Real-time multiple sound source localization using a circular microphone array based on single-source confidence measures

Abstract

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Real-Time Multiple Sound Source Localization and Counting Using a Circular Microphone Array

“…We propose a modified version of the algorithm in [29] and we choose this algorithm because it is computationally efficient and robust in noisy and reverberant environments [22], [29].…”

“…In our previous work [22], [31], [32], we used only the ω max i frequency, corresponding to the strongest component of the cross-power spectrum of the microphone pair {m i m i+1 } in a single-source zone, giving us a single DOA for each single-source zone. In this work we propose the use of d frequency components in each single-source zone, i.e., the use of those frequencies that correspond to the indices of the d highest peaks of the magnitude of the crosspower spectrum over all microphone pairs.…”

“…Using this assumption, the multiple source propagation estimation problem may be rewritten as a single-source one in these windows or zones, and the above methods estimate a mixing/propagation matrix, and then try to recover the sources. By estimating this mixing matrix and knowing the geometry of the microphone array, we may localize the sources, as proposed in [20]- [22], for example. Most of the SCA approaches require the sources to be W-disjoint orthogonal (WDO) [23]-meaning that in each time-frequency component, at most one source is activewhich is approximately satisfied by speech in anechoic environments, but not in reverberant conditions.…”

“…The methodology is not specific to the geometry of the array, and is based on the following steps: (a) finding single-source zones in the time-frequency domain [24] (i.e., zones where one source is clearly dominant over the others); (b) performing single-source DOA estimation on these zones using the method of [29]; (c) collecting these DOA estimations into a histogram to enable the localization of the multiple sources; and (d) jointly performing multiple DOA estimation and source counting through the post-processing of the histogram using a method based on matching pursuit [30]. Parts of this work have been recently presented in [22], [31], [32]. This current work presents a more detailed and improved methodology compared to our recently published results, especially in the following respects: (i) we provide a way of combining the tasks of source counting and DOA estimation using matching pursuit in a natural and efficient manner; and (ii) we provide a thorough performance investigation of our proposed approach in numerous simulation and real-environment scenarios, both for the DOA estimation and the source counting tasks.…”

Source counting in real-time sound source localization using a circular microphone array

“…Their main advantage is their flexibility to deal with both the situations when the number of sources is respectively (strictly) lower or higher than the number of sensors. If we estimate this mixing matrix and if we know the geometry of the microphone array, we may then localize the sources, as proposed in [4]- [6], for example.…”