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Updated: Oct 9, 2025

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention
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Robust Three-Microphone Speech Source Localization Using Randomized Singular Value Decomposition.

Serkan Tokgoz1, Issa M S Panahi1

  • 1Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA.

IEEE Access : Practical Innovations, Open Solutions
|December 20, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new direction-of-arrival (DOA) estimation method using randomized singular value decomposition (RSVD) for non-uniform non-linear microphone arrays (NUNLA). The novel technique achieves significant performance improvements, even in low signal-to-noise ratios (SNR).

Keywords:
Hearing aid devicelow SNRnon-uniform microphone arraysrandomized algorithmreal-time implementationsingular value decompositionsmartphonespeech source localization

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Area of Science:

  • Array Signal Processing
  • Acoustic Signal Processing
  • Machine Learning for Signal Processing

Background:

  • Direction-of-arrival (DOA) estimation is crucial for assistive speech technologies, but performance degrades in non-uniform non-linear microphone arrays (NUNLA) and low signal-to-noise ratios (SNR).
  • Accurate singular value decomposition (SVD) of large matrices is computationally intensive, hindering real-time applications.
  • Existing DOA methods often suffer from ambiguities, such as 'left-right' ambiguity, especially with uniform linear microphone arrays.

Purpose of the Study:

  • To develop a novel DOA estimation technique for NUNLA using randomized singular value decomposition (RSVD).
  • To address computational challenges of SVD for large matrices and improve DOA estimation accuracy under low SNR conditions.
  • To eliminate 'left-right' ambiguity in DOA estimation using a specific microphone array configuration.

Main Methods:

  • A modified dictionary-based RSVD method is employed for DOA estimation of single speech sources.
  • An L-shaped three-microphone setup is utilized to overcome the 'left-right' ambiguity inherent in some DOA techniques.
  • The algorithm incorporates frame-based online time delay of arrival (TDOA) measurements for real-time processing.

Main Results:

  • The proposed RSVD-based DOA method demonstrates at least a 20% performance improvement with simulated data.
  • Experiments with real data show a 25% performance enhancement compared to existing DOA techniques for NUNLA.
  • The method was successfully implemented in real-time on a smartphone for hearing aid applications.

Conclusions:

  • The novel RSVD-based DOA estimation technique effectively enhances performance for NUNLA, particularly in challenging low SNR environments.
  • The L-shaped array configuration successfully resolves 'left-right' ambiguity, offering a more robust DOA solution.
  • The real-time implementation highlights the practical applicability of the method in assistive hearing devices.