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Related Experiment Video

Updated: May 13, 2026

The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

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Published on: August 12, 2013

Exploring super-Gaussianity toward robust information-theoretical time delay estimation.

Theodoros Petsatodis¹, Fotios Talantzis, Christos Boukis

¹Center for TeleInFrastruktur (CTIF), Aalborg University, Aalborg DK-9220, Denmark. thp@es.aau.dk

The Journal of the Acoustical Society of America

|March 8, 2013

Summary

This summary is machine-generated.

This study explores time delay estimation (TDE) for speaker localization. The findings show TDE performance is independent of source distribution assumptions when using a generalized Gaussian model.

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Area of Science:

Signal Processing
Acoustics
Machine Learning

Background:

Speaker localization and tracking rely on time delay estimation (TDE).
Existing TDE methods often assume Gaussian source distribution, which is not always accurate for real-world speech signals affected by noise and reverberation.
Performance fluctuations in TDE are observed due to varying speech distributions and environmental factors like multi-path reflections and background noise.

Purpose of the Study:

To investigate the impact of different speech-based distributions on time delay estimation (TDE).
To evaluate an information-theoretical TDE method using generalized Gaussian distributions to model speech signals.
To assess TDE performance across a range of distributions, including Gaussian, Laplacian, and Gamma.

Main Methods:

Developed an information-theoretical TDE approach incorporating higher-order statistics (HOS).
Replaced the Gaussian source assumption with a generalized Gaussian distribution model.
Derived closed-form expressions for univariate and multivariate entropy of the generalized Gaussian distribution for TDE evaluation.

Main Results:

The time delay estimation (TDE) method demonstrated robustness across various speech signal distributions.
The performance of the TDE was found to be independent of the specific underlying distribution assumption, provided the covariance matrix remained constant.
The generalized Gaussian distribution effectively models a wider range of speech characteristics compared to the traditional Gaussian assumption.

Conclusions:

The proposed information-theoretical TDE method is robust to variations in speech signal distributions.
Accurate time delay estimation can be achieved without strict assumptions on the source signal's statistical distribution.
This research offers a more flexible and reliable approach to speaker localization and tracking in diverse acoustic environments.