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Dynamical System Modelling of Articulator Movement

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    Rights statement: © King, S., & Wrench, A. (1999). Dynamical System Modelling of Articulator Movement. In ICPhS 99: Proceedings of the XIVth International Congress of Phonetic Sciences. (pp. 2259-2262). San Francisco: International Congress of Phonetic Sciences.

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    Licence: Creative Commons: Attribution No Derivatives (CC-BY-ND)

Original languageEnglish
Title of host publicationICPhS 99
Subtitle of host publicationProceedings of the XIVth International Congress of Phonetic Sciences
Place of PublicationSan Francisco
PublisherInternational Congress of Phonetic Sciences
Pages2259-2262
Number of pages4
ISBN (Print)9781563968990
Publication statusPublished - 1 Aug 1999

Abstract

We describe the modelling of articulatory movements using (hidden) dynamical system models trained on Electro-Magnetic Articulograph (EMA) data. These models can be used for automatic speech recognition and to give insights into articulatory behaviour. They belong to a class of continuous-state Markov models, which we believe can offer improved performance over conventional Hidden Markov Models (HMMs) by better accounting for the continuous nature of the underlying speech production process -- that is, the movements of the articulators. To assess the performance of our models, a simple speech recognition task was used, on which the models show promising results.

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