This paper presents TherapEase, a chatbot designed to support students’ mental health using natural language processing. TherapEase focuses on providing personalized guidance tailored to students’ emotional states, offering timely support amid academic and social pressures. The effectiveness of chatbots like TherapEase in addressing mental health challenges among students is explored, highlighting their potential as accessible and interactive support tools. The development of a question-answering chatbot system leveraging embeddings and retrieval techniques is detailed, enhancing its ability to provide comprehensive responses to user queries. Advanced technologies such as Hugging Face embeddings and Facebook AI Similarity Search are employed for efficient data processing, ensuring a seamless user experience while delivering valuable insights and support to students. This research contributes to the advancement of technology-driven mental health interventions, aiming to make support services more accessible and effective for student populations worldwide.

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TherapEase: A Chatbot for Student Mental Health

  • Mohammad Zeeshan,
  • Ishika Saini,
  • Komal,
  • Komal,
  • Preeti Nagrath

摘要

This paper presents TherapEase, a chatbot designed to support students’ mental health using natural language processing. TherapEase focuses on providing personalized guidance tailored to students’ emotional states, offering timely support amid academic and social pressures. The effectiveness of chatbots like TherapEase in addressing mental health challenges among students is explored, highlighting their potential as accessible and interactive support tools. The development of a question-answering chatbot system leveraging embeddings and retrieval techniques is detailed, enhancing its ability to provide comprehensive responses to user queries. Advanced technologies such as Hugging Face embeddings and Facebook AI Similarity Search are employed for efficient data processing, ensuring a seamless user experience while delivering valuable insights and support to students. This research contributes to the advancement of technology-driven mental health interventions, aiming to make support services more accessible and effective for student populations worldwide.