Meta-Learning for Phonemic Annotation of Corpora

dc.creatorHoste, Veronique
dc.creatorDaelemans, Walter
dc.creatorSang, Erik Tjong Kim
dc.creatorGillis, Steven
dc.date2000-08-18
dc.date.accessioned2026-07-07T03:16:27Z
dc.date.available2026-07-07T03:16:27Z
dc.descriptionWe apply rule induction, classifier combination and meta-learning (stacked classifiers) to the problem of bootstrapping high accuracy automatic annotation of corpora with pronunciation information. The task we address in this paper consists of generating phonemic representations reflecting the Flemish and Dutch pronunciations of a word on the basis of its orthographic representation (which in turn is based on the actual speech recordings). We compare several possible approaches to achieve the text-to-pronunciation mapping task: memory-based learning, transformation-based learning, rule induction, maximum entropy modeling, combination of classifiers in stacked learning, and stacking of meta-learners. We are interested both in optimal accuracy and in obtaining insight into the linguistic regularities involved. As far as accuracy is concerned, an already high accuracy level (93% for Celex and 86% for Fonilex at word level) for single classifiers is boosted significantly with additional error reductions of 31% and 38% respectively using combination of classifiers, and a further 5% using combination of meta-learners, bringing overall word level accuracy to 96% for the Dutch variant and 92% for the Flemish variant. We also show that the application of machine learning methods indeed leads to increased insight into the linguistic regularities determining the variation between the two pronunciation variants studied.
dc.description8 pages
dc.identifierhttps://arxiv.org/abs/cs/0008013
dc.identifierhttp://arxiv.org/abs/cs/0008013
dc.identifierProceedings of ICML-2000, Stanford University, CA, USA
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30361
dc.subjectComputation and Language
dc.subjectI.2.7
dc.titleMeta-Learning for Phonemic Annotation of Corpora
dc.typetext

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