ITM Web Conf.
Volume 44, 2022International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
|Number of page(s)||9|
|Published online||05 May 2022|
Regional language Speech Emotion Detection using Deep Neural Network
1 Ramrao Adik college of Engineering, Electronics & Telecommunication Department, Nerul, Navi Mumbai, India
2 Ramrao Adik college of Engineering, Electronics Department, Nerul, Navi Mumbai, India
* Corresponding author: email@example.com
Speaking is the most basic and efficient mode of human contact. Emotions assist people in communicating and understanding others’ viewpoints by transmitting sentiments and providing feedback.The basic objective of speech emotion recognition is to enable computers to comprehend human emotional states such as happiness, fury, and disdain through voice cues. Extensive Effective Method Coefficients of Mel cepstral frequency have been proposed for this problem. The characteristics of Mel frequency ceptral coefficients(MFCC) and the audio based textual characteristics are extracted from the audio characteristics and the hybrid textural framework characteristics of the video are extracted. Voice emotion recognition is used in a variety of applications such as voice monitoring, online learning, clinical investigations, deception detection, entertainment, computer games, and call centres.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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