EnDex: Evaluation of Dialogue Engagingness at Scale

• Published in: arXiv.org
• Main Authors: Xu, Guangxuan, Liu, Ruibo, Harel-Canada, Fabrice, Nischal Reddy Chandra, Peng, Nanyun
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 22.10.2022
• Subjects: Ablation; Datasets; Evaluation; User experience

We propose EnDex, the first human-reaction based model to evaluate dialogue engagingness. EnDex is trained on 80k Reddit-based Engagement Dataset (RED) curated using a novel distant-supervision framework. Engagingness is a key measure that captures high-level quality of AI dialogue systems and close...