Corpus ID: 218517128

TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking

@inproceedings{Heck2020TripPyAT,
  title={TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking},
  author={Michael Heck and Carel van Niekerk and Nurul Lubis and Christian Geishauser and Hsien-Chin Lin and M. Moresi and Milica Gavsi'c},
  booktitle={SIGDIAL},
  year={2020}
}
Task-oriented dialog systems rely on dialog state tracking (DST) to monitor the user’s goal during the course of an interaction. Multi-domain and open-vocabulary settings complicate the task considerably and demand scalable solutions. In this paper we present a new approach to DST which makes use of various copy mechanisms to fill slots with values. Our model has no need to maintain a list of candidate values. Instead, all values are extracted from the dialog context on-the-fly. A slot is… Expand
Multi-domain Dialogue State Tracking with Recursive Inference
STN4DST: A Scalable Dialogue State Tracking based on Slot Tagging Navigation
Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue StateTracking
Zero-shot Generalization in Dialog State Tracking through Generative Question Answering
...
1
2
3
4
...

References

SHOWING 1-10 OF 30 REFERENCES
MultiWOZ 2.1: Multi-Domain Dialogue State Corrections and State Tracking Baselines
Efficient Dialogue State Tracking by Selectively Overwriting Memory
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking
Dialog State Tracking: A Neural Reading Comprehension Approach
MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines
Building a Conversational Agent Overnight with Dialogue Self-Play
A Network-based End-to-End Trainable Task-oriented Dialogue System
Neural Belief Tracker: Data-Driven Dialogue State Tracking
...
1
2
3
...