Papers with Airline Travel Information System dataset

1 papers
Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding (C18-1)

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Challenge: Existing work which augments an utterance without considering its relation with other utterrances, however, has failed to improve the language understanding module.
Approach: They propose a sequence-to-sequence generation based data augmentation framework that leverages one utterance’s same semantic alternatives in the training data.
Outcome: The proposed framework achieves 6.38 and 10.04 F-scores on the Airline Travel Information System dataset and a newly created semantic frame annotation on the Stanford Multi-turn, Multi-domain Dialogue Dataset.

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