Promoting Mental Self-Disclosure in a Spoken Dialogue System

This paper proposes a mental health spoken dialogue to relax mental illness for university students by acting as an active listener to promote self-disclosure. The proposed system is designed for Mandarin with the specific accent and lexicon in Taiwan which is known as one of the underrepresented spoken languages. To achieve the objective, this work considers three key factors which are high quality speech components including automatic speech recognition and text-to-speech models, and the personalized responses while keeping the trustworthiness and seamless integration among dialogue system components.