🤖 AI Summary
This study investigates the distribution of silent gaps in human and AI-generated spoken interactions and their role in turn-taking. Employing a distant viewing methodology, the authors analyze 30 American sitcoms and 51 synthetic podcasts generated by Google NotebookLM—the first application of this approach to compare silence thresholds between human and AI speech. Using Praat, speaker gender is automatically annotated based on fundamental frequency, and silence intervals in audiovisual materials are detected and statistically analyzed. The findings reveal that the duration distribution of silences in AI-generated content significantly differs from that in human dialogue, and that both speaker gender and production context systematically influence silence thresholds, thereby uncovering distinctive characteristics of generative audio in conversational turn structure.
📝 Abstract
This study investigates silence gaps in two kinds of audiovisual material. We analysed thirty US situational comedies and fifty-one synthetic podcasts generated with Google NotebookLM. Gaps were compared across speaker gender, assigned from a fundamental-frequency threshold estimated in Praat, and across production settings.