Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments provides a detailed discussion of deep learning-based robust speech processing and its applications. The book begins by looking at the basics of deep learning and common deep network models, followed by front-end algorithms for deep learning-based speech denoising, speech detection, single-channel speech enhancement multi-channel speech enhancement, multi-speaker speech separation, and the applications of deep learning-based speech denoising in speaker verification and speech recognition.
1. Chapter 1: Introduction of the book - p. 1 2. Chapter 2: Fundamentals of deep learning - p. 7 3. Chapter 3: Voice activity detection - p. 59 4. Chapter 4: Single-channel speech enhancement - p. 85 5. Chapter 5: Multichannel speech enhancement - p. 121 6. Chapter 6: Multispeaker speech separation - p. 149 7. Chapter 7: Speaker recognition - p. 171 8. Chapter 8: Speech recognition - p. 213 9. References - p. 247 10. Index - p. 263
Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments provides a detailed discussion of deep learning-based robust speech processing and its applications. The book begins by looking at the basics of deep learning and common deep network models, followed by front-end algorithms for deep learning-based speech denoising, speech detection, single-channel speech enhancement multi-channel speech enhancement, multi-speaker speech separation, and the applications of deep learning-based speech denoising in speaker verification and speech recognition.
1. Chapter 1: Introduction of the book - p. 1 2. Chapter 2: Fundamentals of deep learning - p. 7 3. Chapter 3: Voice activity detection - p. 59 4. Chapter 4: Single-channel speech enhancement - p. 85 5. Chapter 5: Multichannel speech enhancement - p. 121 6. Chapter 6: Multispeaker speech separation - p. 149 7. Chapter 7: Speaker recognition - p. 171 8. Chapter 8: Speech recognition - p. 213 9. References - p. 247 10. Index - p. 263
