MoEL: Mixture of Empathetic Listeners

08/21/2019
by   Zhaojiang Lin, et al.
0

Previous research on empathetic dialogue systems has mostly focused on generating responses given certain emotions. However, being empathetic not only requires the ability of generating emotional responses, but more importantly, requires the understanding of user emotions and replying appropriately. In this paper, we propose a novel end-to-end approach for modeling empathy in dialogue systems: Mixture of Empathetic Listeners (MoEL). Our model first captures the user emotions and outputs an emotion distribution. Based on this, MoEL will softly combine the output states of the appropriate Listener(s), which are each optimized to react to certain emotions, and generate an empathetic response. Human evaluations on empathetic-dialogues (Rashkin et al., 2018) dataset confirm that MoEL outperforms multitask training baseline in terms of empathy, relevance, and fluency. Furthermore, the case study on generated responses of different Listeners shows high interpretability of our model.

READ FULL TEXT
research
06/06/2021

Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interaction

The consistency of a response to a given post at semantic-level and emot...
research
06/20/2019

HappyBot: Generating Empathetic Dialogue Responses by Improving User Experience Look-ahead

Recent neural conversation models that attempted to incorporate emotion ...
research
11/20/2019

EmpGAN: Multi-resolution Interactive Empathetic Dialogue Generation

Conventional emotional dialogue system focuses on generating emotion-ric...
research
11/15/2020

Target Guided Emotion Aware Chat Machine

The consistency of a response to a given post at semantic-level and emot...
research
06/02/2023

EmoUS: Simulating User Emotions in Task-Oriented Dialogues

Existing user simulators (USs) for task-oriented dialogue systems only m...
research
11/19/2019

Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation

Dialogue response generation (DRG) is a critical component of task-orien...
research
05/03/2022

The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts

The ICML Expressive Vocalization (ExVo) Competition is focused on unders...

Please sign up or login with your details

Forgot password? Click here to reset