Empathy Bot: Conversational Service for Psychiatric Counseling with Chat Assistant.

Area of Science:

• Artificial Intelligence in Mental Health
• Computational Linguistics
• Affective Computing

Background:

• Previous psychiatric counseling chatbots lacked emotional and ethical awareness.
• Existing systems did not integrate multi-modal user state recognition.

Purpose of the Study:

• To propose an intelligent assistant for psychiatric counseling.
• To enhance chatbot interventions by incorporating user emotional status and ethical judgment.

Main Methods:

• Utilizing high-level features of natural language understanding for dialogue comprehension.
• Implementing multi-modal emotion recognition to assess user's affective state.
• Employing a machine learning-based response generation model for clinical appropriateness.

Main Results:

• The proposed system demonstrates an enhanced ability to understand user dialogues in a clinical psychiatric context.
• Integration of multi-modal emotion recognition allows for more nuanced and context-aware responses.
• The machine learning model generates suitable interventions tailored to the user's emotional and ethical state.

Conclusions:

• The intelligent assistant represents a significant advancement in AI-driven psychiatric counseling.
• Considering emotional status and ethical judgment leads to more effective and personalized therapeutic interactions.
• This approach paves the way for more sophisticated and empathetic AI mental health support systems.