%0 Generic %1 serban2015building %A Serban, Iulian V. %A Sordoni, Alessandro %A Bengio, Yoshua %A Courville, Aaron %A Pineau, Joelle %D 2015 %K attention-rnn nn rnn %T Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models %U http://arxiv.org/abs/1507.04808 %X We investigate the task of building open domain, conversational dialogue systems based on large dialogue corpora using generative models. Generative models produce system responses that are autonomously generated word-by-word, opening up the possibility for realistic, flexible interactions. In support of this goal, we extend the recently proposed hierarchical recurrent encoder-decoder neural network to the dialogue domain, and demonstrate that this model is competitive with state-of-the-art neural language models and back-off n-gram models. We investigate the limitations of this and similar approaches, and show how its performance can be improved by bootstrapping the learning from a larger question-answer pair corpus and from pretrained word embeddings.

@misc{serban2015building, abstract = {We investigate the task of building open domain, conversational dialogue systems based on large dialogue corpora using generative models. Generative models produce system responses that are autonomously generated word-by-word, opening up the possibility for realistic, flexible interactions. In support of this goal, we extend the recently proposed hierarchical recurrent encoder-decoder neural network to the dialogue domain, and demonstrate that this model is competitive with state-of-the-art neural language models and back-off n-gram models. We investigate the limitations of this and similar approaches, and show how its performance can be improved by bootstrapping the learning from a larger question-answer pair corpus and from pretrained word embeddings.}, added-at = {2016-12-03T03:26:50.000+0100}, author = {Serban, Iulian V. and Sordoni, Alessandro and Bengio, Yoshua and Courville, Aaron and Pineau, Joelle}, biburl = {https://www.bibsonomy.org/bibtex/2f93a2fa38c2b14faa1de5fd52243e0f7/jkan}, description = {Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models}, interhash = {22dfc8355f1fb003664427c4251aa8c3}, intrahash = {f93a2fa38c2b14faa1de5fd52243e0f7}, keywords = {attention-rnn nn rnn}, note = {cite arxiv:1507.04808Comment: 8 pages with references; Published in AAAI 2016 (Special Track on Cognitive Systems)}, timestamp = {2016-12-03T03:26:50.000+0100}, title = {Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models}, url = {http://arxiv.org/abs/1507.04808}, year = 2015 }