Generalization of discriminative approaches for speech language understanding in a multilingual context

Authors:
Bassam Jabaian;Fabrice Lefèvre;Laurent Besacier
Affiliations:
LIA, University of Avignon, Avignon, France;LIA, University of Avignon, Avignon, France;LIG, University Joseph Fourrier, Grenoble, France
Venue:
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
Year:
2013

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Abstract

Probabilistic approaches are now widespread in the various applications of natural language processing and elicitation of a particular approach usually depends on the task at hand. Targeting multilingual interpretation of speech, this paper presents a comparison between the state-of-the-art methods used for machine translation and speech understanding. This comparison justifies our proposition of a unified framework to perform a joint decoding which translates a sentence and assigns semantic tags to this translation in the same process. The decoding is achieved using a cascade of finite-state transducers allowing to compose translation and understanding hypothesis graphs. This representation is favorable as it can be generalized to allow rich transmission of information between the components of a human-machine vocal interface.