A machine learning system infers a “brand score” curve of a video across the run time for the video. The system uses a ground truth score obtained using user surveys, audio transcription of words spoken, video transcription of words displayed, type of music being played, and computer vision signals to learn a model for inferring the brand score. A given video is segmented, and a piecewise brand score for each segment is generated using the model.
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Porteous, Ian and Asuncion, Arthur, "Machine-Learned Temporal Brand Scores for Video Ads", Technical Disclosure Commons, (August 11, 2016)