Spatial Audio Reproduction with Primary Ambient Extraction

This book first introduces the background of spatial audio reproduction, with different types of audio content and for different types of playback systems. A literature study on the classical and emerging Primary Ambient Extraction (PAE) techniques is presented. The emerging techniques aim to improve the extraction performance and also enhance the robustness of PAE approaches in dealing with more complex signals encountered in practice. The in-depth theoretical study helps readers to understand the rationales behind these approaches. Extensive objective and subjective experiments validate the feasibility of applying PAE in spatial audio reproduction systems. These experimental results, together with some representative audio examples and MATLAB codes of the key algorithms, illustrate clearly the differences among various approaches and also help readers gain insights on selecting different approaches for different applications.

Reviews exhaustively the key recent research into spatial audio reproduction systems Includes experimental results, together with some representative audio examples and MATLAB codes of the key algorithms Provides readers with insights on selecting different approaches for different applications in spatial audio reproduction Includes supplementary material: sn.pub/extras

Auteur

Jianjun He is currently pursuing his Ph.D. degree in electrical and electronic engineering at Nanyang Technological University (NTU), Singapore. In 2011, he was working in Nanjing International Center of Entrepreneurs (NICE), building platforms for start-ups from oversea Chinese scholars. Since 2015, he has been a project officer with School of Electrical and Electronic Engineering in NTU. His research interests include audio and acoustic signal processing, 3D audio (spatial audio), psychoacoustics, active noise control, source separation, and emerging audio and speech applications.

Contenu

Introduction.- Literature Review on Spatial Audio.- Linear Estimation based Primary Ambient Extraction.- Ambient Spectrum Estimation based Primary Ambient Extraction.- Time-Shifting based Primary Ambient Extraction.- Multiple Source based Primary Ambient Extraction.- Conclusion.