检索结果-南通市图书馆

Conditional selection with CNN augmented transformer for multimodal affective analysis

第二届和谐人机环境联合学术会议(HHME2006)——第2届中国人机交互学术会议(CHCI'06)

作者： Luo Qi1,2, Wu yanwen1, Wan Liyong 1, Tang Shuangyan1 11. Department of Information & Technology, Central China Normal University Wuhan, 430074, P.R.China 2 Department of Information Engineering ,Wuhan University of Science and Technology Zhongnan Branch Wuhan, 430000, P.R.China

Aiming at emotion deficiency in present E-Learning system, a lot of negative effects were analyzed and corresponding countermeasures were proposed. Basing on it, we combined affective computing with t

关键词： affective computing E-learning artificial psychology harmonious man-machine environment.

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

CAAI Transactions on Intelligence Technology 2024年第4期9卷 917-931页

作者： Jianwen Wang Shiping Wang Shunxin Xiao Renjie Lin Mianxiong Dong Wenzhong Guo College of Computer and Data Science Fuzhou UniversityFuzhouChina College of Computer and Cyber Security Fujian Normal UniversityFuzhouChina Key Laboratory of Network computing and Intelligent Information Processing Fuzhou UniversityFuzhouChina Digital Fujian Institute of Big Data Security Technology Fujian Normal UniversityFuzhouChina Department of Sciences and Informatics Muroran Institute of TechnologyMuroranJapan

Attention mechanism has been a successful method for multimodal affective analysis in recent years. Despite the advances, several significant challenges remain in fusing language and its nonverbal context information. One is to generate sparse attention coefficients associated with acoustic and visual modalities, which helps locate critical emotional se-mantics. The other is fusing complementary cross‐modal representation to construct optimal salient feature combinations of multiple modalities. A Conditional Transformer Fusion Network is proposed to handle these problems. Firstly, the authors equip the transformer module with CNN layers to enhance the detection of subtle signal patterns in nonverbal sequences. Secondly, sentiment words are utilised as context conditions to guide the computation of cross‐modal attention. As a result, the located nonverbal fea-tures are not only salient but also complementary to sentiment words directly. Experi-mental results show that the authors’ method achieves state‐of‐the‐art performance on several multimodal affective analysis datasets.

关键词： affective computing data fusion information fusion multimodal approaches

Remote heart rate measurement using low-cost RGB face video： a technical literature review

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Computer Science 2018年第5期12卷 858-872页

作者： Philipp V. ROUAST Marc T. P. ADAM Raymond CHIONG David CORNFORTH Ewa LUX Institute of Information Systems and Marketing Karlsruhe Institute of Technology Karlsruhe 76133 Germany School of Electrical Engineering and computing The University of Newcastle Callaghan NSW 2308 Australia

Remote photoplethysmography （rPPG） allows remote measurement of the heart rate using low-cost RGB imaging equipment. In this study, we review the development of the field of rPPG since its emergence in 2008. We also classify existing rPPG approaches and derive a framework that provides an overview of modular steps. Based on this framework, practitioners can use our classification to design algorithms for an rPPG approach that suits their specific needs. Researchers can use the reviewed and classified algorithms as a starting point to improve particular features of an rPPG algorithm.

关键词： affective computing heart rate measurement remote non-contact camera-based photoplethysmography

Game Outlier Behavior Detection System Based on Dynamic Time Warp Algorithm

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2022年第4期131卷 219-237页

作者： Shinjin Kang Soo Kyun Kim School of Games Hongik UniversitySejong30016Korea Department of Computer Engineering Jeju National UniversityJeju63243Korea

This paper proposes a methodology for using multi-modal data in gameplay to detect outlier *** proposedmethodology collects,synchronizes,and quantifies time-series data fromwebcams,mouses,and *** expressions are varied on a one-dimensional pleasure axis,and changes in expression in the mouth and eye areas are detected ***,the keyboard and mouse input frequencies are tracked to determine the interaction intensity of ***,we apply a dynamic time warp algorithm to detect outlier *** detected outlier behavior graph patterns were the play patterns that the game designer did not intend or play patterns that differed greatly from those of other *** outlier patterns can provide game designers with feedback on the actual play experiences of users of the *** results can be applied to the game industry as game user experience analysis,enabling a quantitative evaluation of the excitement of a game.

