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The use of connectionist approaches in conversational agents has beenprogressing rapidly due to the availability of large corpora. However currentgenerative dialogue models often lack coherence and are content poor. This workproposes an architecture to incorporate unstructured knowledge sources toenhance the next utterance prediction in chit-chat type of generative dialoguemodels. We focus on Sequence-to-Sequence (Seq2Seq) conversational agentstrained with the Reddit News dataset, and consider incorporating externalknowledge from Wikipedia summaries as well as from the NELL knowledge base. Ourexperiments show faster training time and improved perplexity when leveragingexternal knowledge.

Extending Neural Generative Conversational Model using External Knowledge Sources