RETRACTED ARTICLE: Emotion recognition model based on facial
            expressions

Yadav, Satya Prakash

doi:10.1007/s11042-021-10962-5

Cited by 37 publications

(14 citation statements)

References 17 publications

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“…Among the various behavioral manifestations resulting from an emotion, facial expressions can be considered of great relevance for the external signaling of what the individual is feeling [1], demonstrating his emotions and interacting socially, besides presenting an adaptive value for the organism that performs them [2] [3] [4].…”

Section: Introductionmentioning

confidence: 99%

TREFACE: A New Computerized Test of Emotional Stroop with Facial Expressions

Prada¹,

Satler²,

Tavares³

et al. 2022

JBBS

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Using the conflict principle of the Stroop task, "effect of interference in color naming", the present study proposes to create a computational version of the emotional Stroop task, called TREFACE, for its acronyms in Portuguese "Teste de Reconhecimento de Expressões Faciais com Conflito Emocional" (Facial Expression Recognition Test with Emotional Conflict). In this protocol, four fixed styles of presentation were generated according to the condition: Congruent Word Reading, Incongruent Word Reading, Congruent Recognition of Face Expression and Incongruent Recognition of Face Expression, counterbalanced in terms of each facial expression, word and gender of the photo character. Forty-two healthy volunteers completed the task. Results revealed that a task associated with word reading allows better performance than a task associated with face recognition. It was also identified that in the congruent condition, there is an advantage in terms of the correct responses. Additionally, the data regarding recognition of face expression showed greater difficulty when the image was not congruent with the word. In general, the results suggest that the emotional attribute can compromise the ability to recognize the faces, reaching the functioning of mechanisms such as cognitive control and regulation of emotions. Thus, the TREFACE paradigm can be considered a good assessment tool for monitoring emotional conflict, in addition to presenting itself as a new instrument in Portuguese language for assessing emotional working memory in healthy individuals and, eventually, in different pathologies that affect the functioning of cortical areas related to executive functions.

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Section: Introductionmentioning

confidence: 99%

TREFACE: A New Computerized Test of Emotional Stroop with Facial Expressions

Prada¹,

Satler²,

Tavares³

et al. 2022

JBBS

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show abstract

“…Through the research in this paper, the data is mined to analyze the physical health of students, to help school health administrators make reasonable health management arrangements, to make effective health management arrangements for student health, and to effectively improve the physical health level of students. The data mining technology is used to record and analyze the changes in students' physical health after health management and to identify the changes in students' emotions, improve the effective guidance of students' emotions, and promote the positive impact of students' physical health on students' emotions [ 2 ]. In addition, it can also provide a reasonable planning program for people's daily life and diet and improve people's quality of life and physical fitness and mental health.…”

Section: Introductionmentioning

confidence: 99%

Data Mining and Analysis of Management Theory on the Emotional Recognition of Students’ Physical Fitness Improvement

Fan

Liu³

2022

Applied Bionics and Biomechanics

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The improvement of the economic level has brought earth-shaking changes to people’s living standards. However, with the improvement of living standards, the pace of life is also accelerating, people’s physical and psychological pressure has also increased sharply, and people’s physical and mental health problems are also increasing. As an important threshold for talent training schools, real-time monitoring of students’ physiques, and effective training of students’ physical fitness, so schools need to strengthen the scientific management of students’ work and rest and exercise according to management theory. To better pay attention to the correlation between students’ physical fitness and psychological emotions, this paper designs a data analysis system for students’ physical health based on data mining, analyzes the improvement of students’ physical fitness under health management, and then identifies students’ emotions according to this to observe the impact of students’ physical fitness improvement on emotional changes, so as to effectively improve students’ physical health level and mental health level. The experimental results of the research system in this paper show that the improvement of students’ physical fitness can promote students’ emotional recognition, and its accuracy can be improved by at least 2%, and various types of emotions can be accurately identified, indicating that changes in students’ physical fitness have a certain impact on student emotions.

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“…The human brain has a compelling information processing capability, which can perceive and understand the part of the information in a speech where the audio reflects the speaker's emotion; therefore, they can sense the change in the speaker's sentiment in address. As the most direct and effective way for people to communicate and transmit information daily, speech contains textual and acoustic data [ 3 ]. Auditory information refers to the characteristics the human ear can perceive, such as timbre, tone quality, volume, and rhythm of people's speech.…”

Section: Introductionmentioning

confidence: 99%

A Classroom Emotion Recognition Model Based on a Convolutional Neural Network Speech Emotion Algorithm

Yuan

2022

Occupational Therapy International

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In this paper, we construct a model of convolutional neural network speech emotion algorithm, analyze the classroom identified by the neural network with a certain degree of confidence together with the school used in the dataset, find the characteristics and rules of teachers’ control of classroom emotion nowadays using big data, find the parts of classroom emotion, and design a classroom emotion recognition model based on convolutional neural network speech emotion algorithm according to these characteristics. This paper will investigate the factors and patterns of teachers’ emotional control in the classroom. In this paper, the existing neural network is adapted and improved, and some preprocessing is performed on the current dataset to train the network. The network used in this paper is a combination of convolutional neural network (CNN) and recurrent neural network (RNN), which takes advantage of both CNN for feature extraction and RNN for memory capability in the sequence model. This network has a good effect on both object labeling and speech recognition. For the problem of extracting emotion features of whole-sentence speech, we propose an attention mechanism-based emotion recognition algorithm for variable-length speech and design a spatiotemporal attention module for the speech emotion algorithm and a convolutional channel attention module for the CNN network to reduce the contribution of the spatiotemporal data of the speech emotion algorithm and the unimportant parts of the CNN convolutional channel feature data in the subsequent recognition by the attention mechanism. In turn, the weight of core key data and features is increased to improve the model recognition accuracy.

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RETRACTED ARTICLE: Emotion recognition model based on facial expressions

Cited by 37 publications

References 17 publications

TREFACE: A New Computerized Test of Emotional Stroop with Facial Expressions

TREFACE: A New Computerized Test of Emotional Stroop with Facial Expressions

Data Mining and Analysis of Management Theory on the Emotional Recognition of Students’ Physical Fitness Improvement

A Classroom Emotion Recognition Model Based on a Convolutional Neural Network Speech Emotion Algorithm

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