4 papers · 1 filter
Mitigating Over-Suppression in Speech Enhancement via Inference-Time Rethink-and-Refine Correction Module
Mike Qu, Yu-Wen Chen, Julia Hirschberg
We present a rethink-and-refine correction module that addresses over-suppression, a common failure mode of speech enhancement (SE) models, where speech cues are suppressed alongsi…
An Audio Language Model-Based Voice Concept Bottleneck Framework for Interpretable Health Assessment
Yu-Wen Chen, Julia Hirschberg
Interpretability is critical in clinical decision support. Concept bottleneck frameworks improve it by representing inputs as human-understandable concepts and restricting predicti…
Hearing Health in Home Healthcare: Leveraging LLMs for Illness Scoring and ALMs for Vocal Biomarker Extraction
Yu-Wen Chen, William Ho, Sasha M. Vergez +8
The growing demand for home healthcare calls for tools that can support care delivery. In this study, we explore automatic health assessment from voice using real-world home care v…
From Who Said What to Who They Are: Modular Training-free Identity-Aware LLM Refinement of Speaker Diarization
Yu-Wen Chen, William Ho, Maxim Topaz +2
Speaker diarization (SD) remains challenging in real-world scenarios due to dynamic environments and unknown speaker numbers. SD is rarely used alone and is typically paired with a…