Depression and Stress Detection Using Speech Emotion Recognition

Keep in mind that depression is becoming an increasingly serious problem around the world. Our goal is to assist people in dealing with anxiety and despair. Speech analysis is used in our study to detect user depression. The Mel-Frequency Cepstral Coefficients (MFCCs) are utilized as a classificatio

2025-06-28 16:26:06 - Adil Khan

Project Title

Depression and Stress Detection Using Speech Emotion Recognition

Project Area of Specialization Computer ScienceProject Summary

Keep in mind that depression is becoming an increasingly serious problem around the world. Our goal is to assist people in dealing with anxiety and despair. Speech analysis is used in our study to detect user depression. The Mel-Frequency Cepstral Coefficients (MFCCs) are utilized as a classification feature in machine learning to diagnose depression. It will be a mobile application via which we will be able to detect depression through voice.

Project Objectives Project Implementation Method

'Depression and Stress Detection Using Speech Emotion Recognition ' _1659399215.png

Hardware requirement: -

Software requirements

IDE

Text Editor

API Testing

Version Control

Web testing

Mobile app testing

Programming Languages used:-

Application development Frameworks

Database

Benefits of the Project

We provide handy access to discover Depression in someone you care about, such as a close relative, and to make an early decision on how to help them overcome their problems.

Technical Details of Final Deliverable

Through voice, a mobile application may identify depression and stress.

Final Deliverable of the Project Software SystemCore Industry MedicalOther Industries IT , Health Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources
Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
Total in (Rs) 80000
Graphic Card Equipment17000070000
Google Developer Account Miscellaneous 165006500
Apple Developer Account Miscellaneous 135003500

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