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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2560))

Abstract

Automatic speech recognition (ASR) systems have reached a technological level that allows their usage in real applications. Leaning towards the human processing of speech various models need to be built to reflect these procedures. Since these models perform badly when there is a mismatch between the situation the system was faced with during the training stage of the models and the situation in which it is actually used or tested,adaptation methods are widely used to adapt the models to the current situation.

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© 2002 Springer-Verlag Berlin Heidelberg

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(2002). Summary. In: Goronzy, S. (eds) Robust Adaptation to Non-Native Accents in Automatic Speech Recognition. Lecture Notes in Computer Science(), vol 2560. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36290-8_10

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  • DOI: https://doi.org/10.1007/3-540-36290-8_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00325-0

  • Online ISBN: 978-3-540-36290-6

  • eBook Packages: Springer Book Archive

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