Browsing by Author "Zabala-Blanco D."

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    3D Multiple Sound Source Localization by Proposed T-Shaped Circular Distributed Microphone Arrays in Combination with GEVD and Adaptive GCC-PHAT/ML Algorithms
    (MDPI, 2022) Firoozabadi A.D.; Irarrazaval P.; Irarrazaval P.; Irarrazaval P.; Adasme P.; Zabala-Blanco D.; Jativa P.P.; Azurdia-Meza C.
    © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Multiple simultaneous sound source localization (SSL) is one of the most important applications in the speech signal processing. The one-step algorithms with the advantage of low computational complexity (and low accuracy), and the two-step methods with high accuracy (and high computational complexity) are proposed for multiple SSL. In this article, a combination of one-step-based method based on the generalized eigenvalue decomposition (GEVD), and a two-step-based method based on the adaptive generalized cross-correlation (GCC) by using the phase transform/maximum likelihood (PHAT/ML) filters along with a novel T-shaped circular distributed microphone array (TCDMA) is proposed for 3D multiple simultaneous SSL. In addition, the low computational complexity advantage of the GCC algorithm is considered in combination with the high accuracy of the GEVD method by using the distributed microphone array to eliminate spatial aliasing and thus obtain more appropriate information. The proposed T-shaped circular distributed microphone array-based adaptive GEVD and GCC-PHAT/ML algorithms (TCDMA-AGGPM) is compared with hierarchical grid refinement (HiGRID), temporal extension of multiple response model of sparse Bayesian learning with spherical harmonic (SH) extension (SH-TMSBL), sound field morphological component analysis (SF-MCA), and time-frequency mixture weight Bayesian nonparametric acoustical holography beamforming (TF-MW-BNP-AHB) methods based on the mean absolute estimation error (MAEE) criteria in noisy and reverberant environments on simulated and real data. The superiority of the proposed method is presented by showing the high accuracy and low computational complexity for 3D multiple simultaneous SSL.
  • No Thumbnail Available
    Item
    Speakers counting by proposed nested microphone array in combination with limited space SRP
    (European Signal Processing Conference, EUSIPCO, 2021) Firoozabadi A.D.; Durney H.; Sanhueza M.; Irarrazaval P.; Adasme P.; Zabala-Blanco D.; Palacios-Jativa P.; Azurdia-Meza C.
    © 2021 European Signal Processing Conference. All rights reserved.In this paper, a novel method is presented for estimating the number of speakers based on the microphone arrays. Firstly, a 3D snowflake nested microphone array (SNMA) is proposed for recording the speech signals. In the following, the steered response power (SRP) algorithm is implemented on subbands in limited spaces conditions for all microphone pairs related to the subarrays. Therefore, a weighted averaging method is implemented on subband limited spaces SRPs (LSRP), and the final energy map is compared with the histogram of the maximums of the SRP function on different subbands for various time frames. The passed candidate points are categorized by unsupervised K-means clustering and the number of speakers is estimated by the silhouette criteria. The accuracy of the proposed method is compared with PENS, i-vector PLDA, and wavelet-GEVD algorithms. The results show the superiority of the proposed method in comparison with other previous research.
  • No Thumbnail Available
    Item
    Three-dimensional sound source localization by distributed microphone arrays
    (European Signal Processing Conference, EUSIPCO, 2021) Firoozabadi A.D.; Durney H.; Sanhueza M.; Irarrazaval P.; Adasme P.; Zabala-Blanco D.; Palacios-Jativa P.; Azurdia-Meza C.
    © 2021 European Signal Processing Conference. All rights reserved.Multiple sound source localization (SSL) is one of the applicable and important areas in the speech signal processing. In this paper, a two-step method is proposed for multiple 3D SSL based on the time delay estimation (TDE) in combination with distributed microphone arrays (DMA). In the first step, the direction of speakers are estimated by the use of a circular microphone array (CMA) in the center of the room and implementing the generalized cross-correlation (GCC) function. In the second step, the distributed T-shaped microphone arrays on the walls are considered for 3D SSL. The two most closed T-shaped array to each speaker are selected, where one of them is used for horizontal and the other one for vertical direction of arrival (DOA) estimation by the use of generalized eigenvalue decomposition (GEVD) algorithm. The experiments on the simulated data for 2 and 3 simultaneous speakers show the superiority of the proposed distributed microphone array-direction of arrival estimators (DMA-DOAE) method in comparison with other previous works in noisy and reverberant environments.