3 papers
cs.SD2026
Language Models as Semantic Teachers: Post-Training Alignment for Medical Audio Understanding
Tsai-Ning Wang, Lin-Lin Chen, Neil Zeghidour +1
Pre-trained audio models excel at detecting acoustic patterns in auscultation sounds but often fail to grasp their clinical significance, limiting their use and performance in diag…
cs.LG2025
CaReAQA: A Cardiac and Respiratory Audio Question Answering Model for Open-Ended Diagnostic Reasoning
Tsai-Ning Wang, Lin-Lin Chen, Neil Zeghidour +1
Medical audio signals, such as heart and lung sounds, play a crucial role in clinical diagnosis. However, analyzing these signals remains challenging: traditional methods rely on h…
eess.AS2025
MAD Speech: Measures of Acoustic Diversity of Speech
Matthieu Futeral, Andrea Agostinelli, Marco Tagliasacchi +2
Generative spoken language models produce speech in a wide range of voices, prosody, and recording conditions, seemingly approaching the diversity of natural speech. However, the e…