Learning Language from Perceptual Context: A Challenge Problem for AI
Raymond J. Mooney · 2006
We present the problem of learning to understand natural language from examples of utterances paired only with their relevant real-world context as an important challenge problem for AI. Machine learning has been adopted as the most effective way of developing naturallanguage processing systems; however, currently, complex annotated corpora are required for training. By learning language from perceptual context, the need for laborious annotation is removed and the system’s resulting understanding is grounded in its perceptual experience.