Knowledge-based Dialogue Processing
❏ Dialogue over context and structured knowledge using a neural network model with an external memory
Overview
The Differentiable Neural Computer (DNC), a neural network model with an addressable external memory, can solve algorithmic and question-answering tasks. There are various improved versions of DNC, such as rsDNC and DNC-DMS. However, how to integrate structured knowledge into these DNC models remains a challenging research question. We incorporate an architecture for knowledge into such DNC models, i.e. DNC, rsDNC, and DNC-DMS, to improve the ability to generate correct responses using both contextual information and structured knowledge. Our improved rsDNC model improves the mean accuracy by approximately 20% to the original rsDNC on tasks requiring knowledge in the dialog bAbI tasks. In addition, our improved rsDNC and DNC-DMS models also yield better performance than their original models in the Movie Dialog dataset.
Slides
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Yuri Murayama
Murayama, Yuri, Lis Kanashiro Pereira, and Ichiro Kobayashi. “Dialogue over context and structured knowledge using a neural network model with external memories.” In Proceedings of Knowledgeable NLP: the First Workshop on Integrating Structured Knowledge and Neural Networks for NLP, pp. 11-20. 2020.