Abstract
In recent years, with the extensive application of deep learning technology, breakthroughs have been made in the study of human-computer dialogue. However, most of the current human-machine dialogue systems are designed under the assumption that both parties are involved, and the research and application of more challenging multi-party human-machine dialogues are not yet mature. Based on the field of natural language processing, this paper will review the research progress of multi-party dialogue based on deep learning in recent years. First, from the perspective of human-machine dialogue, we sort out the key problems and existing solutions of the multi-party dialogue system; then, we introduce other natural language processing tasks based on multi-party dialogue; afterwards, we summarize the existing multi-party dialogue research dataset and make a comparative analysis of limitations on the existing dataset; Finally, we look forward to the future development trend of multi-party dialogue research.
| Translated title of the contribution | A survey of multi-party dialogue research based on deep learning |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 1217-1232 |
| Number of pages | 16 |
| Journal | Scientia Sinica Informationis |
| Volume | 51 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 2021 |
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