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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Springer London : Imprint: Springer,
2015.
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| Edición: | 1st ed. 2015. |
| Colección: | Signals and Communication Technology,
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| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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.