English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Expressing empathy is important in everyday conversations, and exploring howempathy arises is crucial in automatic response generation. Most previousapproaches consider only a single factor that affects empathy. However, inpractice, empathy generation and expression is a very complex and dynamicpsychological process. A listener needs to find out events which cause aspeaker's emotions (emotion cause extraction), project the events into someexperience (knowledge extension), and express empathy in the most appropriateway (communication mechanism). To this end, we propose a novel approach, whichintegrates the three components - emotion cause, knowledge graph, andcommunication mechanism for empathetic response generation. Experimentalresults on the benchmark dataset demonstrate the effectiveness of our methodand show that incorporating the key components generates more informative andempathetic responses.

Wish I Can Feel What You Feel: A Neural Approach for Empathetic Response Generation