An effective approach for emotion detection in multimedia text data using sequence based convolutional neural network

doi:10.1007/s11042-019-07813-9

CASIA OpenIR > 离退休人员

	An effective approach for emotion detection in multimedia text data using sequence based convolutional neural network
	Shrivastava, Kush 1; Kumar, Shishir 1; Jain, Deepak Kumar2
发表期刊	MULTIMEDIA TOOLS AND APPLICATIONS
ISSN	1380-7501
	2019-10-01
卷号	78 期号:20 页码:29607-29639
通讯作者	Kumar, Shishir(shishir.kumar@juet.ac.in)
摘要	In the recent trends, the world has stepped into a multimedia era for enhancing business, recommendation systems, and information retrieval, etc. Multimedia data is highly rich in contents which express different human emotions. Several issues for emotion detection from multimedia images & videos have been addressed in this domain, but a very less effort has been applied for text data. The evaluation of deep learning has outperformed traditional techniques in sentiment analysis tasks. Inspired by the work done in the field of sentiment analysis, a deep learning based framework has been implemented on multimedia text data for the task of fine-grained emotion detection. The presented work introduces a new corpus which expresses different forms of emotions collected from a TV show's transcript. A manual annotation of the corpus has been conducted with the help of English expert annotators. As an emotion detection framework, this paper proposes a sequence-based convolutional neural network(CNN) with word embedding to detect the emotions. An attention mechanism is applied in the proposed model which allows CNN to focus on the words that have more effect on the classification or the part of the features that should be attended more. The main aim of the work is to develop a framework such a way to generalize to newly collected data and help business to understand the customer's mind and social media monitoring as it allows us to gain an overview of the wider public opinion behind certain topics. Experiments conducted on the dataset shows that the proposed framework correctly detects the emotions from the text with good precision and accuracy score.
关键词	Multimedia data Emotion detection Deep learning Convolutional neural network Deep neural network
DOI	10.1007/s11042-019-07813-9
关键词[WOS]	AGREEMENT ; RECOGNITION ; EXPRESSION ; SPEECH
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000485997700065
出版者	SPRINGER
引用统计	被引频次：37[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/26984
专题	离退休人员
通讯作者	Kumar, Shishir
作者单位	1.Jaypee Univ Engn & Technol, Dept Comp Sci & Engn, Guna, MP, India 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Shrivastava, Kush,Kumar, Shishir,Jain, Deepak Kumar. An effective approach for emotion detection in multimedia text data using sequence based convolutional neural network[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2019,78(20):29607-29639.
APA	Shrivastava, Kush,Kumar, Shishir,&Jain, Deepak Kumar.(2019).An effective approach for emotion detection in multimedia text data using sequence based convolutional neural network.MULTIMEDIA TOOLS AND APPLICATIONS,78(20),29607-29639.
MLA	Shrivastava, Kush,et al."An effective approach for emotion detection in multimedia text data using sequence based convolutional neural network".MULTIMEDIA TOOLS AND APPLICATIONS 78.20(2019):29607-29639.