The DeepSpeak-Agentic Dataset
The DeepSpeak-Agentic dataset consists of over 37 hours of semi-structured conversations between humans and AI agents. This dataset aims to enhance the forensic identification of AI agents and improve understanding of human-agent interactions. Additionally, it introduces a scalable system for capturing and analyzing these interactions.
- ▪The dataset includes more than 37 hours of video conversations.
- ▪It is designed to evaluate the identification of AI agents through audio, video, and text.
- ▪The research contributes to advancements in large-language models and AI-generated content.
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Computer Science > Artificial Intelligence arXiv:2606.03686 (cs) [Submitted on 2 Jun 2026] Title:The DeepSpeak-Agentic Dataset Authors:Sarah Barrington, Maty Bohacek, Hany Farid View a PDF of the paper titled The DeepSpeak-Agentic Dataset, by Sarah Barrington and 2 other authors View PDF Abstract:We present DeepSpeak-Agentic, a dataset of videos comprising over 37 hours of semi-structured conversations between a human and an embodied AI agent. We use this dataset to evaluate the automatic forensic identification (audio, video, or text) of AI agents, study the nature of human-agent interactions, and provide a benchmark for future advances in the large-language models and AI-generated voices and faces that power embodied AI agents.
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