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This report presents test results for the \mbox{LOCATA} challenge \cite{lollmann2018locata} using the recently developed MCC-PHAT (multichannel cross correlation - phase transform) sound source localization method. The specific tasks…

音频与语音处理 · 电气工程与系统科学 2018-09-21 Shoufeng Lin

This paper introduces a modification of phase transform on singular value decomposition (SVD-PHAT) to localize multiple sound sources. This work aims to improve localization accuracy and keeps the algorithm complexity low for real-time…

音频与语音处理 · 电气工程与系统科学 2019-07-01 Francois Grondin , James Glass

In the last three decades, the Steered Response Power (SRP) method has been widely used for the task of Sound Source Localization (SSL), due to its satisfactory localization performance on moderately reverberant and noisy scenarios. Many…

Human-robot interaction in natural settings requires filtering out the different sources of sounds from the environment. Such ability usually involves the use of microphone arrays to localize, track and separate sound sources online.…

音频与语音处理 · 电气工程与系统科学 2018-12-04 Francois Grondin , Francois Michaud

This paper introduces a new localization method called SVD-PHAT. The SVD-PHAT method relies on Singular Value Decomposition of the SRP-PHAT projection matrix. A k-d tree is also proposed to speed up the search for the most likely direction…

音频与语音处理 · 电气工程与系统科学 2019-02-12 Francois Grondin , James Glass

Algorithms for acoustic source localization and tracking provide estimates of the positional information about active sound sources in acoustic environments and are essential for a wide range of applications such as personal assistants,…

音频与语音处理 · 电气工程与系统科学 2019-08-21 Heinrich W. Loellmann , Christine Evers , Alexander Schmidt , Hendrik Barfuss , Patrick A. Naylor , Walter Kellermann

In this paper, we present a new single sound source DOA estimation and tracking system based on the well-known SRP-PHAT algorithm and a three-dimensional Convolutional Neural Network. It uses SRP-PHAT power maps as input features of a fully…

音频与语音处理 · 电气工程与系统科学 2020-12-18 David Diaz-Guerra , Antonio Miguel , Jose R. Beltran

This paper introduces a variant of the Singular Value Decomposition with Phase Transform (SVD-PHAT), named Difference SVD-PHAT (DSVD-PHAT), to achieve robust Sound Source Localization (SSL) in noisy conditions. Experiments are performed on…

音频与语音处理 · 电气工程与系统科学 2019-07-31 Francois Grondin , James Glass

The ability to localize and track acoustic events is a fundamental prerequisite for equipping machines with the ability to be aware of and engage with humans in their surrounding environment. However, in realistic scenarios, audio signals…

音频与语音处理 · 电气工程与系统科学 2020-10-22 Christine Evers , Heinrich Loellmann , Heinrich Mellmann , Alexander Schmidt , Hendrik Barfuss , Patrick Naylor , Walter Kellermann

In this article we analyze the state-of-the-art in multilateration - the family of localization methods enabled by the range difference observations. These methods are computationally efficient, signal-independent, and flexible with regards…

声音 · 计算机科学 2020-07-29 Srđan Kitić , Clément Gaultier , Grégory Pallone

This paper proposes an efficient method based on the steered-response power (SRP) technique for sound source localization using microphone arrays: the volumetric SRP (V-SRP). As compared to the SRP, by deploying a sparser volumetric grid,…

In this paper we present a new robust sound source localization and tracking method using an array of eight microphones (US patent pending) . The method uses a steered beamformer based on the reliability-weighted phase transform (RWPHAT)…

机器人学 · 计算机科学 2016-04-07 Jean-Marc Valin , François Michaud , Jean Rouat

Sound source localization (SSL) demonstrates remarkable results in controlled settings but struggles in real-world deployment due to dual imbalance challenges: intra-task imbalance arising from long-tailed direction-of-arrival (DoA)…

声音 · 计算机科学 2026-01-27 Zexia Fan , Yu Chen , Qiquan Zhang , Kainan Chen , Xinyuan Qian

In this paper we present a new localization method SMS-LORETA (Simultaneous Multiple Sources- Low Resolution Brain Electromagnetic Tomography), capable to locate efficiently multiple simultaneous sources. The new method overcomes some of…

定量方法 · 定量生物学 2011-01-07 Avni Pllana , Herbert Bauer

We present the signal processing framework and some results for the IEEE AASP challenge on acoustic source localization and tracking (LOCATA). The system is designed for the direction of arrival (DOA) estimation in single-source scenarios.…

声音 · 计算机科学 2018-12-05 Daniele Salvati , Carlo Drioli , Gian Luca Foresti

This paper introduces SMP-PHAT, which performs direction of arrival (DoA) of sound estimation with a microphone array by merging pairs of microphones that are parallel in space. This approach reduces the number of pairwise cross-correlation…

We propose an advance Steered Response Power (SRP) method for localizing multiple sources. While conventional SRP performs well in adverse conditions, it remains to struggle in scenarios with closely neighboring sources, resulting in…

音频与语音处理 · 电气工程与系统科学 2024-05-21 Wei-Ting Lai , Lachlan Birnie , Xingyu Chen , Amy Bastine , Thushara D. Abhayapala , Prasanga N. Samarasinghe

Steered Response Power (SRP) is a widely used method for the task of sound source localization using microphone arrays, showing satisfactory localization performance on many practical scenarios. However, its performance is diminished under…

声音 · 计算机科学 2024-03-15 Eric Grinstein , Toon van Waterschoot , Mike Brookes , Patrick A. Naylor

Acoustic reverberation is one of the most relevant factors that hampers the localization of a sound source inside a room. To date, several approaches have been proposed to deal with it, but have not always been evaluated under realistic…

Sound source localization (SSL) is a critical technology for determining the position of sound sources in complex environments. However, existing methods face challenges such as high computational costs and precise calibration requirements,…

声音 · 计算机科学 2025-05-28 Yiyuan Yang , Shitong Xu , Niki Trigoni , Andrew Markham
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