Automatic Speech Recognition A Deep Learning Approach /

• Κύριοι συγγραφείς: Yu, Dong (Συγγραφέας), Deng, Li (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: London : Springer London : Imprint: Springer, 2015.
• Σειρά: Signals and Communication Technology,
• Θέματα: 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...

Πίνακας περιεχομένων:

• 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.