most citedNatural Language Generation for Spoken Dialogue System using RNN Encoder-Decoder Networks

19 citations · 29 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL2018

Dual Latent Variable Model for Low-Resource Natural Language Generation in Dialogue Systems

Van-Khanh Tran, Le-Minh Nguyen

Recent deep learning models have shown improving results to natural language generation (NLG) irrespective of providing sufficient annotated data. However, a modest training data m…

cs.CL2018

Adversarial Domain Adaptation for Variational Neural Language Generation in Dialogue Systems

Van-Khanh Tran, Le-Minh Nguyen

Domain Adaptation arises when we aim at learning from source domain a model that can per- form acceptably well on a different target domain. It is especially crucial for Natural La…

cs.CL2017

Neural-based Natural Language Generation in Dialogue using RNN Encoder-Decoder with Semantic Aggregation

Van-Khanh Tran, Le-Minh Nguyen

Natural language generation (NLG) is an important component in spoken dialogue systems. This paper presents a model called Encoder-Aggregator-Decoder which is an extension of an Re…

cs.CL201710 cited

Semantic Refinement GRU-based Neural Language Generation for Spoken Dialogue Systems

Van-Khanh Tran, Le-Minh Nguyen

Natural language generation (NLG) plays a critical role in spoken dialogue systems. This paper presents a new approach to NLG by using recurrent neural networks (RNN), in which a g…

cs.IR2017

Improving Legal Information Retrieval by Distributional Composition with Term Order Probabilities

Danilo S. Carvalho, Duc-Vu Tran, Van-Khanh Tran +1

Legal professionals worldwide are currently trying to get up-to-pace with the explosive growth in legal document availability through digital means. This drives a need for high eff…

cs.CL201719 cited

Natural Language Generation for Spoken Dialogue System using RNN Encoder-Decoder Networks

Van-Khanh Tran, Le-Minh Nguyen

Natural language generation (NLG) is a critical component in a spoken dialogue system. This paper presents a Recurrent Neural Network based Encoder-Decoder architecture, in which a…