Abstract
The concept of empathy is vital in human-agent systems as it contributes to mutual understanding, problem-solving and sustained relationships. Despite the increasing adoption of conversational systems as one of the most significant events in the recent decade, the emotional aspects require considerable improvements, particularly in effectively displaying empathy. This paper provides a critical review of this rapidly growing field by examining the current advances in four dimensions: (i) conceptual empathy models and frameworks, (ii) the adopted empathy-related concepts, (iii) the datasets and algorithmic techniques developed, and (iv) the evaluation strategies. The review findings show that the most studies centred on the use of the EMPATHETICDIALOGUES dataset, and the text-based modality dominated research in this field. Moreover, studies have focused mainly on extracting features from the messages of both users and the conversational systems, with minimal emphasis on user modelling and profiling. For implementation in variegated real-world domain settings, we recommend that future studies address the gaps in detecting and authenticating emotions at the entity level, handling multimodal inputs, displaying more nuanced empathetic behaviours, and encompassing additional dialogue system features.
Abstract (translated)
URL
https://arxiv.org/abs/2206.05017
