Automatic Speech Recognition A Deep Learning Approach /

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 approa...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Yu, Dong (Author), Deng, Li (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: London : Springer London : Imprint: Springer, 2015.
Edition:1st ed. 2015.
Series:Signals and Communication Technology,
Subjects:
Signal processing.
Acoustical engineering.
Social sciences-Data processing.
Signal, Speech and Image Processing .
Engineering Acoustics.
Computer Application in Social and Behavioral Sciences.
Online Access:Texto Completo
Table of Contents:
  • Section 1: Automatic speech recognition: Background
  • Feature extraction: basic frontend
  • Acoustic model: Gaussian mixture hidden Markov model
  • Language model: stochastic N-gram
  • Historical reviews of speech recognition research: 1st, 2nd, 3rd, 3.5th, and 4th generations
  • Section 2: Advanced feature extraction and transformation
  • Unsupervised feature extraction
  • Discriminative feature transformation
  • Section 3: Advanced acoustic modeling
  • Conditional random field (CRF) and hidden conditional random field (HCRF)
  • Deep-Structured CRF
  • Semi-Markov conditional random field
  • Deep stacking models
  • Deep neural network - hidden Markov hybrid model
  • Section 4: Advanced language modeling
  • Discriminative Language model
  • Log-linear language model
  • Neural network language model.

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