Naturalness Assessment

Naturalness assessment focuses on evaluating the perceived realism and quality of artificially generated content, encompassing speech, images, code, and even counterfactual scenarios. Current research emphasizes developing objective metrics and models, often leveraging deep learning architectures like vision transformers and pre-trained language models, to predict human judgments of naturalness, often incorporating features from multiple perspectives (e.g., prosodic, linguistic, technical, and rational). This work is crucial for improving the quality of AI-generated content across various applications and for advancing our understanding of human perception and judgment. The development of robust and reliable naturalness assessment methods is vital for ensuring the responsible and effective deployment of AI systems.