YuJa’s Semantic Topic Analysis provides an automated, topical overview of subjects covered in a capture or uploaded video. The technology is able to quickly categorize the information in the video and creates a visual mindmap for the viewer.
Semantic Topic Analysis starts with YuJa’s high-quality auto-captioning technology. Auto-captioning produces a text transcript of the lecture capture content. Next, semantic topic analysis takes over:
Semantic Topic Analysis automatically reviews auto-captions to create an additional searchable topic meta-layer.
Lecture capture content is organized into topics in the lecture and super-topics that the topics fit into or under.
Super-topics become searchable, identifiable tags within the Media Management.
Super-topics become searchable tags, making it simple for students to find relevant content to further their academic goals.
Topics and super-topics enable students or instructors to quickly review lecture content, without watching the lecture.
Semantic Topic Analysis provides students with increased ability to make connections between different facts and subjects.
The topics and super-topics provide a quick, one-look summary of lecture capture or video content.