A Moving Horizon Framework for Sound Zones

Møller, Marie Sofie; Østergaard, Jan

doi:10.1109/taslp.2019.2951995

Cited by 19 publications

(11 citation statements)

References 29 publications

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“…The former is the ratio of the mean square pressure in the bright zone with respect to the the same quantity in the dark one, when both are sampled under the same conditions. The NMSE quantifies the differences between the pressure in the bright zone and the reference pressure p 𝑟 [12,17].…”

Section: Weighted Least-squares Methodsmentioning

confidence: 99%

Performance of Low Frequency Sound Zones Based on Truncated Room Impulse Responses

et al. 2022

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Using spatially distributed loudspeakers and properly designed control filters, it is possible to generate sound zones that play different audio contents in different regions of the same room. For low frequency content, the design of control filters relies on the room impulse responses (RIRs) between each loudspeaker and the desired listening positions. Estimates of the RIRs can be obtained by distributing wireless microphones within the sound zones and thereby systematically acquiring sufficient knowledge about the acoustical characteristics of the room and loudspeakers. Longer acquisition times would generally lead to better estimates of the RIRs but would also introduce processing delays, which is undesirable in cases where time-varying RIRs are to be compensated. In addition, shorter RIRs may imply lower computational complexity.In this work, control filters were calculated using truncated versions of the RIRs in order to simulate the effect of a reduced acquisition time. The performance was evaluated in terms of the acoustic contrast ratio (ACR) and it was seen that within a certain limit, doubling the acquisition time increases the ACR around 4 dB or more. Moreover, to keep the sound pressure low in the dark zone, only a limited part of the reverberation tail is required.

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Section: Weighted Least-squares Methodsmentioning

confidence: 99%

Performance of Low Frequency Sound Zones Based on Truncated Room Impulse Responses

et al. 2022

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“…In order to deliver the intended sound system behavior to listeners, it is necessary to know about and compensate for this effect. Applications include among others room equalization (Cecchi et al, 2018;Karjalainen et al, 2001;Radlovic et al, 2000), virtual reality sound field navigation (Tylka and Choueiri, 2015), source localization (Nowakowski et al, 2017), and spatial sound field reproduction over predefined or dynamic regions of space also referred to as sound zones (Betlehem et al, 2015;Møller and Østergaard, 2020). An approach to achieve this, is to measure the loudspeaker response at the desired listening locations and adjust the sound system accordingly.…”

Section: Introductionmentioning

confidence: 99%

Deep Sound Field Reconstruction in Real Rooms: Introducing the ISOBEL Sound Field Dataset

Kristoffersen,

Møller,

Martínez-Nuevo

et al. 2021

Preprint

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Knowledge of loudspeaker responses are useful in a number of applications, where a sound system is located inside a room that alters the listening experience depending on position within the room. Acquisition of sound fields for sound sources located in reverberant rooms can be achieved through labor intensive measurements of impulse response functions covering the room, or alternatively by means of reconstruction methods which can potentially require significantly fewer measurements. This paper extends evaluations of sound field reconstruction at low frequencies by introducing a dataset with measurements from four real rooms. The ISOBEL Sound Field dataset is publicly available, and aims to bridge the gap between synthetic and real-world sound fields in rectangular rooms. Moreover, the paper advances on a recent deep learning-based method for sound field reconstruction using a very low number of microphones, and proposes an approach for modeling both magnitude and phase response in a U-Net-like neural network architecture. The complex-valued sound field reconstruction demonstrates that the estimated room transfer functions are of high enough accuracy to allow for personalized sound zones with contrast ratios comparable to ideal room transfer functions using 15 microphones below 150 Hz.The following article has been submitted to the Journal of the Acoustical Society of America. After it is published, it will be found at http://asa.scitation.org/journal/jas.

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“…The higher complexity is not an important limitation for static PSZ systems, where the filters can be computed off-line. However, it is an important aspect for dynamic PSZ systems where the location of the zones may change over time [16] or when the characteristics of the input signal are taken into account [17], as the filters must be often recomputed. Consequently, an algorithm offering similar performance to wPM-TD but with a lower computational complexity could be very useful for certain applications.…”

Section: Introductionmentioning

confidence: 99%

Personal Sound Zones by Subband Filtering and Time Domain Optimization

Moles-Cases

Piñero

Diego

et al. 2020

IEEE/ACM Trans. Audio Speech Lang. Process.

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Personal Sound Zones (PSZ) systems aim to render independent sound signals to multiple listeners within a room by using arrays of loudspeakers. One of the algorithms used to provide PSZ is Weighted Pressure Matching (wPM), which computes the set of filters required to render a desired response in the listening zones while reducing the acoustic energy arriving to the quiet zones. This algorithm can be formulated in time and frequency domains. In general, the time-domain formulation (wPM-TD) can obtain good performance with shorter filters and delays than the frequency-domain formulation (wPM-FD). However, wPM-TD requires higher computation for obtaining the optimal filters. In this paper, we propose a novel approach to the wPM algorithm named Weighted Pressure Matching with Subband Decomposition (wPM-SD), which formulates an independent time-domain optimization problem for each of the subbands of a Generalized Discrete Fourier Transform (GDFT) filter bank. The approach of solving the optimization independently for each subband has two main advantages: 1) lower computational complexity than wPM-TD to compute the optimal filters; 2) higher versatility than the classic wPM algorithms, as it allows different configurations (sets of loudspeakers, filter lengths, etc.) in each subband. Moreover, filtering the input signals with a GDFT filter bank (as in wPM-SD) requires lower computational effort than broadband filtering (as in wPM-TD and wPM-FD), which is beneficial for practical PSZ systems. We present experimental evaluations showing that wPM-SD offers very similar performance to wPM-TD. In addition, two cases where the versatility of wPM-SD is beneficial for a PSZ system are presented and experimentally validated. The experimental results are obtained by using two practical arrays of loudspeakers which can operate together in the frequency range 100-5000 Hz.

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A Moving Horizon Framework for Sound Zones

Cited by 19 publications

References 29 publications

Performance of Low Frequency Sound Zones Based on Truncated Room Impulse Responses

Performance of Low Frequency Sound Zones Based on Truncated Room Impulse Responses

Deep Sound Field Reconstruction in Real Rooms: Introducing the ISOBEL Sound Field Dataset

Personal Sound Zones by Subband Filtering and Time Domain Optimization

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