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The active intensity vector (AIV) is a common descriptor of the sound field. In microphone array processing, AIV is commonly approximated with beamforming operations and utilized as a direction of arrival (DOA) estimator. However, in its original form, it provides inaccurate estimates in sound field conditions where coherent sound sources are simultaneously active. In this work we utilize a higher...
We present the design of a digital microphone array comprised of MEMS microphones and evaluate its potential for spatial audio capturing and direction-of-arrival (DOA) estimation which is an essential part of encoding the soundscape. The device is a cheaper and more compact alternative to analog microphone arrays which require external — and usually expensive — analog-to-digital converters and sound...
Over the years, different spatial audio techniques have been proposed as the means to capture, encode and reproduce the spatial properties of acoustic fields, yet specific issues need to be modified each time in accordance to the type of microphone array used as well as with the technology used for reproduction. Using a circular array of omnidirectional microphones, we formulate in this paper a parametric...
In this paper, we consider the data association problem that arises when localizing multiple sound sources using direction of arrival (DOA) estimates from multiple microphone arrays. In such a scenario, the association of the DOAs across the arrays that correspond to the same source is unknown and must be found for accurate localization. We present an association algorithm that finds the correct DOA...
We propose a novel real-time adaptative localization approach for multiple sources using a circular array, in order to suppress the localization ambiguities faced with linear arrays, and assuming a weak sound source sparsity which is derived from blind source separation methods. Our proposed method performs very well both in simulations and in real conditions at 50% real-time.
We recently proposed an approach inspired by Sparse Component Analysis for real-time localisation 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 localisation in these zones. A histogram of estimated Directions of Arrival (DOAs) was formed and then processed...
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