{
  "id": 5094,
  "url": "https://arxiv.org/abs/2605.01101v2",
  "title": "Virtual Speech Therapist: A Clinician-in-the-Loop AI Speech Therapy Agent for Personalized and Supervised Therapy",
  "summary": "This paper develops Virtual Speech Therapist (VST), an intelligent agent-based platform that streamlines stuttering assessment and delivers customized therapy planning through automated and adaptive AI-driven workflows. VST integrates state-of-the-art deep learning-based stuttering classification, and multi-agent large language model (LLM) reasoning to support evidence-based clinical decision-making. The VST begins with the acquisition and feature extraction of patient speech samples, followed b",
  "authors": "Shakeel Sheikh, Patrick Marmaroli, MD Sahidullah, Slim Ouni, Fabrice Hirsch, Goncalo Leal et al.",
  "category": "research",
  "topics": "healthcare,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-01T21:14:45.000Z",
  "fetched_at": "2026-07-14T16:31:31.210Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5094",
  "original_url": "https://arxiv.org/abs/2605.01101v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}