Associative processes between behavioral symbols and a large scale language model

Abstract

This paper describes an novel approach towards linguistic processing for robots through integration of a motion language model and a natural language model. The motion language model works for association of words from motion symbols. The natural language model is one used for a morphological analysis, which has been developed in natural language community. The natural language model is optimized using a enormous amount of words. So this model is scalable architecture. The motion language model and the natural language model can be integrated since both models are represented graphically. The integration of the motion language model and the natural language model allows robots not only to interpret motion patterns as sentences but also to generate motions from sentences. This paper demonstrates the validity of our proposed framework even in the case that large-scale word corpus is needed processing through experiments of interpreting motion patterns as sentences and generating motion patterns from sentences.