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Small and Large Vocabulary Speech Recognition of MP3 Data under Real-Word Conditions: Experimental Study

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E-Business and Telecommunications (ICETE 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 314))

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Abstract

This paper presents the study of speech recognition accuracy both for small and large vocabulary task with respect to different levels of MP3 compression of processed data. The motivation behind the work was to evaluate the usage of ASR system for off-line automatic transcription of recordings collected from standard present MP3 devices under different levels of background noise and channel distortion. Although MP3 may not be an optimal compression algorithm, the performed experiments have prooved that it does not distort speech signal significantly for higher compression rates. Realized experiments showed also that the accuracy of speech recognition (both small- and large-vocabulary) decreased very slowly for the bit-rate of 24 kbps and higher. However, slightly different setup of speech feature computation is necessary for MP3 speech data, mainly PLP features give significantly better results in comparison to MFCC.

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Authors and Affiliations

  1. Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, 166 27, Prague, Czech Republic

    Petr Pollak & Michal Borsky

Authors
  1. Petr Pollak
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  2. Michal Borsky
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Editors and Affiliations

  1. Department of Computer Science, Monmouth University, 07764, West Long Branch, NJ, U.S.A.

    Mohammad S. Obaidat

  2. University of Seville, C/S. Fernando, 4, C.P. 41004, Sevilla, Spain

    José L. Sevillano

  3. Departament of Systems and Informatics, Polytechnic Institute of Setúbal – INSTICC, Rua do Vale de Chaves - Estefanilha, 2910-761, Setúbal, Portugal

    Joaquim Filipe

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Pollak, P., Borsky, M. (2012). Small and Large Vocabulary Speech Recognition of MP3 Data under Real-Word Conditions: Experimental Study. In: Obaidat, M.S., Sevillano, J.L., Filipe, J. (eds) E-Business and Telecommunications. ICETE 2011. Communications in Computer and Information Science, vol 314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35755-8_29

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  • DOI: https://doi.org/10.1007/978-3-642-35755-8_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35754-1

  • Online ISBN: 978-3-642-35755-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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