An optimal human adaptive algorithm to find action - Reaction word-pairs

Abstract

This paper presents an efficient approach for understanding the formation of associations between random sentences spoken by humans over a period of time. The associations formed are mathematical relations (A X B) where the former is called as the "action" and the latter as the "reaction". The voice-to-text converted file is the input to the algorithm. After processing, the algorithm devises a map (Actions X Reactions). The algorithm stops only after the relation becomes surjective. The most important improvement over the previous techniques is the automatic adaptation of the machine to the ever-changing grammar of the user in real-time. © 2011 Springer-Verlag.