Abstract-In this work, a multiple sound source localization and counting method is presented, that imposes relaxed sparsity constraints on the source signals. A uniform circular microphone array is used to overcome the ambiguities of linear arrays, however the underlying concepts (sparse component analysis and matching pursuit-based operation on the histogram of estimates) are applicable to any microphone array topology. Our method is based on detecting time-frequency (TF) zones where one source is dominant over the others. Using appropriately selected TF components in these "single-source" zones, the proposed method jointly estimates the number of active sources and their corresponding directions of arrival (DOAs) by applying a matching pursuit-based approach to the histogram of DOA estimates. The method is shown to have excellent performance for DOA estimation and source counting, and to be highly suitable for real-time applications due to its low complexity. Through simulations (in various signal-to-noise ratio conditions and reverberant environments) and real environment experiments, we indicate that our method outperforms other state-of-the-art DOA and source counting methods in terms of accuracy, while being significantly more efficient in terms of computational complexity.
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This work proposes a novel method for 3D direction of arrival (DOA) estimation based on the sound intensity vector estimation, via the encoding of the signals of a spherical microphone array from the space domain to the spherical harmonic domain. The sound intensity vector is estimated on detected single source zones (SSZs), where one source is dominant. A smoothed 2D histogram of these estimates reveals the DOA of the present sources and through an iterative process, accurate 3D DOA information can be obtained. The performance of the proposed method is demonstrated through simulations in various signal-to-noise ratio and reverberation conditions.
Abstract-Recently, we proposed an approach inspired by Sparse Component Analysis for real-time localization of multiple sound sources using a circular microphone array. The method was based on identifying time-frequency zones where only one source is active, reducing the problem to single-source localization for these zones. A histogram of estimated Directions of Arrival (DOAs) was formed and then processed to obtain improved DOA estimates, assuming that the number of sources was known. In this paper, we extend our previous work by proposing three different methods for counting the number of sources by looking for prominent peaks in the derived histogram based on: (a) performing a peak search, (b) processing an LPC-smoothed version of the histogram, (c) employing a matching pursuitbased approach. The third approach is shown to perform very accurately in simulated reverberant conditions and additive noise, and its computational requirements are very small.
Sound source localization in three dimensions with microphone arrays is an active field of research, applicable in sound enhancement, source separation, and sound field analysis. In this contribution we propose a method for three dimensional multiple sound source localization in reverberant environments. We employ a spatially constrained steered response beamformer on a spherical sector centered at the direction of arrival (DOA) estimates of the intensity vector. Experiments are performed in both simulated and real acoustical environments with a spherical microphone array for multiple sound sources under different reverberation and signal-to-noise ratio (SNR) conditions. The performance of the proposed method is compared with our previously proposed work and a subspace method in the spherical harmonic domain. The results demonstrate a significant improvement in terms of localization accuracy.Index Termsdirection of arrival, 3D, multiple sources, spherical microphone array processing, sound intensity
Abstract-The MusiNet research project aims to provide a comprehensive architecture and a prototype implementation of a complete Networked Music Performance (NMP) system. In this paper we describe the current status of the project, focusing on critical decisions regarding the system's architecture and specifications, the low delay audio and video coding techniques to be employed, the media relay design, and the synchronous and asynchronous collaboration algorithms to be adopted.
The purpose of this article is to detail and evaluate three alternative approaches to soundfield visualization, which all employ the use of spatially localized active-intensity (SLAI) vectors. These SLAI vectors are of particular interest, as they allow direction-of-arrival (DoA) estimates to be extracted in multiple spatially localized sectors, such that a sound source present in one sector has reduced influence on the DoA estimate made in another sector. These DoA estimates may be used to visualize the sound-field by either: (I) directly depicting the estimates as icons, with their relative size dictated by the corresponding energy of each sector; (II) generating traditional activity maps via histogram analysis of the DoA estimates; or (III) by using the DoA estimates to reassign energy and subsequently sharpen traditional beamformer-based activity maps. Since the SLAI-based DoA estimates are continuous, these approaches are inherently computationally efficient, as they forego the need for dense scanning grids to attain high-resolution imaging. Simulation results also show that these SLAI-based alternatives outperform traditional active-intensity and beamformer-based approaches, for the majority of cases.
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