CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots (D19-1)
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| Challenge: | Prior work on contextual NLU has been limited in terms of the types of contextual signals used and the understanding of their impact on the model. |
| Approach: | They propose a context-aware self-attentive NLU model that uses multiple signals over a variable context window, such as previous intents, slots, dialog acts and utterances, in addition to the current user uttered. |
| Outcome: | The proposed model outperforms a baseline model on two conversational datasets yielding a gain of up to 7% on the IC task. |
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