NSF Convergence Accelerator Track H: Convergent, Human-Centered Design for Making Voice-Activated AI Accessible and Fair to People Who Stutter

NSF 融合加速器轨道 H：融合、以人为本的设计，使语音激活人工智能对口吃者来说更容易使用且公平

• 批准号: 2235916
• 负责人: Nihar Mahapatra
• 金额: $ 75万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-15 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2235916&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Convergent

Disfluencies in speech are common artifacts in conversation, but they are especially prevalent in individuals who stutter, a community of more than 70 million people worldwide. It is well-documented that people who stutter consistently experience employment discrimination, diminished labor market outcomes, and societal stigma. The increasingly pervasive use of exclusionary voice-activated artificial intelligence (AI), which are designed, trained, and tested without considering communication that varies from societal norms, can act as a barrier to daily life participation and employment access for communities such as individuals who stutter. Worse, such technology can actively discriminate against people with speech differences in employment contexts. Therefore, there is an immediate and compelling need for efforts to reduce these barriers and empower people with communication differences and disorders to fully and equitably access all forms of speech recognition systems, including personal voice assistants, automated phone interfaces, and job-preparation and hiring software. This Convergence Accelerator project proposes a multidisciplinary, use-inspired approach that leverages cutting-edge advances in AI, as well as deep understanding of the nature and experience of stuttering, and the legal, ethical, and labor market implications of increased use of voice-activated systems. In partnership with diverse stakeholders, the project will develop and distribute high-impact solutions to a major national and global challenge: accessibility and fairness of voice-activated AI for disfluent speech. Improving the ability of voice-activated AI to appropriately parse and decode disfluent speech will increase quality of life, equality of opportunity, and access, not just for people who stutter, but also for other vulnerable populations and for society at large because all speakers are disfluent to some extent.The goal of this Convergence Accelerator project is to resolve limitations in voice technology by developing and implementing policy-, advocacy-, and AI-based solutions to make voice technology accessible and fair to people who stutter. The project will contribute to advancing knowledge through development of inclusive training and test datasets as well as annotation for accessible automatic speech recognition (ASR) and development of novel ASR deep learning models. Proposed research studies will establish a convergent and holistic understanding of how the nature and experience of stuttering impacts and intersects with AI accessibility and fairness in voice-activated technology, identify barriers and facilitators of access to existing voice-activated AI among people who stutter, and evaluate the effectiveness of guidelines and audit tools. Finally, this activity will engage a multidisciplinary and multisectoral network of partners to ensure participatory research design with a focused plan to recruit diverse participants, widespread dissemination of findings, and uptake of new, accessible technology.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.

言语不流利是谈话中常见的人工制品，但它们在口吃者中尤其普遍，这是一个全球超过7000万人的社区。有充分的证据表明，口吃的人一直受到就业歧视，劳动力市场的结果减少，以及社会耻辱。越来越普遍地使用排他性的语音激活人工智能（AI），这些人工智能的设计、训练和测试都没有考虑与社会规范不同的沟通，这可能会成为社区日常生活参与和就业的障碍，比如口吃的人。更糟糕的是，这种技术可能会在就业环境中积极歧视有语言差异的人。因此，迫切需要努力减少这些障碍，并使有沟通差异和障碍的人能够充分和公平地使用各种形式的语音识别系统，包括个人语音助理，自动电话界面以及工作准备和招聘软件。这个融合加速器项目提出了一种多学科的，以使用为灵感的方法，利用人工智能的前沿进展，以及对口吃的性质和经验的深刻理解，以及增加使用语音激活系统的法律的，道德和劳动力市场影响。该项目将与不同的利益相关者合作，开发和分发高影响力的解决方案，以应对一项重大的国家和全球挑战：语音激活人工智能的可访问性和公平性。提高语音激活人工智能正确解析和解码不流利语音的能力将提高生活质量、机会平等和可及性，不仅适用于口吃者，也适用于其他弱势群体和整个社会，因为所有说话者在某种程度上都是不流利的。这个融合加速器项目的目标是通过制定和实施政策，倡导和基于人工智能的解决方案，使语音技术对口吃的人来说是可访问的和公平的。该项目将通过开发包容性的训练和测试数据集以及可访问的自动语音识别（ASR）注释和开发新型ASR深度学习模型来促进知识的发展。拟议的研究将对口吃的性质和体验如何影响并与语音激活技术中的AI可访问性和公平性交叉建立一种融合和全面的理解，确定口吃者访问现有语音激活AI的障碍和促进因素，并评估指南和审计工具的有效性。最后，这项活动将涉及一个多学科和多部门的合作伙伴网络，以确保参与性的研究设计与一个有针对性的计划，以招募不同的参与者，广泛传播的结果，并吸收新的，可访问的technology.This奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。