Conversational Emotion Analysis via Attention Mechanisms
文献类型:会议论文
作者 | Zheng Lian1,2; Jianhua Tao1,2,3; Bin Liu1; Jian Huang1,2 |
出版日期 | 2019 |
会议日期 | 15-19 September, 2019 |
会议地点 | Graz, Austria |
英文摘要 | Different from the emotion recognition in individual utterances, we propose a multimodal learning framework using relation and dependencies among the utterances for conversational emotion analysis. The attention mechanism is applied to the fusion of the acoustic and lexical features. Then these fusion representations are fed into the self-attention based bi-directional gated recurrent unit (GRU) layer to capture long-term contextual information. To imitate real interaction patterns of different speakers, speaker embeddings are also utilized as additional inputs to distinguish the speaker identities during conversational dialogs. To verify the effectiveness of the proposed method, we conduct experiments on the IEMOCAP database. Experimental results demonstrate that our method shows absolute 2.42% performance improvement over the state-of-the-art strategies. |
语种 | 英语 |
源URL | [http://ir.ia.ac.cn/handle/173211/44724] |
专题 | 模式识别国家重点实验室_智能交互 |
作者单位 | 1.National Laboratory of Pattern Recognition, CASIA, Beijing, China 2.CAS Center for Excellence in Brain Science and Intelligence Technology, Beijing, China 3.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China |
推荐引用方式 GB/T 7714 | Zheng Lian,Jianhua Tao,Bin Liu,et al. Conversational Emotion Analysis via Attention Mechanisms[C]. 见:. Graz, Austria. 15-19 September, 2019. |
入库方式: OAI收割
来源:自动化研究所
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。