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.

言语中的分裂是对话中常见的人工制品，但是在整个世界上有超过7000万人的社区口吃的个人中，它们尤其普遍。有充分记录的是，结结巴巴的人们始终经历就业歧视，减少劳动力市场成果和社会污名。越来越普遍地使用排除语音激活的人工智能（AI），这些人工智能（AI）经过设计，训练和测试而没有考虑与社会规范不同的沟通，可以成为对诸如口臭的个人等社区的日常生活参与和就业机会的障碍。更糟糕的是，这种技术可以积极区分在就业背景下言语差异的人。因此，迫切需要努力减少这些障碍，并赋予具有沟通差异和疾病的人们的能力，以充分而公平地访问各种形式的语音识别系统，包括个人语音助手，自动化电话接口以及求职准备和雇用软件。该融合加速器项目提出了一种多学科，使用的启发方法，利用AI的最先进进展，以及对口吃的性质和经验的深刻理解，以及增加语音激活系统使用的法律，道德和劳动力市场的影响。该项目与各种利益相关者合作，将开发和分发高影响力的解决方案，以应对主要的国家和全球挑战：语音激活AI的可访问性和公平性，以表达不足的演讲。提高语音激活AI适当解析和解码的能力，不仅适用于口吃的人，而且对于其他弱势群体和社会而言，所有演讲者在某种程度上都在某种程度上是构图，而在融合技术方面可以通过限制和实施限制，因此所有演讲者都在某种程度上不受欢迎，而不仅适用于其他脆弱的人群和整个社会，不仅适合其他弱势群体和社会，还可以提高生活质量，机会和访问能力，不仅是针对其他弱势群体和社会的能力，还可以提高生活质量和访问能力。对于口吃的人来说，技术可以访问和公平。该项目将通过开发包容性培训和测试数据集以及可访问的自动语音识别（ASR）和新型ASR深度学习模型的开发来有助于提高知识。拟议的研究将建立对口吃影响和与人工智能激活技术中的AI可访问性和公平性相交的性质和相交的性质和经验的融合和整体理解，确定在口吃的人中访问现有语音激活AI的障碍和促进者，并评估指南和审计工具的有效性和审计工具的有效性。最后，这项活动将与合作伙伴的多学科和跨部门网络相关联，以确保参与性研究设计，以专注的计划招募多样化的参与者，广泛传播发现，并采用了新的，可访问的技术。该奖项反映了NSF的立法使命，并被认为是通过基金会的智力评估来评估的，并且值得通过评估来进行评估。