Euphonia publications
With your help, we have gathered more than 1 million utterances (1400 hours of data) from more than a thousand speakers. This data has enabled us to refine our speech algorithms to better understand different types of speech. Here is a complete list of all the blog posts and papers we have published related to these research efforts.
Blog posts and announcements
Research
Personalized ASR Models from a Large and Diverse Disordered Speech Dataset (2021)
Speech impairments affect millions of people, with underlying causes ranging from neurological or genetic conditions to physical impairment, brain damage or hearing loss. Similarly, the resulting speech patterns are diverse, including stuttering, dysarthria, apraxia, etc., and can have a detrimental impact on self-expression, participation in society and access to voice-enabled technologies.
Recent papers
ICASSP 2023
Speech Intelligibility Classifiers From Half A Million Utterances
Subhashini Venugopalan, Jimmy Tobin, Samuel J. Yang, Katie Seaver, Richard Cave, Pan-Pan Jiang, Neil Zeghidour, Rus Heywood, Jordan Green, Michael P. Brenner
ICASSP 2023
An analysis of degenerating speech due to progressive dysarthria on ASR performance
Katrin Tomanek, Katie Seaver, Pan-Pan Jiang, Richard Cave, Lauren Harrel, Jordan R. Green
Interspeech 2022
Assessing ASR Model Quality on Disordered Speech using BERTScore
Jimmy Tobin, Qisheng Li, Subhashini Venugopalan, Katie Seaver, Richard Cave, Katrin Tomanek
ICASSP 2022
Personalized Automatic Speech Recognition Trained on Small Disordered Speech Datasets
Jimmy Tobin and Katrin Tomanek
FRONTIERS IN COMPUTER SCIENCE, VOL. 4 - 2022
Characterizing Dysarthria Diversity for Automatic Speech Recognition: A Tutorial From the Clinical Perspective
Hannah P. Rowe, Sarah E. Gutz, Marc F. Maffei, Katrin Tomanek, Jordan R. Green
EMNLP 2021
Residual Adapters for Parameter-Efficient ASR Adaptation to Atypical and Accented Speech
Katrin Tomanek, Vicky Zayats, Dirk Padfield, Kara Vaillancourt, Fadi Biadsy
Interspeech 2021
Disordered Speech Data Collection: Lessons Learned at 1 Million Utterances from Project Euphonia
Robert L. MacDonald, Pan-Pan Jiang, Julie Cattiau, Rus Heywood, Richard Cave, Katie Seaver, Marilyn A. Ladewig, Jimmy Tobin, Michael P. Brenner, Philip C. Nelson, Jordan R. Green, Katrin Tomanek
Interspeech 2021
Automatic Speech Recognition of Disordered Speech: Personalized models outperforming human listeners on short phrases
Jordan R. Green, Robert L. MacDonald, Pan-Pan Jiang, Julie Cattiau, Rus Heywood, Richard Cave, Katie Seaver, Marilyn A. Ladewig, Jimmy Tobin, Michael P. Brenner, Philip C. Nelson, Katrin Tomanek
Interspeech 2021
Comparing Supervised Models And Learned Speech Representations For Classifying Intelligibility Of Disordered Speech On Selected Phrases
Subhashini Venugopalan, Joel Shor, Manoj Plakal, Jimmy Tobin, Katrin Tomanek, Jordan R. Green, Michael P. Brenner
Interspeech 2021
A Voice-Activated Switch for Persons with Motor and Speech Impairments: Isolated-Vowel Spotting Using Neural Networks
Shanqing Cai, Lisie Lillianfeld, Katie Seaver, Jordan R. Green, Michael Brenner, Philip Q Nelson, D. Sculley
Interspeech 2019
Personalizing ASR for Dysarthric and Accented Speech with Limited Data
Joel Shor, Dotan Emanuel, Oran Lang, Omry Tuval, Michael Brenner, Julie Cattiau, Fernando Vieira, Maeve McNally, Taylor Charbonneau, Melissa Nollstadt, Avinatan Hassidim, Yossi Matias