Project Euphonia: advancing inclusive speech recognition through expanded data collection and evaluation
Speech recognition models, predominantly trained on standard speech, often exhibit lower accuracy for individuals with accents, dialects, or speech impairments. This disparity is particularly pronounced for economically or socially marginalized communities, including those with disabilities or diver...
Saved in:
| Main Authors: | Alicia Martin, Robert L. MacDonald, Pan-Pan Jiang, Marilyn Ladewig, Julie Cattiau, Rus Heywood, Richard Cave, Jimmy Tobin, Philip C. Nelson, Katrin Tomanek |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-06-01
|
| Series: | Frontiers in Language Sciences |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/flang.2025.1569448/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Machine Learning-Based Scoring System to Predict the Risk and Severity of Ataxic Speech Using Different Speech Tasks
by: Bipasha Kashyap, et al.
Published: (2023-01-01) -
Characteristics of Dysarthria in Post-Stroke Patients
by: Sofija Bajagić, et al.
Published: (2025-07-01) -
Recent advancements in automatic disordered speech recognition: A survey paper
by: Nada Gohider, et al.
Published: (2024-12-01) -
Dysarthria Severity detection Using Recurrent and Convolutional Neural Networks
by: Amina Hamza, et al.
Published: (2024-12-01) -
Management of Dysarthria in Amyotrophic Lateral Sclerosis
by: Elena Pasqualucci, et al.
Published: (2025-07-01)