SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Tracking (P19-1)
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| Challenge: | Existing methods to model domain- and slot-dependent belief trackers have difficulty adding new slot-values, resulting in lack of flexibility of domain ontology configurations. |
| Approach: | They propose a model that captures relationships between domain-slot-types and slot-values appearing in utterances through attention mechanisms based on contextual semantic vectors. |
| Outcome: | The proposed model improves performance on two dialog corpora and achieves state-of-the-art accuracy. |
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| Challenge: | Existing methods for Dialog State Tracking do not generalize well to new domains and unseen slots. |
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