Development of a Chatbot for Personalized Mental Health Support using NLP Techniques
Vanga Ekambram1, Kusuma Saketh2, Pamula Parthi Dinesh Chary3, Mangali Pavan Kumar4 , G.Sruthi5 , Dr.B.Venkataramana6
1 Student, BTech CSE(DS) 4th year, Holy Mary Inst of Tech and Science, Hyderabad, TG, India,
vangaekambram@gmail.com
2 Student, BTech CSE(DS) 4th year, Holy Mary Inst of Tech and Science, Hyderabad, TG, India,
kusumasaketh92@gmail.com
3 Student, BTech CSE(DS) 4th year, Holy Mary Inst of Tech and Science, Hyderabad, TG, India,
dineshcharypamulaparthi@gmail.com
4 Student, BTech CSE(DS) 4th year, Holy Mary Inst of Tech and Science, Hyderabad, TG, India,
m.pavankumar4413@gmail.com
5 Asst prof, CSE(DS), Holy Mary Inst of Tech and Science, Hyderabad, TG, India,
geejulasruthi@gmail.com
6 Assoc prof, CSE(DS), Holy Mary Inst of Tech and Science, Hyderabad, TG, India,
venkataramana.b@hmgi.ac.in
Abstract
Mental health disorders such as stress, anxiety, depression, and emotional instability are rapidly increasing across all age groups due to fast-paced lifestyles, academic and professional pressures, social isolation, and limited emotional support systems. Despite growing awareness, access to timely psychological care remains inadequate for many individuals because of high consultation costs, long waiting periods, social stigma, lack of awareness, and the shortage of qualified mental health professionals—especially in rural and underserved regions. These limitations create a significant gap between the need for mental health support and the availability of reliable assistance, highlighting the urgent requirement for scalable, accessible, and stigma-free digital solutions that can provide immediate emotional guidance and early intervention. Advancements in Artificial Intelligence (AI) and Natural Language Processing (NLP) have enabled the development of intelligent conversational systems capable of understanding human language, detecting emotions, recognizing user intent, and generating empathetic responses in real time. This project proposes a personalized mental health support chatbot that integrates sentiment analysis, emotion recognition, intent classification, conversational context tracking, and safety-aware response generation to deliver meaningful emotional assistance, coping strategies, wellness recommendations, and motivational support. The system also incorporates crisis-detection mechanisms that identify severe distress or self-harm indicators and guide users toward professional or emergency help when necessary. While not a replacement for licensed therapists, the chatbot functions as a privacy-preserving, always-available digital companion that promotes emotional awareness, reduces stigma, and enhances the accessibility of early mental health support in today’s technology-driven world.
Keywords: Conversational AI, Emotion Recognition, Mental Health Support, NLP, Sentiment Analysis
