Automatic Speech Recognition A Deep Learning Approach /

• Main Authors: Yu, Dong (Author), Deng, Li (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London : Imprint: Springer, 2015.
• Series: Signals and Communication Technology,
• Subjects: Engineering.; Application software.; Acoustical engineering.; Signal, Image and Speech Processing.; Engineering Acoustics.; Computer Appl. in Social and Behavioral Sciences.

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...

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.