Perception-Based Reproduction of Spatial Sound With Directional Audio Coding

Pulkki, Ville; Laitinen, Mikko-Ville; Vilkamo, Juha; Ahonen, Jukka; Lokki, Tapio; Pihlajamäki, Tapani

doi:10.1142/9789814299312_0026

Cited by 120 publications

(216 citation statements)

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“…SIRR [15] (which underpins the analysis and synthesis in directional audio coding (DirAC) [39]) is an alternative framework for analyzing, encoding, and synthezing a spatial RIR. The analysis part is based on a B-Format or higher-order recording [40], and represents the timefrequency-wise spatial response using three parameters: the DOA (azimuth and elevation) and a diffuseness coefficient.…”

Section: Low-level Parameters and Synthesismentioning

confidence: 99%

Object-Based Reverberation for Spatial Audio

Coleman¹,

Franck²,

Jackson³

et al. 2017

J. Audio Eng. Soc.

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Object-based audio is gaining momentum as a means for future audio content to be more immersive, interactive, and accessible. Recent standardization developments make recommendations for object formats; however, the capture, production, and reproduction of reverberation is an open issue. In this paper parametric approaches for capturing, representing, editing, and rendering reverberation over a 3D spatial audio system are reviewed. A framework is proposed for a Reverberant Spatial Audio Object (RSAO), which synthesizes reverberation inside an audio object renderer. An implementation example of an object scheme utilizing the RSAO framework is provided, and supported with listening test results, showing that: the approach correctly retains the sense of room size compared to a convolved reference; editing RSAO parameters can alter the perceived room size and source distance; and, format-agnostic rendering can be exploited to alter listener envelopment.

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Section: Low-level Parameters and Synthesismentioning

confidence: 99%

Object-Based Reverberation for Spatial Audio

Coleman¹,

Franck²,

Jackson³

et al. 2017

J. Audio Eng. Soc.

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“…The filters each used 2048 taps and were designed using hamming windows. Estimate direction of arrival (DOA) estimates to be used as features were extracted from each band using directional audio coding (DirAC) analysis [35][36][37] as follows:…”

Section: Baseline Classificationmentioning

confidence: 99%

EigenScape: A Database of Spatial Acoustic Scene Recordings

Green

Murphy

2017

Applied Sciences

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Abstract:The classification of acoustic scenes and events is an emerging area of research in the field of machine listening. Most of the research conducted so far uses spectral features extracted from monaural or stereophonic audio rather than spatial features extracted from multichannel recordings. This is partly due to the lack thus far of a substantial body of spatial recordings of acoustic scenes. This paper formally introduces EigenScape, a new database of fourth-order Ambisonic recordings of eight different acoustic scene classes. The potential applications of a spatial machine listening system are discussed before detailed information on the recording process and dataset are provided. A baseline spatial classification system using directional audio coding (DirAC) techniques is detailed and results from this classifier are presented. The classifier is shown to give good overall scene classification accuracy across the dataset, with 7 of 8 scenes being classified with an accuracy of greater than 60% with an 11% improvement in overall accuracy compared to use of Mel-frequency cepstral coefficient (MFCC) features. Further analysis of the results shows potential improvements to the classifier. It is concluded that the results validate the new database and show that spatial features can characterise acoustic scenes and as such are worthy of further investigation.

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“…Problems become more significant if signal processing includes directional sound encoding and rendering, synthesizing and dynamic controlling of reverberation, room and distance effects. Several software applications have been recently developed to address this problem for various platforms such as Spat [112], Sound Lab (SLAB) [113], DirAC [114], etc.…”

Section: Latency and Memory Usagementioning

confidence: 99%

A Survey on Hardware and Software Solutions for Multimodal Wearable Assistive Devices Targeting the Visually Impaired

2016

APH

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Perception-Based Reproduction of Spatial Sound With Directional Audio Coding

Cited by 120 publications

References 1 publication

Object-Based Reverberation for Spatial Audio

Object-Based Reverberation for Spatial Audio

EigenScape: A Database of Spatial Acoustic Scene Recordings

A Survey on Hardware and Software Solutions for Multimodal Wearable Assistive Devices Targeting the Visually Impaired

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