关键词： Facial expression recognition webcam behavior analysis affective computing

1D-CNN:Speech Emotion Recognition System Using a Stacked Network with Dilated CNN Features

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第6期67卷 4039-4059页

作者： Mustaqeem Soonil Kwon Interaction Technology Laboratory Department of SoftwareSejong UniversitySeoul05006Korea

Emotion recognition from speech data is an active and emerging area of research that plays an important role in numerous applications,such as robotics,virtual reality,behavior assessments,and emergency call ***,researchers have developed many techniques in this field in order to ensure an improvement in the accuracy by utilizing several deep learning approaches,but the recognition rate is still not *** main aim is to develop a new technique that increases the recognition rate with reasonable cost *** this paper,we suggested a new technique,which is a one-dimensional dilated convolutional neural network(1D-DCNN)for speech emotion recognition(SER)that utilizes the hierarchical features learning blocks(HFLBs)with a bi-directional gated recurrent unit(BiGRU).We designed a one-dimensional CNN network to enhance the speech signals,which uses a spectral analysis,and to extract the hidden patterns from the speech signals that are fed into a stacked one-dimensional dilated network that are called *** HFLB contains one dilated convolution layer(DCL),one batch normalization(BN),and one leaky_relu(Relu)layer in order to extract the emotional features using a hieratical correlation ***,the learned emotional features are feed into a BiGRU in order to adjust the global weights and to recognize the temporal *** final state of the deep BiGRU is passed from a softmax classifier in order to produce the probabilities of the *** proposed model was evaluated over three benchmarked datasets that included the IEMOCAP,EMO-DB,and RAVDESS,which achieved 72.75%,91.14%,and 78.01%accuracy,respectively.

关键词： affective computing one-dimensional dilated convolutional neural network emotion recognition gated recurrent unit raw audio clips

affective Preferences Mining Approach with Applications in Process Control

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Shanghai Jiaotong university(Science) 2022年第5期27卷 737-746页

作者： SU Chong LÜJing ZHANG Danyang LI Hongguang College of Information Science and Technology Beijing University of Chemical TechnologyBeijing100029China

Traditional industrial process control activities relevant to multi-objective optimization problems,such as proportional integral derivative(PID)parameter tuning and operational optimizations,always demand for process knowledge and human operators’experiences during human-computer ***,the impact of human operators’preferences on human-computer interactions has been rarely highlighted ever *** response to this problem,a novel multilayer cognitive affective computing model based on human personalities and pleasure-arousal-dominance(PAD)emotional space states is established in this ***,affective preferences are employed to update the affective computing model during human-machine ***,we propose affective parameters mining strategies based on genetic algorithms(GAs),which are responsible for gradually grasping human operators’operational preferences in the process control *** routine process control tasks,including PID controller tuning for coupling loops and operational optimization for batch beer fermenter processes,are carried out to illustrate the effectiveness of the contributions,leading to the satisfactory results.

关键词： affective computing preferences mining process control

TC-Net:A Modest&Lightweight Emotion Recognition System Using Temporal Convolution Network

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第9期46卷 3355-3369页

作者： Muhammad Ishaq Mustaqeem Khan Soonil Kwon Sejong University Software Convergence Department Seoul05006Korea Mohamed Bin Zayed University of Artificial Intelligence(MBZUAI) Abu Dhabi3838-111188United Arab Emirates

Speech signals play an essential role in communication and provide an efficient way to exchange information between humans and *** Emotion Recognition(SER)is one of the critical sources for human evaluation,which is applicable in many real-world applications such as healthcare,call centers,robotics,safety,and virtual *** work developed a novel TCN-based emotion recognition system using speech signals through a spatial-temporal convolution network to recognize the speaker’s emotional *** authors designed a Temporal Convolutional Network(TCN)core block to recognize long-term dependencies in speech signals and then feed these temporal cues to a dense network to fuse the spatial features and recognize global information for final *** proposed network extracts valid sequential cues automatically from speech signals,which performed better than state-of-the-art(SOTA)and traditional machine learning *** of the proposed method show a high recognition rate compared with *** final unweighted accuracy of 80.84%,and 92.31%,for interactive emotional dyadic motion captures(IEMOCAP)and berlin emotional dataset(EMO-DB),indicate the robustness and efficiency of the designed model.

