3 papers
cs.SD2025
Deploying UDM Series in Real-Life Stuttered Speech Applications: A Clinical Evaluation Framework
Eric Zhang, Li Wei, Sarah Chen +1
Stuttered and dysfluent speech detection systems have traditionally suffered from the trade-off between accuracy and clinical interpretability. While end-to-end deep learning model…
cs.AI2025
A Comparative Study of Controllability, Explainability, and Performance in Dysfluency Detection Models
Eric Zhang, Li Wei, Sarah Chen +1
Recent advances in dysfluency detection have introduced a variety of modeling paradigms, ranging from lightweight object-detection inspired networks (YOLOStutter) to modular interp…
cs.AI2025
Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications
Eric Zhang
Stuttering affects approximately 1% of the global population, impacting communication and quality of life. While recent advances in deep learning have pushed the boundaries of auto…