项目将率先为无障碍自动语音识别（ASR）提供包容性训练和测试数据集以及注释，并开发先进的ASR深度学习模型。所采用的方法包括迭代研究，与最终用户的持续接触，以查明现有和未来的障碍，以及对解决方案有效性的严格评估。总体目标是通过一个对所有人都可访问和响应的生态系统来改变语音人工智能，从而确保每个人的声音都能被听到。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

In a society increasingly navigated through voice-activated artificial intelligence (voice AI), people who stutter-representing over 3 million Americans and roughly 80 million individuals globally-face a major barrier: existing voice AI technologies frequently fail to recognize disfluent speech patterns, leading to a cascade of disadvantages in accessibility, employment, and societal inclusion. This project addresses this pressing concern by transforming voice AI into an inclusive platform that comprehends and respects the diversity of human speech. By reimagining voice AI through the lens of those who stutter, this project not only champions the cause of a historically marginalized group; it also enhances voice technology for everyone, because all speakers are disfluent to some extent. Aligning with NSF's mission, these advancements promote scientific progress, foster national welfare, and contribute to a more inclusive society by embracing and understanding diverse speech patterns.Operationalizing a human-centered and convergent paradigm, this project sets out to accomplish four key synergistic objectives: (1) cultivating a multidisciplinary and multi-sectoral network of stakeholders to steer impactful outcomes, (2) articulating a holistic vision for user-centric voice AI, (3) designing a comprehensive set of adaptive voice AI solutions and establishing a testbed for their evaluation, and (4) drafting guidelines for managing associated voice AI risks. Harnessing cutting-edge AI technology, the project will pioneer inclusive training and test datasets as well as annotation for accessible automatic speech recognition (ASR) and develop advanced ASR deep learning models. The adopted methodology encompasses iterative research, continuous engagement with end-users to pinpoint existing and future barriers, and stringent evaluations of solution efficacy. The overarching goal is to transform voice AI, through an ecosystem that is accessible and responsive to all, thereby ensuring that every voice is heard.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.