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International Workshop on Evaluation of Natural Language and Speech Tool for Italian

EVALITA 2012: Evaluation of Natural Language and Speech Tools for Italian pp 274–285Cite as

Evalita 2011: Automatic Speech Recognition Large Vocabulary Transcription

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7689))

Abstract

In this paper we describe design, setup and results of the speech recognition task in the framework of the Evalita campaign for the Italian language, giving details on the released corpora and tools used for the challenge. A general discussion about approaches to large vocabulary speech recognition introduces the recognition tasks. Systems are compared for recognition accuracy on audio sequences of Italian parliament. Although only a few systems have participated to the tasks, the contest provides an overview of the state-of-the-art of speech-to-text transcription technologies; the document reports systems performance, computed as Word Error Rate (WER), showing that the current approaches provide effective results. The best system achieves a WER as low as 5.4% on the released testset.

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Author information

Authors and Affiliations

  1. FBK-irst, via Sommarive 18, Povo, TN, 38123, Italy

    Marco Matassoni, Fabio Brugnara & Roberto Gretter

Authors
  1. Marco Matassoni
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  2. Fabio Brugnara
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  3. Roberto Gretter
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Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler, Via Sommarive 18, 38123, Povo, TN, Italy

    Bernardo Magnini

  2. University of Naples, Via Cinthia, 80126, Napoli, NA, Italy

    Francesco Cutugno

  3. Fondazione Ugo Bordoni, Viale del Policlinico, 161, Roma, Italy

    Mauro Falcone

  4. CELCT, Via alla Cascata, 38123, Povo, TN, Italy

    Emanuele Pianta

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Matassoni, M., Brugnara, F., Gretter, R. (2013). Evalita 2011: Automatic Speech Recognition Large Vocabulary Transcription. In: Magnini, B., Cutugno, F., Falcone, M., Pianta, E. (eds) Evaluation of Natural Language and Speech Tools for Italian. EVALITA 2012. Lecture Notes in Computer Science(), vol 7689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35828-9_30

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  • DOI: https://doi.org/10.1007/978-3-642-35828-9_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35827-2

  • Online ISBN: 978-3-642-35828-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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