An effective approach for emotion detection in multimedia text data using sequence based convolutional neural network
文献类型：期刊论文
| 作者 | Shrivastava, Kush1; Kumar, Shishir1; Jain, Deepak Kumar2
|
| 刊名 | MULTIMEDIA TOOLS AND APPLICATIONS
 |
| 出版日期 | 2019-10-01 |
| 卷号 | 78期号:20页码:29607-29639 |
| ISSN号 | 1380-7501 |
| 关键词 | Multimedia data Emotion detection Deep learning Convolutional neural network Deep neural network |
| DOI | 10.1007/s11042-019-07813-9 |
| 通讯作者 | Kumar, Shishir(shishir.kumar@juet.ac.in) |
| 英文摘要 | 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. |
| WOS关键词 | AGREEMENT ; RECOGNITION ; EXPRESSION ; SPEECH |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| 出版者 | SPRINGER |
| WOS记录号 | WOS:000485997700065 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/26983]  |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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