Time-shifting based primary-ambient extraction for spatial audio reproduction
One of the key issues in spatial audio analysis and reproduction is to decompose a signal into primary and ambient components based on their directional and diffuse spatial features, respectively. Existing approaches employed in primary-ambient extraction (PAE), such as principal component analysis...
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sg-ntu-dr.10356-813652020-03-07T13:57:25Z Time-shifting based primary-ambient extraction for spatial audio reproduction He, Jianjun Gan, Woon-Seng Tan, Ee-Leng School of Electrical and Electronic Engineering Primary-ambient extraction (PAE) Principal component analysis (PCA) Spatial audio Spatial cues One of the key issues in spatial audio analysis and reproduction is to decompose a signal into primary and ambient components based on their directional and diffuse spatial features, respectively. Existing approaches employed in primary-ambient extraction (PAE), such as principal component analysis (PCA), are mainly based on a basic stereo signal model. The performance of these PAE approaches has not been well studied for the input signals that do not satisfy all the assumptions of the stereo signal model. In practice, one such case commonly encountered is that the primary components of the stereo signal are partially correlated at zero lag, referred to as the primary-complex case. In this paper, we take PCA as a representative of existing PAE approaches and investigate the performance degradation of PAE with respect to the correlation of the primary components in the primary-complex case. A time-shifting technique is proposed in PAE to alleviate the performance degradation due to the low correlation of the primary components in such stereo signals. This technique involves time-shifting the input signal according to the estimated inter-channel time difference of the primary component prior to the signal decomposition using conventional PAE approaches. To avoid the switching artifacts caused by the varied time-shifting in successive time frames, overlapped output mapping is suggested. Based on the results from our experiments, PAE approaches with the proposed time-shifting technique are found to be superior to the conventional PAE approaches in terms of extraction accuracy and spatial accuracy. Accepted version 2016-01-04T06:11:59Z 2019-12-06T14:29:21Z 2016-01-04T06:11:59Z 2019-12-06T14:29:21Z 2015 Journal Article He, J., Gan, W.-S., & Tan, E.-L. (2015). Time-Shifting Based Primary-Ambient Extraction for Spatial Audio Reproduction. IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 23(10), 1576-1588. 2329-9290 https://hdl.handle.net/10356/81365 http://hdl.handle.net/10220/39538 10.1109/TASLP.2015.2439577 en IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) © 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.2015.2439577]. 35 p. application/pdf |
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Primary-ambient extraction (PAE) Principal component analysis (PCA) Spatial audio Spatial cues |
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Primary-ambient extraction (PAE) Principal component analysis (PCA) Spatial audio Spatial cues He, Jianjun Gan, Woon-Seng Tan, Ee-Leng Time-shifting based primary-ambient extraction for spatial audio reproduction |
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One of the key issues in spatial audio analysis and reproduction is to decompose a signal into primary and ambient components based on their directional and diffuse spatial features, respectively. Existing approaches employed in primary-ambient extraction (PAE), such as principal component analysis (PCA), are mainly based on a basic stereo signal model. The performance of these PAE approaches has not been well studied for the input signals that do not satisfy all the assumptions of the stereo signal model. In practice, one such case commonly encountered is that the primary components of the stereo signal are partially correlated at zero lag, referred to as the primary-complex case. In this paper, we take PCA as a representative of existing PAE approaches and investigate the performance degradation of PAE with respect to the correlation of the primary components in the primary-complex case. A time-shifting technique is proposed in PAE to alleviate the performance degradation due to the low correlation of the primary components in such stereo signals. This technique involves time-shifting the input signal according to the estimated inter-channel time difference of the primary component prior to the signal decomposition using conventional PAE approaches. To avoid the switching artifacts caused by the varied time-shifting in successive time frames, overlapped output mapping is suggested. Based on the results from our experiments, PAE approaches with the proposed time-shifting technique are found to be superior to the conventional PAE approaches in terms of extraction accuracy and spatial accuracy. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering He, Jianjun Gan, Woon-Seng Tan, Ee-Leng |
format |
Article |
author |
He, Jianjun Gan, Woon-Seng Tan, Ee-Leng |
author_sort |
He, Jianjun |
title |
Time-shifting based primary-ambient extraction for spatial audio reproduction |
title_short |
Time-shifting based primary-ambient extraction for spatial audio reproduction |
title_full |
Time-shifting based primary-ambient extraction for spatial audio reproduction |
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Time-shifting based primary-ambient extraction for spatial audio reproduction |
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Time-shifting based primary-ambient extraction for spatial audio reproduction |
title_sort |
time-shifting based primary-ambient extraction for spatial audio reproduction |
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2016 |
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https://hdl.handle.net/10356/81365 http://hdl.handle.net/10220/39538 |
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1681039192971280384 |