EMOTION DETECTION BASED ON SPEECH AND FACE: A REVIEW

Khushali K. Trivedi , Prof. Amee Chhaya

Speech recognition, Face recognition, Emotion detection, Speech Processing, Image Processing

Clinical depression has been a common but a serious mood disorder nowadays affecting people of any age group. Since depression affects the mental state, the patient will find it difficult to communicate his/her condition to the doctor. Commonly used diagnostic measures are interview style assessment or questionnaires about the symptoms, laboratory tests to check whether the depression symptoms are related with other serious illness. With the emergence of machine learning many techniques have been developed for supporting the diagnosis of depression in the past few years. Since depression is a multifactor disorder, the diagnosis of depression should follow a multimodal approach for its effective assessment. This paper presents a review of various unimodal and multimodal approaches that have been developed with the aim of analyzing the depression using emotion recognition. The unimodal approach considers either of the attributes among facial expressions, speech, etc. for depression detection while multimodal approaches are based on the combination of one or more attributes. The survey covers the existing emotion detection research efforts that use audio and visual data for depression detection. The survey shows that the depression detection using multimodal approach and deep learning techniques achieve greater performance over unimodal approaches in the depression analysis.

Published Paper   E-Certificate

"EMOTION DETECTION BASED ON SPEECH AND FACE: A REVIEW", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.e708-e715, March-2023, Available :https://ijnrd.org/papers/IJNRD2303493.pdf

Volume 8 Issue 3, March-2023

Pages : e708-e715

Paper Reg. ID: IJNRD_200858

Published Paper Id: IJNRD2303493

Downloads: 000118851

Research Area: Engineering

Country: -, -, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303493

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303493

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

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition