Amirreza Vishteh

I graduated with a Bachelor's degree from Iran University of Science and Technology (IUST). Currently, I am pursuing a Master's degree in Computer Engineering at Sharif University of Technology.

Psychological Health Chatbot: Enhancing Mental Well-being with AI

Model

Overview

The Psychological Health Chatbot is designed to assist individuals in their mental health journey by leveraging advanced natural language processing (NLP) techniques. Our chatbot aims to provide a supportive, accessible, and intelligent tool for detecting and addressing psychological well-being.

📄 Read our full paper here: ACL Anthology

Team Members

Sadegh Jafari
Mohammad Erfan Zare
Amirreza Vishteh
Mirzae Melike
Zahra Amiri
Sima Mohammadparast
Sauleh Eetemadi

Data Collection
Model Training
Evaluation
Results
Conclusion
Future Work

1. Data Collection

To ensure the chatbot effectively understands and responds to mental health queries, we compiled a diverse dataset of conversations related to psychological well-being. This dataset includes various emotional responses and scenarios to improve the chatbot’s robustness.

Data Collection

2. Model Training

We fine-tuned a pre-trained transformer-based model to enhance contextual understanding and response accuracy. Key aspects of training included:

Optimizing hyperparameters
Incorporating advanced emotion recognition techniques
Improving contextual relevance in responses

Model Training

3. Evaluation

Our chatbot underwent rigorous evaluation through user testing. We assessed:

Emotion detection accuracy
User satisfaction rates
Response relevance and coherence

Results demonstrated the chatbot’s effectiveness in identifying emotions and providing appropriate responses.

4. Results

Our final evaluation yielded promising results, with user satisfaction rates reaching [insert percentage]%. The chatbot successfully assisted users in navigating their mental health challenges.

Results Results

Conclusion

The Psychological Health Chatbot represents a significant step in integrating AI-driven solutions for mental health support. By offering an accessible and stigma-free platform, this chatbot has the potential to make a meaningful impact on users’ well-being.

Future Work

Future developments will focus on:

Enhancing emotional detection capabilities
Integrating personalized feedback mechanisms
Improving multi-turn conversational depth

📄 For more details, read our paper: ACL Anthology

2025 1
2024 4
2023 2
2021 2
2020 3

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