A Study of Automatic Speech Recognition in Noisy Classroom Environments for Automated Dialog Analysis

  • Nathaniel Blanchard
  • Michael Brady
  • Andrew M. Olney
  • Marci Glaus
  • Xiaoyi Sun
  • Martin Nystrand
  • Borhan Samei
  • Sean Kelly
  • Sidney D’Mello
Conference paper

DOI: 10.1007/978-3-319-19773-9_3

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9112)
Cite this paper as:
Blanchard N. et al. (2015) A Study of Automatic Speech Recognition in Noisy Classroom Environments for Automated Dialog Analysis. In: Conati C., Heffernan N., Mitrovic A., Verdejo M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science, vol 9112. Springer, Cham

Abstract

The development of large-scale automatic classroom dialog analysis systems requires accurate speech-to-text translation. A variety of automatic speech recognition (ASR) engines were evaluated for this purpose. Recordings of teachers in noisy classrooms were used for testing. In comparing ASR results, Google Speech and Bing Speech were more accurate with word accuracy scores of 0.56 for Google and 0.52 for Bing compared to 0.41 for AT&T Watson, 0.08 for Microsoft, 0.14 for Sphinx with the HUB4 model, and 0.00 for Sphinx with the WSJ model. Further analysis revealed both Google and Bing engines were largely unaffected by speakers, speech class sessions, and speech characteristics. Bing results were validated across speakers in a laboratory study, and a method of improving Bing results is presented. Results provide a useful understanding of the capabilities of contemporary ASR engines in noisy classroom environments. Results also highlight a list of issues to be aware of when selecting an ASR engine for difficult speech recognition tasks.

Keywords

Google Speech Bing Speech Sphinx 4 Microsoft Speech ASR engine evaluation 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nathaniel Blanchard
    • 1
  • Michael Brady
    • 1
  • Andrew M. Olney
    • 2
  • Marci Glaus
    • 3
  • Xiaoyi Sun
    • 3
  • Martin Nystrand
    • 3
  • Borhan Samei
    • 2
  • Sean Kelly
    • 4
  • Sidney D’Mello
    • 1
  1. 1.University of Notre DameNotre DameUSA
  2. 2.University of MemphisMemphisUSA
  3. 3.University of Wisconsin-MadisonMadisonUSA
  4. 4.University of PittsburghPittsburghUSA

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