2023 Research Symposium at the ASHA Convention

The Research Symposium is an annual event at ASHA's Convention where clinicians and researchers discuss current research in communication sciences and disorders (CSD). Each year's symposium has a specific research theme. Find out more about the Research Symposium at the ASHA Convention and its associated travel award.

Symposium Topic

Artificial Intelligence in CSD

Coordinated by Jordan Green, PhD (MGH Institute of Health Professions)

Symposium Presentations

Breaking Barriers with AI: Google's Programs for Advancing Accessibility, Communication, and Social Inclusion
Speaker: Philip Nelson (Google Research), Jordan Green (MGH Institute of Health Professions)

Community-supported Shared Infrastructure in Support of Speech Accessibility
Speaker: Mark Hasegawa-Johnson (University of Illinois at Urbana-Champaign)

Working Towards a Measurement Model for Clinical Speech Analytics
Speakers: Julie Liss & Visar Berisha (Arizona State University)

Multimodal Conversational AI for Neurological and Mental Health Assessment
Speaker: Vikram Ramanarayanan (Modality.ai)

Automatic Speech Modeling for the Detection and Measurement of Disease Severity
Speaker: Emily Provost (University of Michigan)

Longitudinal Study of People With ALS Using Personalized Recognition to Support Communication
Speaker: Richard Cave (MND Association)

Implications of Modern Speech Synthesis on Clinical Standards and Outcomes
Speaker: Rupal Patel (Northeastern University)

Brain-Computer Interfaces for the Restoration of Communication
Speaker: Leigh Hochberg (Mass General Research Institute/Harvard Medical School/Providence VA Medical Center)

Decoding Speech from Neuromagnetic Signals
Speaker: Jun Wang (The University of Texas at Austin)

Symposium Publications

Papers based on the 2023 Research Symposium were published in a Forum in the November 2024 issue of Journal of Speech, Language, and Hearing Research (JSLHR) and are open access.

Green, J. (2024). Artificial intelligence in communication sciences and disorders: Introduction to the Forum. Journal of Speech, Language, and Hearing Research, 67(11), 4157–4161. https://doi.org/10.1044/2024_JSLHR-24-00594).
Cave, R. (2024). How people living with ALS use personalized automatic speech recognition technology to support communication. Journal of Speech, Language, and Hearing Research, 67(11), 4186–4202. https://doi.org/10.1044/2024_JSLHR-24-00097
Dash, D., Ferrari, P. and Wang, J. (2024). Neural decoding of spontaneous overt and intended speech. Journal of Speech, Language, and Hearing Research, 67(11), 4216–4225. https://doi.org/10.1044/2024_JSLHR-24-00046
Hasegawa-Johnson, M.A., Zheng, X., Kim, H., Mendes, C. Dickinson, M., Hage, E., Zwilling, C., Channel, M.M., Mattie, L., Hodges, H., Ramig, L., Bellard, M., Shebanek, M., Sari, L., Kalgaonkar, K., Frerichs, D., Bigham, J.P., Findlater, L., Lea, C., Herrlinger, S., Korn, P., Abou-Zahra, S., Heywood, R., Tomanek, K., and MacDonald, B. (2024). Community-supported shared infrastructure in support of speech accessibility. Journal of Speech, Language, and Hearing Research, 67(11), 4162–4175. https://doi.org/10.1044/2024_JSLHR-24-00122
Liss, J. and Berisha, V. (2024). Operationalizing clinical speech analytics: Moving from features to measures for real-world clinical impact. Journal of Speech, Language, and Hearing Research, 67(11), 4226–4232. https://doi.org/10.1044/2024_JSLHR-24-00039
Ramanarayanan, V. (2024). Multimodal technologies for remote assessment of neurological and mental health. Journal of Speech, Language, and Hearing Research, 67(11), 4233–4245. https://doi.org/10.1044/2024_JSLHR-24-00142
Romana, A., Niu, M., Perez, M., Provost, E.M. (2024). FluencyBank Timestamped: An updated dataset for disfluency detection and automatic intended speech recognition. Journal of Speech, Language, and Hearing Research, 67(11), 4203–4215. https://doi.org/10.1044/2024_JSLHR-24-00070
Tobin, J., Nelson, P., MacDonald B., Heywood R., Cave, R., Seaver, K., Desjardins, A., Jiang, P. and Green, J.R. (2024). Automatic speech recognition of conversational speech in individuals with disordered speech. Journal of Speech, Language, and Hearing Research, 67(11), 4176–4185. https://doi.org/10.1044/2024_JSLHR-24-00045

The Research Symposium at ASHA Convention is funded, in part, by a grant from the National Institute on Deafness and Other Communication Disorders (NIDCD).