Dialog State Tracking(DST)aims to extract the current state from the conversation and plays an important role in dialog systems.Existing methods usually predict the value of each slot independently and do not consider...Dialog State Tracking(DST)aims to extract the current state from the conversation and plays an important role in dialog systems.Existing methods usually predict the value of each slot independently and do not consider the correlations among slots,which will exacerbate the data sparsity problem because of the increased number of candidate values.In this paper,we propose a multi-domain DST model that integrates slot-relevant information.In particular,certain connections may exist among slots in different domains,and their corresponding values can be obtained through explicit or implicit reasoning.Therefore,we use the graph adjacency matrix to determine the correlation between slots,so that the slots can incorporate more slot-value transformer information.Experimental results show that our approach has performed well on the Multi-domain Wizard-Of-Oz(MultiWOZ)2.0and MultiWOZ2.1 datasets,demonstrating the effectiveness and necessity of incorporating slot-relevant information.展开更多
Due to the significance and value in human-computer interaction and natural language processing,task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.In this p...Due to the significance and value in human-computer interaction and natural language processing,task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.In this paper,we survey recent advances and challenges in task-oriented dialog systems.We also discuss three critical topics for task-oriented dialog systems:(1)improving data efficiency to facilitate dialog modeling in low-resource settings,(2)modeling multi-turn dynamics for dialog policy learning to achieve better task-completion performance,and(3)integrating domain ontology knowledge into the dialog model.Besides,we review the recent progresses in dialog evaluation and some widely-used corpora.We believe that this survey,though incomplete,can shed a light on future research in task-oriented dialog systems.展开更多
基金supported by the National Natural Science Foundation of China(No.61976247)
文摘Dialog State Tracking(DST)aims to extract the current state from the conversation and plays an important role in dialog systems.Existing methods usually predict the value of each slot independently and do not consider the correlations among slots,which will exacerbate the data sparsity problem because of the increased number of candidate values.In this paper,we propose a multi-domain DST model that integrates slot-relevant information.In particular,certain connections may exist among slots in different domains,and their corresponding values can be obtained through explicit or implicit reasoning.Therefore,we use the graph adjacency matrix to determine the correlation between slots,so that the slots can incorporate more slot-value transformer information.Experimental results show that our approach has performed well on the Multi-domain Wizard-Of-Oz(MultiWOZ)2.0and MultiWOZ2.1 datasets,demonstrating the effectiveness and necessity of incorporating slot-relevant information.
基金the National Natural Science Foundation of China(Grant Nos.61936010 and 61876096)the National Key R&D Program of China(Grant No.2018YFC0830200)。
文摘Due to the significance and value in human-computer interaction and natural language processing,task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.In this paper,we survey recent advances and challenges in task-oriented dialog systems.We also discuss three critical topics for task-oriented dialog systems:(1)improving data efficiency to facilitate dialog modeling in low-resource settings,(2)modeling multi-turn dynamics for dialog policy learning to achieve better task-completion performance,and(3)integrating domain ontology knowledge into the dialog model.Besides,we review the recent progresses in dialog evaluation and some widely-used corpora.We believe that this survey,though incomplete,can shed a light on future research in task-oriented dialog systems.
