Speech AI for All: Promoting Accessibility, Fairness, Inclusivity, and Equity

April 27, 2025 in Yokohama, Japan

Workshop Overview

Trained and optimized for typical and fluent speech, speech AI works poorly for people with speech diversities, often cutting them off from speaking and misinterpreting their speech. The increasing deployment of speech AI in automated phone menus, AI-conducted job interviews, and everyday devices poses tangible risks to people with speech diversities. To mitigate these risks, this workshop aims to build a multidisciplinary coalition and set the research agenda for fair and accessible speech AI. Bringing together a broad group of academics and practitioners with diverse perspectives including HCI, AI, and other relevant fields such as disability studies, speech language pathology, and law, this workshop will establish a shared understanding of the technical challenges for fair and accessible speech AI, as well as its ramifications in design, user experience, policy, society. In addition, the workshop will invite and highlight first-person accounts from people with speech diversities, facilitating direct dialogues and collaboration between speech AI developers and the impacted communities. The key outcomes of this workshop include a summary paper that synthesizes our leanings and outlines the roadmap for improving speech AI for people with speech diversities, as well as a community of scholars, practitioners, activists, and policy makers interested in drivings progress in this domain. Find more details in the workshop proposal.

Call For Participation

This one-day, in-person, and hybrid CHI 2025 workshop invites researchers, practitioners, policy makers, and community members interested in fair and inclusive speech AI technologies to explore the challenges, impact, and opportunities of speech AI for people with speech diversities.

Participants will have the opportunity to directly engage with and learn from impacted communities and experts from technical and non-technical fields to build a deeper understanding of the challenges and opportunities for fair and inclusive speech AI. Leveraging the collective knowledge shared during the workshop, participants will co-create a roadmap for fair and inclusive speech AI, driven by a cross-sector coalition of scholars and stakeholders formed through the workshop.

Participants are encouraged, but not required, to submit position papers, tech demo papers, technical research papers, policy papers, or experience reports and briefs from other fields, under the general theme of understanding and improving speech AI technologies for and with people with speech diversities. Accepted papers will be presented during the workshop as oral or poster presentations, and published on the workshop's website.

Interested participants can apply by completing the application form below to share their background and motivation for participation, with an option to attach a paper of up to ten pages (plus references) in the ACM single-column format.

The workshop organizing team will select participants based on the alignment between the participants' backgrounds and the workshop themes, while striving to assemble a diverse group across a range of disciplines, methodologies, and seniorities.

Themes and Objectives

The workshop will center the lived experiences and expectations of those most affected by disparities in speech AI performance. Based on this grounding, participants will then have opportunities to present and discuss the technical and design challenges and opportunities for fair and accessible speech AI, as well as the norms and public policies that underpin these challenges and opportunities.

Understanding the Lived Experience. We recognize the inherent relational nature of AI disparities and the epistemic privileges held by marginalized communities to identify and address harm. Our workshop aims to elevate the voices of those most affected through our organizing team, invited speakers, and attendees. Accordingly, we will discuss the disparate cognitive and emotional burdens of speech AI, its social impacts on stigmatizing and suppressing speech diversities, and its historical roots in structural inequalities. A further objective under this theme is to outline opportunities for allyship.

Showcasing Solutions. Grounded in the experiences of affected users, our workshop will capture incremental solutions to speech AI inequities. This will include both technical and design approaches proposed by the research, non-profit, and industry communities. For example, we ask: What metrics for speech recognition systems are the most respectful and representative of the experiences of marginalized users? What is the most equitable approach to engage the affected communities in data collection and solution development? How do we balance between long-term capacity builder versus short-term bandage solutions? Through presentations, demos, and discussion, this workshop will offer human-centered technical, measurement, and design recommendations.

Unpacking Norms and Policy. While many developed countries have laws and regulations to protect marginalized groups against systematic inaccessibility and discrimination, current legal and policy frameworks have also been falling behind with the rapid development of AI technologies and new challenges arise. Our workshop will attend to the structures and norms that underlie the challenges and progress in fair and accessible speech AI. We will discuss and propose policy recommendations - such as assessments and requirements for ASR performance parity for both typical and diverse speech, as well as advocacy avenues - such as academic conference accessibility guidelines that accommodate speech diversity.

Resources

Accepted papers

1. How People Living With Amyotrophic Lateral Sclerosis Use Personalized Automatic Speech Recognition Technology to Support Communication

Richard Cave (University College London)

2. Listening to Bias: Tracing Lineage, Impacts, and Paths Forward

Johann Diedrick (New York University / Social Science Research Council, Just Tech Fellow)

3. Bridging the Speech AI Accessibility Gap for Deaf and Hard of Hearing People

Abraham Glasser (Gallaudet University)

4. Towards Temporally Explainable Dysarthric Speech Clarity Assessment

Chitralekha Gupta (National University of Singapore)

5. Inclusivity of AI Speech in Healthcare: A Decade Look Back

Retno Larasati (The Open University, United Kingdom)

6. Automatic Speech Recognition Model Adaptation for Individuals with Autism Spectrum Disorder

Bowon Lee (Inha University)

7. Addressing Non-Pathological Speech Disfluency in AI

Ralph Rose, Ayaka Sugawara, Aina Tanaka (Waseda University)

8. On the Lack of Queer Voices in Diverse Speech Datasets

Brooklyn Sheppard (University of Calgary)

9. Enhancing Mental Health through DSR: Psychological Behavioral Evidence and Future Application Prospects

Su-Jing Wang (CAS Key Laboratory of Behavioral Science, Institute of Psychology)

Discussion topics

Inclusion and Representation: How can we centralize involvement of those who are most impacted be Speech AI? How can we meaningfully involve and include folks?
A Roadmap for Fair Speech AI: What are guiding principles to building long-term solutions regarding Speech AI? For example, what design principles or metrics and measurements can we develop?
Policy: How can HCI collectively partner and influence policy around Speech AI? How can policy allow us to scale inclusive solutions to be adopted widely and to eventually have influence social norms around diverse speech?
Tensions in the “All” of Speech AI for All: What are the tensions (e.g., debates about synthesized speech, the role of transcripts for stuttered speech) within the “all” - communities impacted with Speech AI? How do we navigate that plurality? How can we productively and positively move forward?