SpeechMedAssist adapts SpeechLMs for medical consultations via two-stage training (text knowledge injection then limited speech re-alignment) using 10k synthesized samples and outperforms baselines in effectiveness and robustness.
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A systematic analysis of perceptual speech features finds stable associations with symptom severity in depression, anxiety, and ADHD across multiple datasets using XGBoost with SHAP and LIME.
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SpeechMedAssist: Efficiently and Effectively Adapting Speech Language Models for Medical Consultation
SpeechMedAssist adapts SpeechLMs for medical consultations via two-stage training (text knowledge injection then limited speech re-alignment) using 10k synthesized samples and outperforms baselines in effectiveness and robustness.
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Exploration of Perceptual Speech Features for Clinical Decision-Support in Mental Health Care
A systematic analysis of perceptual speech features finds stable associations with symptom severity in depression, anxiety, and ADHD across multiple datasets using XGBoost with SHAP and LIME.