CONVERSATIONAL AI

RESEARCH

Extending Neural Generative Conversational Model using External Knowledge Sources

October 31, 2018

Abstract

The use of connectionist approaches in conversational agents has been progressing rapidly due to the availability of large corpora. However current generative dialogue models often lack coherence and are content poor. This work proposes an architecture to incorporate unstructured knowledge sources to enhance the next utterance prediction in chit-chat type of generative dialogue models. We focus on Sequence-to-Sequence (Seq2Seq) conversational agents trained with the Reddit News dataset, and consider incorporating external knowledge from Wikipedia summaries as well as from the NELL knowledge base. Our experiments show faster training time and improved perplexity when leveraging external knowledge.

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AUTHORS

Written by

Joelle Pineau

Prasanna Parthasarathi

Publisher

EMNLP

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