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Stuttered Speech Data for Stutterers, with Stutterers, by Stutterers: Insights from Stuttering Advocates

Published on: March 10, 2025
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Jingjin Li

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Automatic Speech Recognition (ASR) systems have long struggled to accurately recognize and process stuttered speech, largely due to their training on fluency-biased datasets. As a result, people who stutter (PWS) frequently encounter challenges when using voice-activated technologies, automated transcription services, and other speech-based AI tools. This lack of inclusivity and accessibility also reinforces social and technological barriers for people with speech differences. Funded by the Patrick J. McGovern Foundation, our project seeks to change that by creating a representative, community-driven dataset of stuttered speech.  

Centering the perspectives of the community from the very beginning, we conducted in-depth interviews with eight stuttering advocates, including researchers, nonprofit leaders, and community organizers to gather their insights on how to structure a community-centered data collection that is ethical, empowering, and inclusive. Six of our interviewees are PWS and two are long-term allies for the stuttering community.

Background of the Stuttering Advocates

  • Maya Chupkov – PWS, CEO & founder of Proud Stutter, a podcast challenging societal perceptions of stuttering, and filmmaker working on a documentary about race and stuttering.
  • Naomi Rodgers, Ph.D., CCC-SLP – PWS, assistant professor at the University of Iowa and leader of the Iowa Stuttering Lab, focusing on clinical intervention, counseling, and community support.
  • Edmund Metzold – PWS, senior healthcare technology specialist and leader in the Passing Twice LGBTQ+ and stuttering support network.
  • Jia Bin, M.A. – PWS, Ph.D. researcher at Michigan State University, specializing in stuttering research, and co-founder of StammerTalk (口吃说), an online community for Chinese-speaking PWS.
  • Rong Gong, Ph.D. – PWS, principle research scientist at Microsoft and co-founder of StammerTalk (口吃说), a grassroots online community for Mandarin speaking people who stutter. With the support of StammerTalk community, Rong led the development of AS-70, the first and largest Mandarin stuttered speech dataset for ASR.
  • Tracy Wang, Ph.D. – PWS, Principal Applied Scientist at Oracle and a core member of StammerTalk (口吃说), co-leading the development of AS-70.
  • Nan Bernstein Ratner, Ed.D., F-, H-ASHA, F-AAAS, Board Certified Specialist in Stuttering, Cluttering, and Fluency Disorders – Professor at the University of Maryland, expert in fluency disorders, and co-director of FluencyBank, one of the most popular stuttering research corpus.
  • Aidan Sank – Executive Director of SPACE, a nonprofit dedicated to increasing visibility and agency for PWS through storytelling and community engagement.

Community Perspectives on Empowering Data Collection Process

Our work is deeply valued by the stuttering community, as reflected in the voices of our interviewees. Nan Bernstein Ratner, professor in the Department of Hearing and Speech Sciences at the University of Maryland, College Park, commented on the potential impact of the project and shared her past data collection experience:

“I think it’s a really good idea. We definitely have done it before. I’m happy to consult with you on how to do it again.”

Jia Bin, a speech and language researcher and co-founder of StammerTalk (口吃说), emphasized,

“I love working with you because of the human-centered, stutter-centered approach. That’s why we do what we do. You are creating a space where people who stutter can contribute in a meaningful way, and I fully support that.”

Edmund Metzold, co-founder of Passing Twice, an LGBTQ+ and stuttering support organization, also noted:

“Just the fact that the dataset of people who stutter is created by people who stutter, I think, will naturally appeal to many people.”

This community-driven approach ensures authenticity and trust, as echoed by Aidan Sank, Executive Director of SPACE, a nonprofit organization working to create more space for stuttering and change the way the world listens, commenced on our data collection plan,

“The data collection plan sounds effective, and deeply needed. I think this is going to make a huge difference, and I love that you are engaging with such a community-centered process. The combination of unscripted conversation and voice command recitation will create a really robust dataset for learning and development.”

Rather than treating data collection as a transactional process, we focus on the personal benefits of this data collection process to people who stutter. Maya Chupkov, founder of Proud Stutter, emphasized the design of spontaneous conversation of our data collection process:

“Personal interaction—introducing yourself, sharing a bit of your background, and explaining why you’re doing this—could make participants feel more empowered and invested.”

Naomi Rodgers, a researcher leading the Iowa Stuttering Lab, commented on our plan of having people who stutter as data collectors,

“If you’re aiming for this to be community-led and to capture as much stuttering as possible, then having interviewers who stutter could be a good approach. It helps create a sense of safety within the interview.”

Summary and Next Steps

Our research highlighted the importance of recruiting both PWS and allies as data collectors, diversity in participants, and designing tasks that encourage natural speech patterns. Additionally, we are prioritizing transparent data governance, fair compensation, and ethical consent practices. We have already made significant progress:

  • Finalizing legal agreements for data contributor and usage.
  • Recruited a diverse group of participants and data collectors.
  • Designed a balanced set of speech tasks that authentically represent stuttering patterns.
  • Implementing improved annotation strategies to accurately capture stuttering events.

