An L-shaped microphone array configuration for impulsive acoustic source localization in 2-D using orthogonal clustering based time delay estimation

Omer, Muhammad; Quadeer, Ahmed Abdul; Al-Naffouri, Tareq Y.; Sharawi, Mohammad S.

doi:10.1109/iccspa.2013.6487241

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…However, no detailed description about the microphone array itself is provided. An L-Shaped microphone array configuration has been presented in [22] for impulsive acoustic source localization in a reverberant environment. The localization technique relies on a time delay estimation technique based on the orthogonal clustering algorithm (TDE-OC) which is designed to work under room reverberant conditions and at low sampling rates.…”

Section: Introductionmentioning

confidence: 99%

Non-Uniform Microphone Arrays for Robust Speech Source Localization for Smartphone-Assisted Hearing Aid Devices

Ganguly

Panahi

2017

J Sign Process Syst

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Robust speech source localization (SSL) is an important component of the speech processing pipeline for hearing aid devices (HADs). SSL via time direction of arrival (TDOA) estimation has been known to improve performance of HADs in noisy environments, thereby providing better listening experience for hearing aid users. Smartphones now possess the capability to connect to the HADs through wired or wireless channel. In this paper, we present our findings about the non-uniform non-linear microphone array (NUNLA) geometry for improving SSL for HADs using an L-shaped three-element microphone array available on modern smartphones. The proposed method is implemented on a frame-based TDOA estimation algorithm using a modified Dictionary-based singular value decomposition method (SVD) method for localizing single speech sources under very low signal to noise ratios (SNR). Unlike most methods developed for uniform microphone arrays, the proposed method has low spatial aliasing as well as low spatial ambiguity while providing a robust low-error with 360° DOA scanning capability. We present the comparison among different types of microphone arrays, as well as compare their performance using the proposed method.

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Section: Introductionmentioning

confidence: 99%

Non-Uniform Microphone Arrays for Robust Speech Source Localization for Smartphone-Assisted Hearing Aid Devices

Ganguly

Panahi

2017

J Sign Process Syst

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“…They calculated the location of the source from the intersection of hyperbolic curves taken from the TDOA estimations. Another L-Shaped microphone array structure was suggested in [ 54 ] for impulsive acoustic source localization. This method focuses on a TDOA estimation technique that uses the orthogonal clustering algorithm.…”

Section: Related Workmentioning

confidence: 99%

Robust Three-Microphone Speech Source Localization Using Randomized Singular Value Decomposition

Tokgoz¹,

Panahi

2021

IEEE Access

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Direction-of-arrival (DOA) estimation is a fundamental technique in array signal processing due to its wide applications in beamforming, speech enhancement and many other assistive speech processing technologies. In this paper, we devise a novel DOA technique based on randomized singular value decomposition (RSVD) to improve the performance of non-uniform non-linear microphone arrays (NUNLA). The accurate and efficient singular value decomposition of large data matrices is computationally challenging, and randomization provides an effective tool for performing matrix approximation, therefore, the developed DOA estimation utilizes a modified dictionary-based RSVD method for localizing single speech sources under low signal-to-noise ratios (SNR). Unlike previous methods developed for uniform linear microphone arrays, the proposed approach with L-shaped three microphone setup has no ‘left-right’ ambiguity. We present the performance of our proposed method in comparison to other techniques. The demonstrated experiments shows at-least 20% performance improvement using simulated data and 25% performance improvement using real data when compared with similar DoA estimation techniques for NUNLA. The proposed method exploits frame-based online time delay of arrival (TDOA) measurements which facilitates the proposed algorithm to run on real-time devices. We also show an efficient real-time implementation of the proposed method on a Pixel 3 Android smartphone using its built-in three microphones for hearing aid applications.

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“…Additionally, the L-shaped array allows for simple implementation, because it consists of two ULAs connected orthogonally at one end of each ULA. For these reasons, the L-shaped array is widely applied to the 2D DOA estimation method [17,18,19,20,21,22,23,24,25,26], and its practical applications can be found in the past researches [27,28]. Although the narrowband subspace method may be unable to directly estimate wideband DOAs, one possible way to solve this problem is to employ the narrowband subspace method in each temporal frequency intensively, and then the wideband DOA results can be estimated by interpolating the narrowband DOA results all frequency bins [29,30].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Framework for Estimating the Direction of Multiple Sound Sources Using Higher-Order Generalized Singular Value Decomposition

Suksiri

Fukumoto

2019

Sensors

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This paper presents an efficient framework for estimating the direction-of-arrival (DOA) of wideband sound sources. The proposed framework provides an efficient way to construct a wideband cross-correlation matrix from multiple narrowband cross-correlation matrices for all frequency bins. In addition, the proposed framework is inspired by the coherent signal subspace technique with further improvement of linear transformation procedure, and the new procedure no longer requires any process of DOA preliminary estimation by exploiting unique cross-correlation matrices between the received signal and itself on distinct frequencies, along with the higher-order generalized singular value decomposition of the array of this unique matrix. Wideband DOAs are estimated by employing any subspace-based technique for estimating narrowband DOAs, but using the proposed wideband correlation instead of the narrowband correlation matrix. It implies that the proposed framework enables cutting-edge studies in the recent narrowband subspace methods to estimate DOAs of the wideband sources directly, which result in reducing computational complexity and facilitating the estimation algorithm. Practical examples are presented to showcase its applicability and effectiveness, and the results show that the performance of fusion methods perform better than others over a range of signal-to-noise ratios with just a few sensors, which make it suitable for practical use.

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An L-shaped microphone array configuration for impulsive acoustic source localization in 2-D using orthogonal clustering based time delay estimation

Cited by 5 publications

References 20 publications

Non-Uniform Microphone Arrays for Robust Speech Source Localization for Smartphone-Assisted Hearing Aid Devices

Non-Uniform Microphone Arrays for Robust Speech Source Localization for Smartphone-Assisted Hearing Aid Devices

Robust Three-Microphone Speech Source Localization Using Randomized Singular Value Decomposition

An Efficient Framework for Estimating the Direction of Multiple Sound Sources Using Higher-Order Generalized Singular Value Decomposition

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