Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments

Erscheinungsjahr 2024
ISBN: 978-0-443-24856-6
Verlag: Elsevier Science

Buch, Englisch, 280 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 450 g

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.

Autoren/Hrsg.

Zhang, Xiao-Lei

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung

Inhaltsverzeichnis

1. Introduction
2. Fundamentals of Deep Learning
3. Voice Activity Detection
4. Single-Channel Speech Enhancement
5. Multi-Channel Speech Enhancement
6. Multi-Speaker Speech Separation
7. Speaker Recognition
8. Speech Recognition

Über Autor(innen)

Zhang, Xiao-Lei
Xiao-Lei Zhang received his Ph.D. degree with honors from Tsinghua University, China, in 2012. He was a postdoctoral researcher with the Department of Electronic Engineering at Tsinghua University from 2012 to 2014. He was a visiting scholar at The Ohio State University, USA, from 2013 to 2014 and a postdoctoral researcher with the Department of Computer Science and Engineering, The Ohio State University, from 2014 to 2016. Since 2016 he has been a full professor at the Northwestern Polytechnical University, Xi'an, China.

His research interests are the topics in speech processing, machine learning, statistical signal processing, and artificial intelligence.