Incorporating Interlocutor-Aware Context into Response Generation on Multi-Party Chatbots | |
Liu, Cao1,3; Liu, Kang1,3; He, Shizhu1,3; Nie, Zaiqing2; Zhao, Jun1,3 | |
2019-11 | |
会议日期 | November 3-4, 2019 |
会议地点 | Hong Kong, China |
英文摘要 | Conventional chatbots focus on two-party response generation, which simplifies the real dialogue scene. In this paper, we strive toward a novel task of Response Generation on Multi-Party Chatbot (RGMPC), where the generated responses heavily rely on the interlocutors’ roles (e.g., speaker and addressee) and their utterances. Unfortunately, complex interactions among the interlocutors’ roles make it challenging to precisely capture conversational contexts and interlocutors’ information. Facing this challenge, we present a response generation model which incorporates Interlocutor-aware Contexts into Recurrent Encoder-Decoder frameworks (ICRED) for RGMPC. Specifically, we employ interactive representations to capture dialogue contexts for different interlocutors. Moreover, we leverage an addressee memory to enhance contextual interlocutor information for the target addressee. Finally, we construct a corpus for RGMPC based on an existing open-access dataset. Automatic and manual evaluations demonstrate that the ICRED remarkably outperforms strong baselines. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/39187] |
专题 | 模式识别国家重点实验室_自然语言处理 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.Alibaba AI Labs 3.University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Liu, Cao,Liu, Kang,He, Shizhu,et al. Incorporating Interlocutor-Aware Context into Response Generation on Multi-Party Chatbots[C]. 见:. Hong Kong, China. November 3-4, 2019. |
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