Parametric coding of stereo audio

Parametric-stereo coding is a technique to efficiently code a stereo audio signal as a monaural signal plus a small amount of parametric overhead to describe the stereo image. The stereo properties are analyzed, encoded, and reinstated in a decoder according to spatial psychoacoustical principles. The monaural signal can be encoded using any (conventional) audio coder. Experiments show that the parameterized description of spatial properties enables a highly efficient, high-quality stereo audio representation

Parametric first-order ambisonic decoding for headphones utilising the cross-pattern coherence algorithm

International audienceRegarding the reproduction of recorded or synthesised spatial sound scenes, perhaps the most convenient and flexible approach is to employ the Ambisonics framework. The Ambisonics framework allows for linear and non-parametric storage, manipulation and reproduction of sound-fields, described using spherical harmonics up to a given order of expansion. Binaural Ambisonic reproduction can be realised by matching the spherical harmonic patterns to a set of binaural filters, in manner which is frequency-dependent, linear and time-invariant. However, the perceptual performance of this approach is largely dependent on the spatial resolution of the input format. When employing lower-order material as input, perceptual deficiencies may easily occur, such as poor localisation accuracy and colouration. This is especially problematic, as the vast majority of existing Ambisonic recordings are often made available as first-order only. The detrimental effects associated with lower-order Ambisonics reproduction have been well studied and documented. To improve upon the perceived spatial accuracy of the method, the simplest solution is to increase the spherical harmonic order at the recording stage. However, microphone arrays capable of capturing higher-order components, are generally much more expensive than first-order arrays; while more affordable options tend to offer higher-order components only at limited frequency ranges. Additionally, an increase in spherical harmonic order also requires an increase in the number of channels and storage, and in the case of transmission, more bandwidth is needed. Furthermore, it is important to note that this solution does not aid in the reproduction of existing lower-order recordings. It is for these reasons that this work focuses on alternative methods which improve the reproduction of first-order material for headphone playback. For the task of binaural sound-field reproduction, an alternative is to employ a parametric approach, which divides the sound-field decoding into analysis and synthesis stages. Unlike Ambisonic reproduction, which operates via a linear combination of the input signals, parametric approaches operate in the time-frequency domain and rely on the extraction of spatial parameters during their analysis stage. These spatial parameters are then utilised to conduct a more informed reproduction in the synthesis stage. Parametric methods are capable of reproducing sounds at a spatial resolution that far exceeds their linear and time-invariant counterparts, as they are not bounded by the resolution of the input format. For example, they can elect to directly convolve the analysed source signals with Head-Related Transfer Functions (HRTF), which correspond to their analysed directions. An infinite order of spherical harmonic components would be required to attain the same resolution with a binaural Ambisonic decoder. The most well-known and established parametric reproduction method is Directional Audio Coding (DirAC), which employs a sound-field model consisting of one plane-wave and one diffuseness estimate per time-frequency tile. These parameters are derived from the active-intensity vector, in the case of first-order input. More recent formulations allow for multiple plane-wave and diffuseness estimates via spatially-localised active-intensity vectors, using higher-order input. Another parametric method is High Angular Resolution plane-wave Expansion (HARPEX), which extracts two plane-waves per frequency and is first-order only. The Sparse-Recovery method extracts a number of plane-waves, which corresponds to up to half the number of input channels of arbitrary order. The COding and Multi-Parameterisation of Ambisonic Sound Scenes (COMPASS) method also extracts source components up to half the number of input channels, but employs an additional residual stream that encapsulates the remaining diffuse and ambient components in the scene. In this paper, a new binaural parametric decoder for first-order input is proposed. The method employs a sound-field model of one plane-wave and one diffuseness estimate per frequency, much like the DirAC model. However, the source component directions are identified via a plane-wave decomposition using a dense scanning grid and peak-finding, which is shown to be more robust than the active-intensity vector for multiple narrow-band sources. The source and ambient components per time-frequency tile are then segregated, and their relative energetic contributions are established, using the Cross-Pattern Coherence (CroPaC) spatial-filter. This approach is shown to be more robust than deriving this energy information from the active-intensity-based diffuseness estimates. A real-time audio plug-in implementation of the proposed approach is also described.A multiple-stimulus listening test was conducted to evaluate the perceived spatial accuracy and fidelity of the proposed method, alongside both first-order and third-order Ambisonics reproduction. The listening test results indicate that the proposed parametric decoder, using only first-order signals, is capable of delivering perceptual accuracy that matches or surpasses that of third-order ambisonics decoding

Reviews on Technology and Standard of Spatial Audio Coding

Market  demands  on a more impressive entertainment media have motivated for delivery of three dimensional  (3D) audio content to  home consumers  through Ultra  High  Definition  TV  (UHDTV), the next generation of TV broadcasting, where spatial  audio  coding plays  fundamental role. This paper reviews fundamental concept on spatial audio coding which includes technology, standard, and application. Basic principle of object-based audio reproduction system  will also be elaborated, compared  to  the  traditional channel-based system, to provide good understanding on this popular interactive audio reproduction system which gives end users flexibility to render  their  own preferred  audio composition.Keywords : spatial audio, audio coding, multi-channel audio signals, MPEG standard, object-based audi

Real-time Microphone Array Processing for Sound-field Analysis and Perceptually Motivated Reproduction

This thesis details real-time implementations of sound-field analysis and perceptually motivated reproduction methods for visualisation and auralisation purposes. For the former, various methods for visualising the relative distribution of sound energy from one point in space are investigated and contrasted; including a novel reformulation of the cross-pattern coherence (CroPaC) algorithm, which integrates a new side-lobe suppression technique. Whereas for auralisation applications, listening tests were conducted to compare ambisonics reproduction with a novel headphone formulation of the directional audio coding (DirAC) method. The results indicate that the side-lobe suppressed CroPaC method offers greater spatial selectivity in reverberant conditions compared with other popular approaches, and that the new DirAC formulation yields higher perceived spatial accuracy when compared to the ambisonics method

EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis

Data clustering has received a lot of attention and numerous methods, algorithms and software packages are available. Among these techniques, parametric finite-mixture models play a central role due to their interesting mathematical properties and to the existence of maximum-likelihood estimators based on expectation-maximization (EM). In this paper we propose a new mixture model that associates a weight with each observed point. We introduce the weighted-data Gaussian mixture and we derive two EM algorithms. The first one considers a fixed weight for each observation. The second one treats each weight as a random variable following a gamma distribution. We propose a model selection method based on a minimum message length criterion, provide a weight initialization strategy, and validate the proposed algorithms by comparing them with several state of the art parametric and non-parametric clustering techniques. We also demonstrate the effectiveness and robustness of the proposed clustering technique in the presence of heterogeneous data, namely audio-visual scene analysis.Comment: 14 pages, 4 figures, 4 table

Proceedings of the EAA Spatial Audio Signal Processing symposium: SASP 2019

International audienc

Improved Time Delay Analysis/Synthesis for Parametric Stereo Audio Coding

For parametric stereo and multi-channel audio coding, it has been proposed to use level difference, time difference, and coherence cues between audio channels to represent the perceptual spatial features of stereo and multi-channel audio signals. In practice, it has turned out that by merely considering level difference and coherence cues a high audio quality can already be achieved. Time difference cue analysis/synthesis did not contribute much to a higher audio quality, or, even decreases audio quality when not done properly. However, for binaural audio signals, e.g. binaural recordings or signals mixed with HRTFs, time differences play an important role. We investigate problems of time difference analysis/synthesis with such critical signals and propose algorithms for improving it. A subjective evalution indicates significant improvements over previous time difference analysis/synthesis