Tom Laureys


2004

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A Comparison of Two Different Approaches to Morphological Analysis of Dutch
Guy De Pauw | Tom Laureys | Walter Daelemans | Hugo Van hamme
Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology

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Evaluation and Adaptation of the Celex Dutch Morphological Database
Tom Laureys | Guy De Pauw | Hugo Van hamme | Walter Daelemans | Dirk Van Compernolle
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

This paper describes some important modifications to the Celex morphological database in the context of the FLaVoR project. FLaVoR aims to develop a novel modular framework for speech recognition, enabling the integration of complex linguistic knowledge sources, such as a morphological model. Morphology is a fairly unexploited linguistic information source speech recognizers could benefit from. This is especially true for languages which allow for a rich set of morphological operations, such as our target language Dutch. In this paper we focus on the exploitation of the Celex Dutch morphological database as the information source underlying two different morphological analyzers being developed within the project. Although the Celex database provides a valuable source of morphological information for Dutch, many modifications were necessary before it could be practically applied. We identify major problems, discuss the implemented solutions and finally experimentally evaluate the effect of our modifications to the database.

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Automatic Phonemic Labeling and Segmentation of Spoken Dutch
Kris Demuynck | Tom Laureys | Patrick Wambacq | Dirk Van Compernolle
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

The CGN corpus (Corpus Gesproken Nederlands/Corpus Spoken Dutch) is a large speech corpus of contemporary Dutch as spoken in Belgium (3.3 million words) and in the Netherlands (5.6 million words). Due to its size, manual phonemic annotation was limited to 10% of the data and automatic systems were used to complement this data. This paper describes the automatic generation of the phonemic annotations and the corresponding segmentations. First, we detail the processes used to generate possible pronunciations for each sentence and to select to most likely one. Next, we identify the remaining difficulties when handling the CGN data and explain how we solved them. We conclude with an evaluation of the quality of the resulting transcriptions and segmentations.

2002

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An Improved Algorithm for the Automatic Segmentation of Speech Corpora
Tom Laureys | Kris Demuynck | Jacques Duchateau | Patrick Wambacq
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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Word Segmentation in the Spoken Dutch Corpus
Jean-Pierre Martens | Diana Binnenpoorte | Kris Demuynck | Ruben Van Parys | Tom Laureys | Wim Goedertier | Jacques Duchateau
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)