共 21 条
POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN DIALOGUE SYSTEMS
被引:0
作者:
Gasic, M.
[1
]
Mrksic, N.
[1
]
Su, P-H.
[1
]
Vandyke, D.
[1
]
Wen, T-H.
[1
]
Young, S.
[1
]
机构:
[1] Univ Cambridge, Dept Engn, Trumpington St, Cambridge CB2 1PZ, England
来源:
2015 IEEE WORKSHOP ON AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING (ASRU)
|
2015年
基金:
英国工程与自然科学研究理事会;
关键词:
Bayesian committee machines;
Gaussian processes;
reinforcement learning;
D O I:
暂无
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
Moving from limited-domain dialogue systems to open domain dialogue systems raises a number of challenges. One of them is the ability of the system to utilise small amounts of data from disparate domains to build a dialogue manager policy. Previous work has focused on using data from different domains to adapt a generic policy to a specific domain. Inspired by Bayesian committee machines, this paper proposes the use of a committee of dialogue policies. The results show that such a model is particularly beneficial for adaptation in multi-domain dialogue systems. The use of this model significantly improves performance compared to a single policy baseline, as confirmed by the performed real-user trial. This is the first time a dialogue policy has been trained on multiple domains on-line in interaction with real users.
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页码:806 / 812
页数:7
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