Long, Deep and Wide Artificial Neural Nets for Dealing with Unexpected Noise in Machine Recognition of Speech

  • Hynek Hermansky
Conference paper

DOI: 10.1007/978-3-642-40585-3_2

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8082)
Cite this paper as:
Hermansky H. (2013) Long, Deep and Wide Artificial Neural Nets for Dealing with Unexpected Noise in Machine Recognition of Speech. In: Habernal I., Matoušek V. (eds) Text, Speech, and Dialogue. TSD 2013. Lecture Notes in Computer Science, vol 8082. Springer, Berlin, Heidelberg

Abstract

Most emphasis in current deep learning artificial neural network based automatic recognition of speech is put on deep net architectures with multiple sequential levels of processing. . The current work argues that benefits can be also seen in expanding the nets longer in temporal direction, and wider into multiple parallel processing streams.

Keywords

artificial neural networks machine recognition of speech robustness to noise unexpected distortions parallel processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hynek Hermansky
    • 1
  1. 1.Center for Language and Speech ProcessingThe Johns Hopkins UniversityBaltimoreUSA

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