Use of Grammatical Inference in Natural Speech Recognition

Abstract

This paper presents the application of stochastic grammatical inference to speech recognition. In speech recognition, the acoustic signal process produces a set of words which are combinating to build sentences. Language models are then used to lead the speech recognition application to the most pertinent combination. Up to now, statistical language models are used. We suggest to use stochastic formal grammars instead of statistical models. Theses stochastic grammars will be build by machine learning algorithms. We will first show that unaided grammatical inference cannot be used for speech recognition. We will then make manifest that smoothing is necessary and show the gain that one can obtain by using a basic smoothing. We finally put up a smoothing technic dedicates to stochastic formal grammars. 2 THE QUALITY CRITERION 1 Introduction Our aim is to use stochastic grammatical inference for natural speech recognition. The main difference between validations of grammatical inference..