Towards domain adaptation for Neural Network Language Generation in Dialogue

This paper studies the performance and domain adaptation of two different Neural Network Language Generators in Spoken Dialogue Systems: a gating-based Recurrent Neural Network Generator and an extension of an Attentional Encoder-Decoder Generator.