TotalRecall: Visualization and Semi-Automatic Annotation of Very Large Audio-Visual Corpora

Rony Kubat, Philip DeCamp, Brandon Roy, Deb Roy


We introduce a system for visualizing, annotating, and analyzing very large collections of longitudinal audio and video recordings. The system, TotalRecall, is designed to address the requirements of projects like the Human Speechome Project [18], for which more than 100,000 hours of multitrack audio and video have been collected over a twentytwo month period. Our goal in this project is to transcribe speech in over 10,000 hours of audio recordings, and to annotate the position and head orientation of multiple people in the 10,000 hours of corresponding video. Higher level behavioral analysis of the corpus will be based on these and other annotations. To efficiently cope with this huge corpus, we are developing semi-automatic data coding methods that are integrated into TotalRecall. Ultimately, this system and the underlying methodology may enable new forms of multimodal behavioral analysis grounded in ultradense longitudinal data.

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