Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81370
Title: Primary-Ambient Extraction Using Ambient Spectrum Estimation for Immersive Spatial Audio Reproduction
Authors: He, Jianjun
Gan, Woon-Seng
Tan, Ee-Leng
Keywords: Ambient spectrum estimation (ASE)
Computational efficiency
Primary-ambient extraction (PAE)
Sparsity
Spatial audio
Issue Date: 2015
Source: He, J., Gan, W.-S., & Tan, E.-L. (2015). Primary-Ambient Extraction Using Ambient Spectrum Estimation for Immersive Spatial Audio Reproduction. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 23(9), 1431-1444.
Series/Report no.: IEEE/ACM Transactions on Audio, Speech, and Language Processing
Abstract: The diversity of today’s playback systems requires a flexible, efficient, and immersive reproduction of sound scenes in digital media. Spatial audio reproduction based on primary-ambient extraction (PAE) fulfills this objective, where accurate extraction of primary and ambient components from sound mixtures in channel-based audio is crucial. Severe extraction error was found in existing PAE approaches when dealing with sound mixtures that contain a relatively strong ambient component, a commonly encountered case in the sound scenes of digital media. In this paper, we propose a novel ambient spectrum estimation (ASE) framework to improve the performance of PAE. The ASE framework exploits the equal magnitude of the uncorrelated ambient components in two channels of a stereo signal, and reformulates the PAE problem into the problem of estimating either ambient phase or magnitude. In particular, we take advantage of the sparse characteristic of the primary components to derive sparse solutions for ASE based PAE, together with an approximate solution that can significantly reduce the computational cost. Our objective and subjective experimental results demonstrate that the proposed ASE approaches significantly outperform existing approaches, especially when the ambient component is relatively strong.
URI: https://hdl.handle.net/10356/81370
http://hdl.handle.net/10220/39537
ISSN: 2329-9290
DOI: 10.1109/TASLP.2015.2434272
Rights: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TASLP.2015.2434272].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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