关键词： affective computing deep learning emotion recognition speech signal temporal convolutional network

Construction and cross-correlation analysis of the affective physiological response database

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2010年第9期53卷 1774-1784页

作者： WEN WanHui1,QIU YuHui2,LIU GuangYuan1*,CHENG NanPu3 & HUANG XiTing4 1School of Electronic and Information Engineering,Southwest University,Chongqing 400715,China 2College of Computer and Information Science,Southwest University,Chongqing 400715,China 3School of Materials Science and Engineering,Southwest University,Chongqing 400715,China 4School of Psychology,Southwest University,Chongqing 400715,China 1. School of Electronic and Information Engineering Southwest University Chongqing 400715 China2. College of Computer and Information Science Southwest University Chongqing 400715 China3. School of Materials Science and Engineering Southwest University Chongqing 400715 China4. School of Psychology Southwest University Chongqing 400715 China

Six kinds of emotions,namely joy,surprise,disgust,grief,anger and fear,are elicited from 300 ordinary college students by means of high-rated movie *** signals of galvanic skin response(GSR),heart rate(HR),blood volume pulse(BVP),electrocardiogram(ECG),respiration(Rsp.),facial electromyography(EMG) and two channels of electroencephalography(EEG) from the frontal lobe were recorded while the subjects were watching the affective eliciting *** samples of each kind of signals are analyzed by using random matrix theory(RMT).From the distribution of the eigenvalues and eigenvectors of the correlation matrices of BVP,facial EMG and two EEGs,we find that the statistical properties of these four kinds of signals coincide with the RMT ***,the largest eigenvalue and the corresponding eigenvector component distribution of the correlation matrices of GSR,HR,ECG and *** deviated significantly from the RMT *** experiments also reveal that the correlations between two arbitrary samples of BVP,facial EMG or EEGs does not result from affective response but from random noises,whereas the amplitude variations of GSR,HR,ECG and *** the correlated affective physiological response *** to the data analysis results of RMT,110 features are firstly extracted from the GSR and HR signals,and then a subset of the initial features is selected by using the Backward Selection *** affective data samples each of which is a vector of the features are classified by using a Fisher classifier,and furthermore,the user-independent emotion recognition systems with good prediction performance are constructed during the model selection process.

关键词： affective computing emotion recognition affective physiological response database correlation analysis random matrix theory

Attention emotion recognition via ECG signals

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Quantitative Biology 2022年第3期10卷 276-286页

作者： Aihua Mao Zihui Du Dayu Lu Jie Luo School of Computer Science&Engineering South China University of TechnologyGuangzhou 510006China School of Medicine South China University of TechnologyGuangzhou 510006China School of Fine Art and Artistic Design Guangzhou UniversityGuangzhou 510006China

Background:Physiological signal-based research has been a hot topic in affective *** works mainly focus on some strong,short-lived emotions(e.g.,joy,anger),while the attention,which is a weak and long-lasting emotion,receives less *** this paper,we present a study of attention recognition based on electrocardiogram(ECG)signals,which contain a wealth of information related to ***:The ECG dataset is derived from 10 subjects and specialized for attention *** relieve the impact of noise of baseline wondering and power-line interference,we apply wavelet threshold denoising as preprocessing and extract rich features by pan-tompkins and wavelet decomposition *** improve the generalized ability,we tested the performance of a variety of combinations of different feature selection algorithms and ***:Experiments show that the combination of generic algorithm and random forest achieve the highest correct classification rate(CCR)of 86.3%.Conclusion:This study indicates the feasibility and bright future of ECG-based attention research.

关键词： affective computing attention recognition ECG signals