Context-Aware Sequence-to-Sequence Models for Conversational Systems

05/22/2018
by   Silje Christensen, et al.
2

This work proposes a novel approach based on sequence-to-sequence (seq2seq) models for context-aware conversational systems. Exist- ing seq2seq models have been shown to be good for generating natural responses in a data-driven conversational system. However, they still lack mechanisms to incorporate previous conversation turns. We investigate RNN-based methods that efficiently integrate previous turns as a context for generating responses. Overall, our experimental results based on human judgment demonstrate the feasibility and effectiveness of the proposed approach.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset