Evaluator for Emotionally Consistent Chatbots

12/02/2021
by   Chenxiao Liu, et al.
0

One challenge for evaluating current sequence- or dialogue-level chatbots, such as Empathetic Open-domain Conversation Models, is to determine whether the chatbot performs in an emotionally consistent way. The most recent work only evaluates on the aspects of context coherence, language fluency, response diversity, or logical self-consistency between dialogues. This work proposes training an evaluator to determine the emotional consistency of chatbots.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/28/2017

A Dual Encoder Sequence to Sequence Model for Open-Domain Dialogue Modeling

Ever since the successful application of sequence to sequence learning f...
research
09/18/2018

Better Conversations by Modeling,Filtering,and Optimizing for Coherence and Diversity

We present three enhancements to existing encoder-decoder models for ope...
research
10/16/2019

Memory-Augmented Recurrent Networks for Dialogue Coherence

Recent dialogue approaches operate by reading each word in a conversatio...
research
08/15/2019

A Multi-Turn Emotionally Engaging Dialog Model

Open-domain dialog systems (also known as chatbots) have increasingly dr...
research
09/16/2021

Alquist 4.0: Towards Social Intelligence Using Generative Models and Dialogue Personalization

The open domain-dialogue system Alquist has a goal to conduct a coherent...
research
04/17/2019

Reinforcement Learning Based Emotional Editing Constraint Conversation Generation

In recent years, the generation of conversation content based on deep ne...
research
06/04/2021

Addressing Inquiries about History: An Efficient and Practical Framework for Evaluating Open-domain Chatbot Consistency

A good open-domain chatbot should avoid presenting contradictory respons...

Please sign up or login with your details

Forgot password? Click here to reset