<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Multiple sound source localization in noisy and reverberant conditions is one of the important challenges in the speech signal processing. The aim of this article is three-dimensional sound source localization in undesirable scenarios. For the localization algorithms, the spatial aliasing is one of the destructive factors in reducing the accuracy. Firstly, a 3D quasi-spherical nested microphone array (QSNMA) is proposed for eliminating the spatial aliasing. Since the speech signal has the windowed-disjoint orthogonality property, the speech information differs in terms of the frequency bands. Then, the Gammatone filter bank is introduced for the speech subband processing. In the following, the multiresolution steered response power (SRP) algorithm is adaptively implemented on subbands with the phase transform (PHAT)/maximum likelihood (ML) weighted functions based on the levels of the noise and reverberation. The peaks of the multiresolution adaptive SRP (MASRP) algorithm are extracted in each subband based on the number of speakers for continuous time frames. Finally, the distribution of these peaks are calculated in each subband and they are merged by the use of weighted averaging method. The final 3D speakers locations are estimated by extracting the peaks in the final distribution. The proposed QSNMAMASRP(PHAT/ML) algorithm is evaluated on real and simulated data for 2 and 3 simultaneous speakers in noisy and reverberant conditions. The proposed method is compared with SRP-PHAT, spectral source model-deep neural network, and spherical harmonic temporal extension of multiple response model sparse Bayesian learning algorithms on different range of signal-to-noise ratio and reverberation time. The mean absolute estimation error, averaged standard deviation for absolute estimation error, and computational complexity results show the superiority of the proposed method.</p></abstract>

Multiple sound source localization in noisy and reverberant conditions is one of the important challenges in the speech signal processing. The aim of this article is three-dimensional sound source localization in undesirable scenarios. For the localization algorithms, the spatial aliasing is one of the destructive factors in reducing the accuracy. Firstly, a 3D quasi-spherical nested microphone array (QSNMA) is proposed for eliminating the spatial aliasing. Since the speech signal has the windowed-disjoint orthogonality property, the speech information differs in terms of the frequency bands. Then, the Gammatone filter bank is introduced for the speech subband processing. In the following, the multiresolution steered response power (SRP) algorithm is adaptively implemented on subbands with the phase transform (PHAT)/maximum likelihood (ML) weighted functions based on the levels of the noise and reverberation. The peaks of the multiresolution adaptive SRP (MASRP) algorithm are extracted in each subband based on the number of speakers for continuous time frames. Finally, the distribution of these peaks are calculated in each subband and they are merged by the use of weighted averaging method. The final 3D speakers locations are estimated by extracting the peaks in the final distribution. The proposed QSNMAMASRP(PHAT/ML) algorithm is evaluated on real and simulated data for 2 and 3 simultaneous speakers in noisy and reverberant conditions. The proposed method is compared with SRP-PHAT, spectral source model-deep neural network, and spherical harmonic temporal extension of multiple response model sparse Bayesian learning algorithms on different range of signal-to-noise ratio and reverberation time. The mean absolute estimation error, averaged standard deviation for absolute estimation error, and computational complexity results show the superiority of the proposed method.

Evaluation of localization precision by proposed quasi-spherical nested microphone array in combination with multiresolution adaptive steered response power

Pontificia Universidad Católica de Chile

Journal of Electrical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Multiple sound source localization in noisy and reverberant conditions is one of the important challenges in the speech signal processing. The aim of this...

Evaluation of localization precision by proposed quasi-spherical nested microphone array in combination with multiresolution adaptive steered response power

Online veröffentlicht: 10. Aug. 2020

Seitenbereich: 150 - 164

Eingereicht: 09. Mai 2020

DOI: https://doi.org/10.2478/jee-2020-0022

Schlüsselwörter
sound source localization, nested microphone array, subband processing, time delay estimation, filter bank

© 2020 Ali Dehghan Firoozabadi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Evaluation of localization precision by proposed quasi-spherical nested microphone array in combination with multiresolution adaptive steered response power

Online veröffentlicht: 10. Aug. 2020

Seitenbereich: 150 - 164

Eingereicht: 09. Mai 2020

DOI: https://doi.org/10.2478/jee-2020-0022

Schlüsselwörtersound source localization, nested microphone array, subband processing, time delay estimation, filter bank

© 2020 Ali Dehghan Firoozabadi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
sound source localization, nested microphone array, subband processing, time delay estimation, filter bank