Automatic Speech Recognition

A Deep Learning Approach

  • Dong Yu
  • Li Deng

Part of the Signals and Communication Technology book series (SCT)

Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Dong Yu, Li Deng
    Pages 1-9
  3. Conventional Acoustic Models

    1. Front Matter
      Pages 11-11
    2. Dong Yu, Li Deng
      Pages 13-21
    3. Dong Yu, Li Deng
      Pages 23-54
  4. Deep Neural Networks

    1. Front Matter
      Pages 55-55
    2. Dong Yu, Li Deng
      Pages 57-77
    3. Dong Yu, Li Deng
      Pages 79-95
  5. Deep Neural Network-Hidden Markov Model Hybrid Systems for Automatic Speech Recognition

    1. Front Matter
      Pages 97-97
    2. Dong Yu, Li Deng
      Pages 117-136
  6. Representation Learning in Deep Neural Networks

    1. Front Matter
      Pages 155-155
    2. Dong Yu, Li Deng
      Pages 193-215
  7. Advanced Deep Models

    1. Front Matter
      Pages 217-217
    2. Dong Yu, Li Deng
      Pages 237-266
    3. Dong Yu, Li Deng
      Pages 267-298

About this book

Introduction

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.

Keywords

Adaptive Training Automatic Speech Recognition Computational Network Deep Generative Model Deep Learning Deep Neural Network Distributed Representation Full-Sequence Training Hidden Markov Model LSTM Recurrent Neural Network Transfer Learning

Authors and affiliations

  • Dong Yu
    • 1
  • Li Deng
    • 2
  1. 1.Microsoft ResearchBothellUSA
  2. 2.Microsoft ResearchRedmondUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-5779-3
  • Copyright Information Springer-Verlag London 2015
  • Publisher Name Springer, London
  • eBook Packages Engineering
  • Print ISBN 978-1-4471-5778-6
  • Online ISBN 978-1-4471-5779-3
  • Series Print ISSN 1860-4862
  • Series Online ISSN 1860-4870
  • About this book