INTELLIGENT CONVERSATIONAL MODEL FOR MENTAL HEALTH WELLNESS
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Abstract
Mental Health affects how we think, feel and act. Mental Health Problems (MHP) affect our thinking, behavior
and mood. The Conversational Model which is being proposed for MHP is an AI based model for slight to moderate
measurement users who have MHP like depression, mental stress. The learning techniques used in this work is a neural
framework exhibit for setting up the model to give activities and solutions for the users. Here, we are using NLTK for Python
to analyse text. The human responses are captured by designing an intelligent engine. The dataset used to train this neural
framework is designed and curated under the supervision of psychologists. Here the model helps people with light to
moderate level of MHPs by giving simple and easy to perform activities and solutions for their appropriate problems. The
model identifies particular phrases which is matched with the data corpus and helps providing appropriate solutions for that
particular problem. The Data Corpus has been developed under the guidance of Psychiatrists to help users with MHPs. The
user must pass a preliminary test before getting access to the Chat bot
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