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2020 | OriginalPaper | Chapter

Reinforcement Learning Based Personalized Neural Dialogue Generation

Authors : Tulika Saha, Saraansh Chopra, Sriparna Saha, Pushpak Bhattacharyya

Published in: Neural Information Processing

Publisher: Springer International Publishing

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Abstract

In this paper, we present a persona aware neural reinforcement learning response generation framework capable of optimizing long-term rewards carefully devised by system developers. The proposed model utilizes an extension of the recently introduced Hierarchical Encoder Decoder (HRED) architecture. We leverage insights from Reinforcement Learning (RL) and employ policy gradient methods to optimize rewards which are defined as simple heuristic approximations that indicate good conversation to a human mind. The proposed model is demonstrated on two benchmark datasets. Empirical results indicate that the proposed approach outperforms their counterparts that do not optimize long-term rewards, have no access to personas, standard models trained using solely maximum-likelihood estimation objective.

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Title: Reinforcement Learning Based Personalized Neural Dialogue Generation
Authors: Tulika Saha
Saraansh Chopra
Sriparna Saha
Pushpak Bhattacharyya
Publisher: Springer International Publishing
Book: Neural Information Processing
Print ISBN: 978-3-030-63819-1

Electronic ISBN: 978-3-030-63820-7

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-63820-7_81

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