Year: 2024
Type: preprint
Abstract: Empathetic Conversational Systems (ECS) are built to respond empathetically to the user's emotions and sentiments, regardless of the application domain. Current ECS studies evaluation approaches are restricted to offline evaluation experiments primarily for gold standard comparison & benchmarking, and user evaluation studies for collecting human ratings on specific constructs. These methods are inadequate in measuring the actual quality of empathy in conversations. In this paper, we propose a multidimensional empathy evaluation framework with three new methods for measuring empathy at (i) structural level using three empathy-related dimensions, (ii) behavioral level using empathy behavioral types, and (iii) overall level using an empathy lexicon, thereby fortifying the evaluation process. Experiments were conducted with the state-of-the-art ECS models and large language models (LLMs) to show the framework's usefulness.
Source: arXiv (Cornell University)
Institution: Agency for Science, Technology and Research
Language: English
Topic: Emotion and Mood Recognition
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4401594491