A Primer on Deep Learning Architectures and Applications in Speech Processing

  • Tokunbo OgunfunmiEmail author
  • Ravi Prakash Ramachandran
  • Roberto Togneri
  • Yuanjun Zhao
  • Xianjun Xia


In the recent past years, deep-learning-based machine learning methods have demonstrated remarkable success for a wide range of learning tasks in multiple domains. They are suitable for complex classification and regression problems in applications such as computer vision, speech recognition and other pattern analysis branches. The purpose of this article is to contribute a timely review and introduction of state-of-the-art and popular discriminative DNN, CNN and RNN deep learning techniques, the basic framework and algorithms, hardware implementations, applications in speech, and the overall benefits of deep learning.


Deep learning Signal processing Discriminative algorithms 



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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Tokunbo Ogunfunmi
    • 1
    Email author
  • Ravi Prakash Ramachandran
    • 2
  • Roberto Togneri
    • 3
  • Yuanjun Zhao
    • 3
  • Xianjun Xia
    • 3
  1. 1.Department of Electrical EngineeringSanta Clara UniversitySanta ClaraUSA
  2. 2.Department of Electrical and Computer EngineeringRowan UniversityGlassboroUSA
  3. 3.Department of EEC EngineeringThe University of Western AustraliaPerthAustralia

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