A Working Memory Model for Task-oriented Dialog Response Generation | |
Chen, Xiuyi2,3,4; Xu, Jiaming3,4; Xu, Bo1,2,3,4 | |
2019-07 | |
会议日期 | 2019-07 |
会议地点 | Florence, Italy |
英文摘要 | Recently, to incorporate external Knowledge Base (KB) information, one form of world knowledge, several end-to-end task-oriented dialog systems have been proposed. These models, however, tend to confound the dialog history with KB tuples and simply store them into one memory. Inspired by the psychological studies on working memory, we propose a working memory model (WMM2Seq) for dialog response generation. Our WMM2Seq adopts a working memory to interact with two separated long-term memories, which are the episodic memory for memorizing dialog history and the semantic memory for storing KB tuples. The working memory consists of a central executive to attend to the aforementioned memories, and a short-term storage system to store the “activated” contents from the long-term memories. Furthermore, we introduce a context-sensitive perceptual process for the token representations of dialog history, and then feed them into the episodic memory. Extensive experiments on two task-oriented dialog datasets demonstrate that our WMM2Seq significantly outperforms the state-of-the-art results in several evaluation metrics. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/48917] |
专题 | 数字内容技术与服务研究中心_听觉模型与认知计算 |
通讯作者 | Xu, Jiaming |
作者单位 | 1.Center for Excellence in Brain Science and Intelligence Technology, CAS. China 2.University of Chinese Academy of Sciences 3.Research Center for Brain-inspired Intelligence, CASIA 4.Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China |
推荐引用方式 GB/T 7714 | Chen, Xiuyi,Xu, Jiaming,Xu, Bo. A Working Memory Model for Task-oriented Dialog Response Generation[C]. 见:. Florence, Italy. 2019-07. |
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