This article provides a comprehensive review of dialogue evaluation metrics for conversational AI, covering aspects such as engagement, coherence, and relevance.
The National Institute of Standards and Technology (NIST) provides an overview of conversational AI dialogue evaluation metrics, including automatic and human evaluation methods.
This survey paper discusses various dialogue evaluation metrics for conversational AI, including metrics for evaluating response generation, dialogue management, and user experience.
The Conversational AI Evaluation Toolkit is an open-source tool for evaluating conversational AI models, providing a range of metrics and evaluation protocols for assessing dialogue quality.
This research paper from MIT explores the challenges of evaluating conversational AI dialogue systems and proposes a framework for evaluating dialogue systems using a combination of automatic and human evaluation metrics.
This article discusses the importance of evaluating conversational AI metrics, including metrics such as user engagement, conversation completion rate, and customer satisfaction.
This course lecture from Stanford University covers the fundamentals of dialogue evaluation metrics for conversational AI, including metrics for evaluating dialogue coherence, relevance, and engagement.
This video lecture provides an introduction to conversational AI evaluation metrics, covering topics such as automatic evaluation metrics, human evaluation metrics, and evaluation protocols.