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  Published Paper Details:

  Paper Title

Survey on Automatic Depression Level Detection

  Authors

  Shilpa S B,  Dr. Shashikumar D R

  Keywords

  Abstract


The depression is a medical condition and it is among the major mental diseases that affects numerous people worldwide. For this work, the Distress Analysis Interview Corpus-Wizard of Oz interviews (DAJC-WOZ) dataset will be utilized which contains 189 sessions in zip file format and responses from 59 depressed and BO non-depressed patients[1]. This dataset has video, audio and text clips so individual preprocessing techniques are utilized which is given as a source for depression detection level. The inputs are in the form of video, audio and text, so individual preprocessing methods for feature extraction are used with separate techniques. Then, the extracted features from separate techniques are concatenated and given as input for the classification of depression level. The Long-Short Term Memory (LSTM) can be utilized in this research for classifying the depression levels

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2403064

  Paper ID - 251740

  Page Number(s) - a534-a538

  Pubished in - Volume 12 | Issue 3 | March 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Shilpa S B,  Dr. Shashikumar D R,   "Survey on Automatic Depression Level Detection", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 3, pp.a534-a538, March 2024, Available at :http://www.ijcrt.org/papers/IJCRT2403064.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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