A Primer on Deep Learning Architectures and Applications in Speech Processing

Tokunbo Ogunfunmi, Ravi Ramachandran, Roberto Togneri, Yuanjun Zhao, Xianjun Xia

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)3406-3432
Number of pages27
JournalCircuits, Systems, and Signal Processing
Volume38
Issue number8
DOIs
StatePublished - Aug 15 2019

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Applied Mathematics

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