A system for primitive natural language acquisition

Abstract

Natural language acquisition deals with two very difficult problems in artificial intelligence: computer learning and natural language processing. This system focuses on the problems involved in the acquisition of primitive linguistic capability. That is when words are first correlated to concepts and when the ordering of the words of utterance first become important. With these beginnings the techniques developed herein eventually acquire the capability to deal with nested dependent clauses. This work is of interest in the field of computer learning in as much as it provides an example of an adaptive system that, rather than tuning numeric weights, actually varies its primary structural element, namely the grammar that defines its current language. This work is of interest in the field of natural language processing in as much as it requires the development of a parsing algorithm robust enough to deal with grammars and dictionaries that vary with time. The ability to automatically extend the,grammar to include new sentence forms is also requisite for language acquisition.