Name
Title | ||
|---|---|---|
Speaker Role Contextual Modeling for Language Understanding and Dialogue Policy Learning. |
Abstract | ||
|---|---|---|
Language understanding (LU) and dialogue policy learning are two essential components in conversational systems. Human-human dialogues are not well-controlled and often random and unpredictable due to their own goals and speaking habits. This paper proposes a role-based contextual model to consider different speaker roles independently based on the various speaking patterns in the multi-turn dialogues. The experiments on the benchmark dataset show that the proposed role-based model successfully learns role-specific behavioral patterns for contextual encoding and then significantly improves language understanding and dialogue policy learning tasks. |
Year | Venue | DocType |
|---|---|---|
2017 | international joint conference on natural language processing | Conference |
Volume | Citations | PageRank |
abs/1710.00164 | 3 | 0.41 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ta-Chung Chi | 1 | 6 | 2.51 |
| Po-Chun Chen | 2 | 3 | 0.41 |
| Shang-Yu Su | 3 | 3 | 0.41 |
| Yun-Nung Chen | 4 | 324 | 35.41 |