Spatial Audio Processing: MPEG Surround and Other Applications
Spatial Audio Processing: MPEG Surround and Other Applications
Enhancement of Spatial Sound Quality: A New Reverberation-Extraction Audio Upmixer
IEEE Transactions on Audio, Speech, and Language Processing
Performance measurement in blind audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
Parametric multichannel audio coding: synthesis of coherence cues
IEEE Transactions on Audio, Speech, and Language Processing
Phantom Materialization: A Novel Method to Enhance Stereo Audio Reproduction on Headphones
IEEE Transactions on Audio, Speech, and Language Processing
Blind Extraction of Dominant Target Sources Using ICA and Time-Frequency Masking
IEEE Transactions on Audio, Speech, and Language Processing
Upmixing and Downmixing Two-channel Stereo Audio for Consumer Electronics
IEEE Transactions on Consumer Electronics
Binaural Noise Reduction in the Time Domain With a Stereo Setup
IEEE Transactions on Audio, Speech, and Language Processing
Enhanced Principal Component Using Polar Coordinate PCA for Stereo Audio Coding
ICME '12 Proceedings of the 2012 IEEE International Conference on Multimedia and Expo
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Audio signals for moving pictures and video games are often linear combinations of primary and ambient components. In spatial audio analysis-synthesis, these mixed signals are usually decomposed into primary and ambient components to facilitate flexible spatial rendering and enhancement. Existing approaches such as principal component analysis (PCA) and least squares (LS) are widely used to perform this decomposition from stereo signals. However, the performance of these approaches in primary-ambient extraction (PAE) has not been well studied and no comparative analysis among the existing approaches has been carried out so far. In this paper, we generalize the existing approaches into a linear estimation framework. Under this framework, we propose a series of performance measures to identify the components that contribute to the extraction error. Based on the generalized linear estimation framework and our proposed performance measures, a comparative study and experimental testing of the linear estimation based PAE approaches including existing PCA, LS, and three proposed variant LS approaches are presented.