Depression detection using Face, Text and Audio

Registration ID: IJNRD_197248

Published ID: IJNRD2305789

DOI: Click Here to Get

Gitanjali Tukaram Gadakh , Kavita Sawant , Pooja jagtap , Snehal Avhad , Pooja Shinde

Machine Learning, Face detection, Image preprocessing, segmentation, extraction, CNN, SVM, MFCC, Depression detection

Depression is a serious illness that affects millions of people globally. From child to senior citizens are facing depression. Major area is occupied by adults, college going students and teenagers also. In recent years, the task of automatic depression detection from speech has gained popularity. However, several challenges remain, including which features provide the best discrimination between classes or depression levels. We provide a comparative analyses of various features for depression detection. Using the same corpus, we evaluate how a system built on text-based, audio- based and speech-based system. We find that a combination of features drawn from both speech and text lead to the best system performance. By doing a survey we have find most efficient algorithms for detection purpose. We have used CNN (Convolutional Neural Network) for Face images training, for Face recognition we have used Harr Cascade Algorithm. To detect depression using Text ,we have used SVM(Support Vector Machine) Algorithm. Lastly for Audio input, we have used MFCC for speech recognition.

Published Paper   E-Certificate

Gitanjali Tukaram Gadakh, Kavita Sawant, Pooja jagtap, Snehal Avhad, & Pooja Shinde (May-2023). Depression detection using Face, Text and Audio. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), h672-h680. https://ijnrd.org/papers/IJNRD2305789.pdf

Volume 8 Issue 5, May-2023

Pages : h672-h680

Paper Reg. ID: IJNRD_197248

Published Paper Id: IJNRD2305789

Downloads: 000121978

Research Area: Computer Engineering 

Country: Pune, Maharastra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305789.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305789

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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