In this paper, we study the problem of data augmentation for language understanding in taskoriented dialogue system.
to previous work which augments an utterance without considering its relation with other utterances, we propose a sequence-to-sequence generation based data augmentation framework that leverages one utterance's same semantic alternatives in the training data.