Research towards speech understanding models for artificial and natural languages

The Signal Processing and Pattern Recognition Group in Nancy is developing the MYRTILLE System for recognizing and understanding sentences in artificial and natural languages. A model for the oral control of a telephone exchange with an artificial language was proposed and described at ICASSP 76. In this paper, we first present a comparative study of two syntactic models that we have used concurrently in this experiment : a classical top-down model and a generalized bottom-up, island-driven model. Then, we discuss the generalization of this model to natural language understanding system (e.g. for the oral consultation of a data base). Such a generalization involves a very different structure, which is described in details.