AI PsyRoom: Artificial Intelligence Platform for Segmented Yearning and Reactive Outcome Optimization Method (2506.06740v1)

Abstract: Psychological counseling faces huge challenges due to the growing demand for mental health services and the shortage of trained professionals. LLMs have shown potential to assist psychological counseling, especially in empathy and emotional support. However, existing models lack a deep understanding of emotions and are unable to generate personalized treatment plans based on fine-grained emotions. To address these shortcomings, we present AI PsyRoom, a multi-agent simulation framework designed to enhance psychological counseling by generating empathetic and emotionally nuanced conversations. By leveraging fine-grained emotion classification and a multi-agent framework, we construct a multi-agent PsyRoom A for dialogue reconstruction, generating a high-quality dialogue dataset EmoPsy, which contains 35 sub-emotions, 423 specific emotion scenarios, and 12,350 dialogues. We also propose PsyRoom B for generating personalized treatment plans. Quantitative evaluations demonstrate that AI PsyRoom significantly outperforms state-of-the-art methods, achieving 18% improvement in problem orientation, 23% in expression, 24% in Empathy, and 16% in interactive communication quality. The datasets and models are publicly available, providing a foundation for advancing AI-assisted psychological counseling research.

• The paper introduces a multi-agent AI framework that generates over 12,000 empathetic dialogues and the comprehensive EmoPsy dataset covering 35 sub-emotions.
• It employs concurrent emotion recognition with a multi-agent simulation to reduce response latency and improve empathetic communication by up to 24%.
• The framework generates personalized treatment plans based on established psychological methods, marking a significant advancement in AI-assisted mental health care.

AI PsyRoom: Enhancing Psychological Counseling with AI

The paper presents AI PsyRoom, a multi-agent simulation framework designed to address the limitations of traditional psychological counseling methods by leveraging advancements in artificial intelligence, particularly LLMs. The framework aims to enhance psychological counseling through the generation of empathetic dialogues that are finely tuned to individual emotions. This work is significant given the growing global demand for mental health services and the concurrent shortage of trained professionals.

Key Contributions

The AI PsyRoom framework is composed of two main components: PsyRoom A and PsyRoom B. PsyRoom A specializes in generating high-quality dialogues through a multi-agent system, producing a dataset named EmoPsy. This dataset includes 35 sub-emotions and over 12,000 dialogues, far exceeding previous resources available for psychological counseling research. PsyRoom B focuses on generating personalized treatment plans by leveraging fine-grained emotion analysis, showcasing significant improvements in various metrics such as empathy and interactive communication.

Methodology

The framework employs a multi-agent architecture with distinct roles: a client agent, a counselor agent, and a psychology professor agent for evaluation. PsyRoom A uses these agents to simulate real-life counseling interactions, allowing for iterative improvements until a satisfactory dialogue quality is reached. This approach contrasts with traditional sequential emotion analysis models by utilizing concurrent emotion recognition, which reduces response latency and enhances conversational coherence.

PsyRoom B further refines these interactions by generating tailored treatment plans derived from these dialogues. The treatment plans are grounded in well-established psychological frameworks such as CBT and EFT, incorporating evidence-based strategies to address individual emotional difficulties.

Numerical Results

Quantitative evaluations highlight PsyRoom's superiority over existing methods; improvements are noted across several dimensions:

• Problem orientation improved by 18%
• Compassion by 23%
• Empathy by 24%
• Interactive communication quality by 16%

These enhancements underscore the framework's capability to emulate the nuanced therapeutic interactions critical to effective psychological counseling.

Implications and Future Directions

AI PsyRoom addresses fundamental challenges in psychological counseling by integrating nuanced emotional modeling within AI systems. The public availability of the EmoPsy dataset broadens the foundation for future research within AI-assisted psychological services. The framework’s ability to provide dynamic, contextually-appropriate interventions marks a significant advancement in the application of AI to mental health services.

The research sets a precedent for future developments while acknowledging limitations such as the need for multimodal data integration and clinical validation to ensure long-term effectiveness in real-world counseling environments. Future work should strive to incorporate these elements to enhance interpretative capabilities and further align AI systems with human counseling expertise.

In conclusion, AI PsyRoom represents a pivotal step in advancing psychological counseling through AI, providing researchers and practitioners with novel tools and datasets to address the ever-growing demand for mental health services across the globe.