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New LLM 'AudiPsy' assesses depression using multimodal reasoning

By PulseAugur Editorial · [1 sources] ·

Researchers have developed AudiPsy, a novel omni-LLM designed for assessing depression through spoken counseling conversations. This system uniquely integrates textual and acoustic evidence, along with emotional incongruence, using an Observation-Assessment-Summary (OAS) paradigm. The OAS framework incrementally processes multimodal observations, performs contextualized assessments, and maintains an evolving dialogue summary. Experiments on the DAIC-WoZ dataset show AudiPsy outperforms existing depression detection methods and general-purpose LLMs, while also demonstrating improved reasoning quality. AI

IMPACT This research could lead to more nuanced and accurate AI-driven mental health assessment tools.

RANK_REASON The cluster describes a new research paper detailing a novel LLM for a specific application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New LLM 'AudiPsy' assesses depression using multimodal reasoning

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The cluster describes a new research paper detailing a novel LLM for a specific application. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Chuanbo Zhu, Run Luo, Weibo Zhao, Yue Li, Kun Qian, Qiang Qu, Yike Guo, Minghuan Tan, Wei Xue ·

    AudiPsy: Evidence-Grounded Multimodal Reasoning over Spoken Counseling Conversations for Depression Assessment

    arXiv:2610.27567v1 Announce Type: cross Abstract: Depression assessment from counseling speech requires integrating textual and acoustic psychological evidence across turns, yet existing end-to-end classification approaches lack explicit multimodal evidence interpretation and con…

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