Abstract
For almost 30 years, digital nonlinear editing systems (DNLEs) have functioned as a practical replacement for film and videotape editing. While DNLEs have progressed in their capabilities by offering increased video resolutions and visual effects, they have not fundamentally changed their operational constructs. Editors must still choose in and out points of shots and then methodically edit those shots into a cohesive sequencing. Technology improvements in artificial intelligence and machine learning have the potential to profoundly impact how DNLE systems operate, and, in turn, content creation methodologies will dramatically change. This paper examines the effects of image recognition, natural speech processing, language recognition, cognitive metadata extraction, tonal analysis, and data and statistical integration on the creation of content.
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