Multiple Sound Source Counting and Localization Based on Spatial Principal Eigenvector

2017 ◽  
Author(s):  
Bing Yang ◽  
Hong Liu ◽  
Cheng Pang
Keyword(s):  
Sound Source ◽  
Principal Eigenvector

Speaker Localization in Reverberant Noisy Environment Using Principal Eigenvector and Classifier

2013 ◽  
Vol 433-435 ◽  
pp. 416-419
Author(s):  
Xin Wang Wan ◽  
Juan Liang
Keyword(s):  
Sound Source ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Localization Algorithm ◽  
Noisy Environment ◽  
Principal Eigenvector ◽  
Localization Accuracy ◽  
Phase Transform ◽  
Bayes Algorithm

Sound source localization is essential in many microphone arrays application, ranging from speech enhancement to human-computer interface. The steered response power (SRP) using the phase transform (SRP-PHAT) method has been proved robust, but the algorithm may fail to locate the sound source in highly reverberant noisy environment. The Naive-Bayes localization algorithm based on classification of cross-correlation functions outperforms the SRP-PHAT in highly reverberant noisy environment. This paper proposes the improved Naive-Bayes localization algorithm using principal eigenvector. Simulation results have demonstrated that the proposed algorithm provides higher localization accuracy than the Naive-Bayes algorithm in reverberant noisy environment.

Role of pinnae and head movements in localizing pure tones 1The authors would like to thank Mr. Remi Humbert for implementing the experiment in Turbo Pascal and for his further assistance.

1999 ◽  
Vol 58 (3) ◽  
pp. 170-179 ◽  
Author(s):  
Barbara S. Muller ◽  
Pierre Bovet
Keyword(s):  
Sound Source ◽  
Head Movement ◽  
Movement Analysis ◽  
Head Movements ◽  
Sound Sources ◽  
Localization Accuracy ◽  
Sound Effects ◽  
Posterior Quadrant ◽  
Localization Performance ◽  
Pure Tones

Twelve blindfolded subjects localized two different pure tones, randomly played by eight sound sources in the horizontal plane. Either subjects could get information supplied by their pinnae (external ear) and their head movements or not. We found that pinnae, as well as head movements, had a marked influence on auditory localization performance with this type of sound. Effects of pinnae and head movements seemed to be additive; the absence of one or the other factor provoked the same loss of localization accuracy and even much the same error pattern. Head movement analysis showed that subjects turn their face towards the emitting sound source, except for sources exactly in the front or exactly in the rear, which are identified by turning the head to both sides. The head movement amplitude increased smoothly as the sound source moved from the anterior to the posterior quadrant.

Target Detection in a Scenario of Natural Sounds: The Role of Spatial Sound Source Separation

2013 ◽  
Author(s):  
Susanne Mayr ◽  
Gunnar Regenbrecht ◽  
Kathrin Lange ◽  
Albertgeorg Lang ◽  
Axel Buchner
Keyword(s):  
Target Detection ◽  
Sound Source ◽  
Source Separation ◽  
Natural Sounds ◽  
Sound Source Separation ◽  
Spatial Sound

It's only real if you see it: Surround system based 3D sound source modelling in virtual reality

2013 ◽  
Author(s):  
Agoston Torok ◽  
Daniel Mestre ◽  
Ferenc Honbolygo ◽  
Pierre Mallet ◽  
Jean-Marie Pergandi ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Sound Source ◽  
3D Sound
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