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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)
Portability of a spoken dialogue system (SDS) to a new domain or a new language is a hot topic as it may imply gains in time and cost for building new SDSs. In particular in this paper we investigate several fast and efficient approaches for language portability of the spoken language understanding (SLU) module of a dialogue system. We show that the use of(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)
Many recent competitive state-of-the-art solutions for understanding of speech data have in common to be probabilistic and to rely on machine learning algorithms to train their models from large amount of data. The difficulty remains in the cost and time of collecting and annotating such data, but also to update the existing models to new conditions, tasks(More)
Generalization of spoken dialogue systems increases the need for fast development of spoken language understanding modules for semantic tagging of speaker's turns. Statistical methods are performing well for this task but require large corpora to be trained. Collecting such corpora is expensive in time and human expertise. In this paper we propose a semi(More)
RÉSUMÉ Le projet ANR PORTMEDIA avait pour objectif de compléter le corpus MEDIA afin de favoriser le développement de méthodes performantes, notamment statistiques, pour la compréhension automatique de la parole dans le cadre des systèmes de dialogues homme-machines. Les princi-paux axes traités sont : la robustesse aux erreurs de reconnaissance de la(More)