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In this paper, several approaches for language portability of dialogue systems are investigated with a focus on the spoken language understanding (SLU) component. We show that the use of statistical machine translation (SMT) can greatly reduce the time and cost of porting an existing system from a source to a target language. Using automatically translated(More)
The challenge with language portability of a spoken language understanding module is to be able to reuse the knowledge and the data available in a source language to produce knowledge in the target language. In this paper several approaches are proposed, motivated by the availability of the MEDIA French dialogue corpus and its manual translation into(More)
The PORTMEDIA project is intended to develop new corpora for the evaluation of spoken language understanding systems. The newly collected data are in the field of human-machine dialogue systems for tourist information in French in line with the MEDIA corpus. Transcriptions and semantic annotations, obtained by low-cost procedures, are provided to allow a(More)
Probabilistic approaches are now widespread in most natural language processing applications and selection of a particular approach usually depends on the task at hand. Targeting speech semantic interpretation in a multilingual context, this paper presents a comparison between the state-of-the-art methods used for machine translation and speech(More)