Depression Detection using AI With Chatbot Support

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 14 | 01 | Page :
    By

    S. A. Patil,

  • Anushka Sanjay Gaikwad,

  • Komal Ashok Gaikwad,

  • Sampada Nitin Aher,

  • Sakshi Babasaheb Mogal,

  1. Lecturer, Department of Computer Technolsogy, Sanjivani K.B.P Polytechnic, Kopargaon, Maharashtra, India
  2. Research Scholar, Department of Computer Technolsogy, Sanjivani K.B.P Polytechnic, Kopargaon, Maharashtra, India
  3. Research Scholar, Department of Computer Technolsogy, Sanjivani K.B.P Polytechnic, Kopargaon, Maharashtra, India
  4. Research Scholar, Department of Computer Technolsogy, Sanjivani K.B.P Polytechnic, Kopargaon, Maharashtra, India
  5. Research Scholar, Department of Computer Technolsogy, Sanjivani K.B.P Polytechnic, Kopargaon, Maharashtra, India

Abstract

Depression is a big worry around the globe, and its pushing up the number of suicides. Indias got some real high numbers of people taking their own lives so spotting the mental pressure and sadness is key for helping out quick. Wee got this piece of research showing off an AI system that can pick up on depression. It uses some smart deep learning and NLP plus a chatting bot to help out. This system also looks at how your face moves with CNNs, and it figures out your mood from the words you use with some machine learning moves like Naïve Bayes and SVM. The system snaps shots of your face in the now with a camera then these snapshots get worked over by CNN algorithms ending up sorted as happy or sad vibes. At the same time, it digs into what you say checking out the way you word things to figure out your sentiment, stress levels, and depressive tendencies. Mixing in some SMOTE (Synthetic Minority Over-sampling Technique), it evens out the data we got, and thats a plus for spotting the blues with more oomph. And hey, its got a chatbot interface that chitchats with you tossing out a helping hand and some tips that make sense with what it sees in your headspace readings. They put the model through its paces with stuff like DAIC-WOZ and PHQ-8, and it showed its smart at figuring out if someones feeling blue. Tossing together how someone’s mug looks when theyre emotional and the vibe of the words they use turns out to be a combo for nailing the diagnosis.

Keywords: Mental Stress Detection, Speech Processing, CNN, NLP, Chatbot, Deep Learning, Machine Learning, Depression Prediction

How to cite this article:
S. A. Patil, Anushka Sanjay Gaikwad, Komal Ashok Gaikwad, Sampada Nitin Aher, Sakshi Babasaheb Mogal. Depression Detection using AI With Chatbot Support. Research & Reviews: A Journal of Embedded System & Applications. 2025; 14(01):-.
How to cite this URL:
S. A. Patil, Anushka Sanjay Gaikwad, Komal Ashok Gaikwad, Sampada Nitin Aher, Sakshi Babasaheb Mogal. Depression Detection using AI With Chatbot Support. Research & Reviews: A Journal of Embedded System & Applications. 2025; 14(01):-. Available from: https://journals.stmjournals.com/rrjoesa/article=2025/view=242057


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Ahead of Print Subscription Review Article
Volume 14
01
Received 01/04/2025
Accepted 07/10/2025
Published 20/12/2025
Publication Time 263 Days
30

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