A primer on deep learning architectures and applications in speech processing

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

Research output: Contribution to journalReview article

4 Citations (Scopus)


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
Pages (from-to)3406–3432
JournalCircuits, Systems, and Signal Processing
Issue number8
Publication statusPublished - Aug 2019


Cite this