LLMs in the Mental Health Context: Development of the Rafira Platform and the Use of Speech Recognition and AI in Therapy Sessions - Lima Neto, Elze Pinheiro; Conceição, Josivan Mesquita da; Silva, Nádia Félix Felipe da; Fagundes, Thiago da Silva (Anais do Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS), 2026)
This paper presents the development and evaluation of the Rafira platform, an assistant for psychologists that uses speech recognition and Large Language Models (LLMs) for automated transcription and summarization of therapy sessions. This study aims to develop and evaluate an LLM-based platform considering criteria of accuracy, clinical applicability, usability, and ethics. A case study was conducted in three stages: prototype development, testing with psychologists from different approaches, and analysis of the results. Key findings demonstrate technical accuracy, clinical applicability, and the tool's scalability, contributing to the optimization of clinical practice and therapeutic follow-up.