Sector-Based Parametric Sound Field Reproduction in the Spherical Harmonic Domain

Politis, Archontis; Vilkamo, Juha; Pulkki, Ville

doi:10.1109/jstsp.2015.2415762

Cited by 49 publications

(51 citation statements)

References 22 publications

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“…The active-intensity vector expresses the mean flow of energy due to the effect of all sources and multi-path contributions in the sound scene, and has been extensively used for spatial sound reproduction [15,16], and for localisation of dominant sound sources, through the analysis of its directional statistics [17,18]. The notion of an intensity vector due to contributions in a spatially-localised region of the sound-field was introduced in [11]. It is expressed by the product of the acoustic pressure and acoustic particle velocity, due to a sound-field weighted by a desired beampattern c(γ 0 , γ)…”

Section: Spatially-localised Acoustic Intensitymentioning

confidence: 99%

“…In the trivial case of a single plane wave source in the scene, all re-assignment DoAs will point to the source direction, independently of the beamforming direction, and hence all SRP powers are combined at the same point [11]. For a proper power preservation in this case, and assuming a uniformly arranged set of PWD/SRP directions, the beamformers should be normalised with the energy-preserving condition…”

Section: Directional Re-assignment-based Srpmentioning

confidence: 99%

“…The re-assigned DoA is based on a spatially weighted acoustic intensity vector, which expresses propagating energy flow due to waves incident around the beamforming direction. Such a spatially-localised intensity vector was first used for directional analysis and sound-field reproduction in [11], and further formulated in [12,13]. Recently, it has been used for DoA estimation using a histogram-clustering approach [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sharpening of Angular Spectra Based on a Directional Re-assignment Approach for Ambisonic Sound-field Visualisation

McCormack

Politis

Pulkki

2019

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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A method for computing and sharpening angular spectra, derived from low-order ambisonic signals, is presented in this paper, which is intended for high-resolution directional sound-field visualisation. The method relies on a re-assignment principle, whereby the directional energy for each grid point is assigned to a new direction, which corresponds to a direction-of-arrival (DoA) estimate within a spatially-localised region, centred around the respective grid point. This leads to the concentration of energy around the true sources, and hence, to sharper angular spectra than that of steered response power (SRP) beamformers of maximum directivity, with the same order of ambisonic input. It is demonstrated that the proposed method, when using loworder input, can achieve similar results to the SRP approach of much higher order.

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Section: Spatially-localised Acoustic Intensitymentioning

confidence: 99%

Section: Directional Re-assignment-based Srpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sharpening of Angular Spectra Based on a Directional Re-assignment Approach for Ambisonic Sound-field Visualisation

McCormack

Politis

Pulkki

2019

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…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. Editing this kind of metadata in production was considered in [41] to achieve effects including rotation, zoom, compression, and spatial filtering.…”

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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“…Direction of arrival (DOA) estimation is the task of identifying the relative position of the sound sources with respect to the microphone. DOA estimation is a fundamental operation in microphone array processing and forms an integral part of speech enhancement [1], multichannel sound source separation [2] and spatial audio coding [3]. Popular approaches to DOA estimation are based on time-delay-of-arrival (TDOA) [4], the steered-response-power (SRP) [5], or on subspace methods such as multiple signal classification (MUSIC) [6] and the estimation of signal parameters via rotational invariance technique (ESPRIT) [7].…”

Section: Introductionmentioning

confidence: 99%

Direction of Arrival Estimation for Multiple Sound Sources Using Convolutional Recurrent Neural Network

Adavanne

Politis

Virtanen

2018

2018 26th European Signal Processing Conference (EUSIPCO)

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202

177

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This paper proposes a deep neural network for estimating the directions of arrival (DOA) of multiple sound sources. The proposed stacked convolutional and recurrent neural network (DOAnet) generates a spatial pseudo-spectrum (SPS) along with the DOA estimates in both azimuth and elevation. We avoid any explicit feature extraction step by using the magnitudes and phases of the spectrograms of all the channels as input to the network. The proposed DOAnet is evaluated by estimating the DOAs of multiple concurrently present sources in anechoic, matched and unmatched reverberant conditions. The results show that the proposed DOAnet is capable of estimating the number of sources and their respective DOAs with good precision and generate SPS with high signal-to-noise ratio.

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Sector-Based Parametric Sound Field Reproduction in the Spherical Harmonic Domain

Cited by 49 publications

References 22 publications

Sharpening of Angular Spectra Based on a Directional Re-assignment Approach for Ambisonic Sound-field Visualisation

Sharpening of Angular Spectra Based on a Directional Re-assignment Approach for Ambisonic Sound-field Visualisation

Object-Based Reverberation for Spatial Audio

Direction of Arrival Estimation for Multiple Sound Sources Using Convolutional Recurrent Neural Network

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