Speech Emotion Recognition Using Machine Learning

Aman Kumar, Vishrut Kumar, P. Rajakumar
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Abstract

In the field of human-computer interaction, identifying the emotions conveyed in a person's speech is a challenge that is both incredibly fascinating and challenging. Recent times have seen a significant uptick in people's interest in this topic. In the subject of speech emotion recognition, a wide variety of techniques have been applied in order to extract emotions from signals. These techniques include a number of well-known speech analysis and classification strategies. This paper provides an overview of the deep learning technique, which is based on a simple algorithm based on feature extraction and model creation that recognizes emotion. In the traditional method of speech emotion recognition, features are first extracted from the speech signals, then the features themselves are picked, collectively known as the selection module, and then the emotions are recognized.
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使用机器学习的语音情感识别
在人机交互领域,识别一个人讲话中所传达的情感是一项既令人难以置信又具有挑战性的挑战。近年来,人们对这个话题的兴趣显著上升。在语音情感识别领域,为了从信号中提取情感,已经应用了各种各样的技术。这些技术包括许多著名的语音分析和分类策略。本文概述了深度学习技术,该技术基于基于特征提取和模型创建的简单算法来识别情绪。在传统的语音情绪识别方法中,首先从语音信号中提取特征,然后对特征本身进行挑选,统称为选择模块,然后对情绪进行识别。
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