| Presentation | 2014-12-15 Dialogue state tracking in statistical dialogue management Kai YU, Lu CHEN, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Dialogue state tracking (DST) is a process to estimate the distribution of the dialogue states of each dialogue turn given the previous interaction history. It plays an important role in statistical dialogue management based on partially observable Markov decision process (POMDP). This paper reviews and compare various statistical and rule based approaches for dialogue state tracking. Then, a novel framework, constrained Markov Polynomial Bayesian, is introduced. It combines the advantage of both rule and statistical approach and offers a highly efficient way for dialogue state tracking. |
| Keyword(in Japanese) | (See Japanese page) |
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| Paper # | SP2014-108 |
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| Committee | SP |
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| Conference Date | 2014/12/8(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Speech (SP) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Dialogue state tracking in statistical dialogue management |
| Sub Title (in English) | |
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| 1st Author's Name | Kai YU |
| 1st Author's Affiliation | SpeechLab, Department of Computer Science and Engineering, Shanghai Jiao Tong University() |
| 2nd Author's Name | Lu CHEN |
| 2nd Author's Affiliation | SpeechLab, Department of Computer Science and Engineering, Shanghai Jiao Tong University |
| Date | 2014-12-15 |
| Paper # | SP2014-108 |
| Volume (vol) | vol.114 |
| Number (no) | 365 |
| Page | pp.pp.- |
| #Pages | 5 |
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