Almost from the very beginning of the digital age, people have sought better ways to communicate with computers. This research investigates how computers might be enabled to understand natural language in a more humanlike way. Based, in part, on cognitive development in infants, we introduce an open computational framework for visual perception and grounded language acquisition called Experience-Based Language Acquisition (EBLA). EBLA can watch a series of short videos and acquire a simple language of nouns and verbs corresponding to the objects and object-object relations in those videos. Upon acquiring this protolanguage, EBLA can perform basic scene analysis to generate descriptions of novel videos. The general architecture of EBLA is comprised of three stages: vision processing, entity extraction, and lexical resolution. In the vision processing stage, EBLA processes the individual frames in short videos, using a variation of the mean shift analysis image segmentation algorithm...

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