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“Google” Lithuanian Speech Recognition Efficiency Evaluation Research

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Information and Software Technologies (ICIST 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 639))

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Abstract

This paper presents “Google” Lithuanian speech recognition efficiency evaluation research. For the experiment it was chosen method that consists of three parts: (1) to process all voice records without adding any noise; (2) process all voice records with several different types of noise, modified so as to get some predefined signal-to-noise ratio (SNR); (3) after one month reprocess all voice records without any additional noise and to assess improvements in the quality of the speech recognition. It was chosen WER metrics for speech recognition quality assessment. Analyzing the results of the experiment it was observed that the greatest impact on the quality of speech recognition has a SNR and speech type (most recognizable is isolated words, the worst - spontaneous speech). Meanwhile, characteristics such as the gender of the speaker, smooth speech, speech speed, speech volume does not make any significant influence on speech recognition quality.

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Notes

  1. 1.

    The standard deviation is a numerical value used to indicate how widely individuals in a group vary. If individual observations vary greatly from the group mean, the standard deviation is big; and vice versa.

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Author information

Authors and Affiliations

  1. Department of Multimedia Engeneering, Kaunas University of Technology, Studentu St. 50, 51368, Kaunas, Lithuania

    Donatas Sipavičius & Rytis Maskeliūnas

Authors
  1. Donatas Sipavičius
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  2. Rytis Maskeliūnas
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Correspondence to Donatas Sipavičius .

Editor information

Editors and Affiliations

  1. Kaunas University of Technology , Kaunas, Lithuania

    Giedre Dregvaite

  2. Kaunas University of Technology , Kaunas, Lithuania

    Robertas Damasevicius

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Sipavičius, D., Maskeliūnas, R. (2016). “Google” Lithuanian Speech Recognition Efficiency Evaluation Research. In: Dregvaite, G., Damasevicius, R. (eds) Information and Software Technologies. ICIST 2016. Communications in Computer and Information Science, vol 639. Springer, Cham. https://doi.org/10.1007/978-3-319-46254-7_49

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  • DOI: https://doi.org/10.1007/978-3-319-46254-7_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46253-0

  • Online ISBN: 978-3-319-46254-7

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