Primary-Ambient Signal Decomposition and Vector-Based Localization for Spatial Audio Coding and Enhancement

Abstract

Spatial audio coding and enhancement address the growing commercial need to store and distribute multichannel audio and to render content optimally on arbitrary reproduction systems. In this paper, we discuss a spatial analysis-synthesis scheme which applies principal component analysis to an STFT-domain representation of the original audio to separate it into primary and ambient components, which are then respectively analyzed for cues that describe the spatial percept of the audio scene on a per-tile basis; these cues are used by the synthesis to render the audio appropriately on the available playback system. The proposed framework can be tailored for robust spatial audio coding, or it can be applied directly to enhancement scenarios where there are no rate constraints on the intermediate spatial data and audio representation.

Joint Channel Coding Based on Principal Component Analysis

“…The proposed joint channel coding algorithm uses PCA to separate the primary and ambient components [5]. First, it estimates the correlation matrix of the input channels as 11 12…”

“…For practical implementations, sample correlation matrices obtained in frames can be smoothed over several frames [5]. Next, the proposed algorithm calculates the correlation matrix eigenvalues and eigenvectors.…”

Clean Audio for TV broadcast: An Object-Based Approach for Hearing-Impaired Viewers

“…However his research suggested that existing upmixing algorithms either provided inadequate center channel separation or produced "watery sound" or "musical noise" artifacts although formal subjective testing was not applied to assess this thoroughly [51]. In other related work Goodwin and Jot [52] make reference to primary-ambient decomposition in extracting ambient information from stereo signals using principal component analysis (PCA). Other research by Zielinski et al [53] documents principal component analysis (PCA) processing to separate sources for produced media under certain specific conditions.…”

Three-dimensional audio parametric encoding based on perceptual characteristics of spatial cue1

“…This frame is applicable in robustness of spatial audio parameter coding and in the enhancement of certain scenes or sound effects [13].…”