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A new Automatic approach for Understanding the Spontaneous Utterance in Human-Machine Dialogue based on Automatic Text Categorization

In the present paper, we suggested an implementation of an automatic understanding system of the statement in Human-Machine Communication. The architecture we adopted was based on a stochastic approach that assumes that the understanding of a statement is nothing but a simple theme identification process. Therefore, we presented a new theme identification method based on a documentary retrieval technique which is text (document) classification [2]. The method we suggested was validated on a basic platform that give information related to university schooling management (Querying a student database), taking into consideration a textual input in french. This method has achieved a theme identification rate of 95% and a correctly utterance understanding rate of about 91.66%.