As we begin data collection in the coming weeks, we remain committed to an inclusive, ethical, and community-driven process. We are grateful to our stuttering advocates for their guidance and look forward to continued collaboration in making ASR technology more accessible for all. For a detailed breakdown of our findings, including insights from each interviewee, please continue reading the full report here.

Contributing Your Voice

If you are a person who stutters and are interested in contributing your stuttered speech, please complete this survey to sign up.

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Shaomei Wu

Shaomei was a staff research scientist and engineer at Facebook AI and Instagram, leading large cross-org teams on “tech for good” initiatives and products, including Accessibility, AI for Inclusion, and Instagram Equity. She received her PhD at Cornell University studying viralness and collective behaviors in large social networks. As a person of color, an immigrant, a woman in tech, as well as a person who stutters, Shaomei has experienced intersectionality and marginalizations first-hand, and is committed to leverage her technical expertise and lived experiences to create a new paradigm of technologies that is truly equitable and empowering for all.

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Niranjan Sivakumar

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Ran Wei

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Prior to AImpower, Ran was a research manager at Meta, leading data science and UX research teams to shape business and product strategies. With an educational background in statistics and psychology, Ran’s experiences spanned over NGOs and the tech industry, from evaluating international development programs to building user-centered technology products.

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Kaiton Williams

Kaiton is a Silicon Valley engineer turned Human-Computer Interaction researcher. He oversees investments at Impact America Fund with a particular interest in the challenges of connecting community-oriented research and design with scalable technology production and investment. Previously, Kaiton held senior engineering and architecture roles at Microsoft for over a decade, where he helped build and manage early web applications for billions of users. He then went on to earn his Ph.D. in Information Science from Cornell University, where his ethnographic research focused on the experiences of tech entrepreneurs building products for and from communities outside of Silicon Valley’s “normal.”

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Salmana Ahmed

Salmana is a Principal on Global Programmes team at Luminate, leading Luminate’s work in Africa, Asia, and Latin America. She previously grew and supported the foundation’s Data & Digital Rights portfolio. Prior to joining Luminate, Salmana was a Senior Programme Manager at the Mo Ibrahim Foundation where she helped develop the strategy for the Ibrahim Forum and co-managed the production of the Ibrahim Index of African Governance and Forum reports. She previously served as a Consultant at the Open Data Institute, as an editorial assistant at Royal United Services Institute, and as Deputy Project Manager at the Centre for Religion and Geopolitics.

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Ben Lickly

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Qisheng Li

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Jingjin Li

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Jingjin received her Ph.D. degree in Information Science from Cornell University.

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Mike Meaney

Mike Meaney is a research and product leader with over a decade of experience building inclusive technologies. He began his career as a middle school science teacher and has since worked in R&D and Product Management at Multiverse, Facebook, and Arizona State University. Through AImpower, he is conducting research and development to build a new company focused on serving communities underserved by traditional tech. 

Mike holds a Ph.D. from the University of Cambridge, where he was a Gates Cambridge Scholar and a Visiting Research Fellow at the Brookings Institution.

Mike Meaney has stuttered all his life and has been actively involved in the addiction recovery community for more than a decade. 

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Greg Price

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Huynh Yen Nhi Tran

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Adedotun Bello

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Charan Sridhar

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Aishwarya Pai

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Meredith Ringel Morris

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Gilly Leshed

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Yu-Ru Lin

Yu-Ru Lin an associate professor at School of Computing and Information, University of Pittsburgh. She is interested in studying social and political networks, as well as computational and visualization methods for understanding network data. Her work has focused on large-scale community dynamics, high-dimensional (rich-context) social information summarization and representation. Yu-Ru leads the PITT Computational Social Dynamics Lab (PICSO LAB). Her most recent research and services interrogate structural inequalities and systematic oppression of marginalized groups in different social context.

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Channarong Intahchomphoo

ชาญณรงค์ อินต๊ะชมภู

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Ting-an Lin

Ting-an is an AI ethics researcher, socio-political and feminist philosopher, and community builder dedicated to aligning sociotechnical systems with democratic values and structural justice. Combining scholarly rigor with deep care for humanity, she collaborates across disciplines to conceptualize and shape alternative sociotechnical orders where everyone, especially the marginalized, can thrive.

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Xinru Tang

Xinru is a researcher working at the intersection of HCI, accessibility and responsible AI. She has extensive experience working with people across disabilities and scholars across disciplines. At AImpower, she is committed to centering communities’ lived experiences in the design and development of truly human-centered AI and emerging technologies. She is expected to receive her PhD in Informatics from University of California, Irvine.

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