An adaptive approach for Human Emotions Recognition System for Neural Networks using Hidden Markov Model and Self Organizing Maps algorithms

K. M. Azaraffali, Dr. T. Krishnakumar, Dr.M. Sriram
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引用次数: 0

Abstract

. In machine learning, recognition of human emotions by a machine is an important research area. It is informal to reason of emotions as a luxury, approximately that is needless for basic intelligent operative, and something that is problematic to encode in a computer program. Then giving expressivecapabilities to machine has been a least priority up till now. But recent studies suggest that emotions play surprisingly dangerous role in balanced and brainybehavior. Too slightfeeling can damagebalancedthoughtful and behaviour. The main impartial of this paper is the identification of emotional states of human beings.Inthis researchthe algorithms to be used are Hidden Markov Model and Self Organizing Maps..
基于隐马尔可夫模型和自组织映射算法的神经网络人类情绪识别系统的自适应方法
. 在机器学习中,机器对人类情感的识别是一个重要的研究领域。将情感作为一种奢侈品进行推理是不正式的,这对于基本的智能操作来说是不必要的,并且在计算机程序中编码是有问题的。到目前为止,赋予机器表达能力一直是最不重要的。但最近的研究表明,情绪在平衡和聪明的行为中起着惊人的危险作用。太轻微的感觉会破坏平衡的思想和行为。本文的主要偏颇点在于对人类情绪状态的识别。在本研究中使用的算法是隐马尔可夫模型和自组织映射。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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