Enhanced sound localization

Authors:
B. Mungamuru;P. Aarabi
Affiliations:
Dept. of Electr. & Comput. Eng., Univ. of Toronto, Ont., Canada;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Year:
2004

Citing 0
Cited 15

Verifier-tuple for audio-forensic to determine speaker environment

MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
Robust localization and tracking of simultaneous moving sound sources using beamforming and particle filtering

Robotics and Autonomous Systems
Using vision, acoustics, and natural language for disambiguation

Proceedings of the ACM/IEEE international conference on Human-robot interaction
Improving human-robot interaction through adaptation to the auditory scene

Proceedings of the ACM/IEEE international conference on Human-robot interaction
Performance of phase transform for detecting sound sources with microphone arrays in reverberant and noisy environments

Signal Processing
3D-audio matting, postediting, and rerendering from field recordings

EURASIP Journal on Applied Signal Processing
Cough localization for the detection of respiratory diseases in pig houses

Computers and Electronics in Agriculture
Verified speaker localization utilizing voicing level in split-bands

Signal Processing
Discovery of sound sources by an autonomous mobile robot

Autonomous Robots
Evaluating real-time audio localization algorithms for artificial audition in robotics

IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Speaker localization and tracking with a microphone array on a mobile robot using von Mises distribution and particle filtering

Robotics and Autonomous Systems
Sound direction estimation using an artificial ear for robots

Robotics and Autonomous Systems
Enhancing the energy efficiency of wireless-communicated binaural hearing aids for speech separation driven by soft-computing algorithms

Applied Soft Computing
A new adaptive sensor fusion localization method for passive acoustic arrays

Intelligent Decision Technologies
Intelligent acoustic rotor speed estimation for an autonomous helicopter

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

A new approach to sound localization, known as enhanced sound localization, is introduced, offering two major benefits over state-of-the-art algorithms. First, higher localization accuracy can be achieved compared to existing methods. Second, an estimate of the source orientation is obtained jointly, as a consequence of the proposed sound localization technique. The orientation estimates and improved localizations are a result of explicitly modeling the various factors that affect a microphone's level of access to different spatial positions and orientations in an acoustic environment. Three primary factors are accounted for, namely the source directivity, microphone directivity, and source-microphone distances. Using this model of the acoustic environment, several different enhanced sound localization algorithms are derived. Experiments are carried out in a real environment whose reverberation time is 0.1 seconds, with the average microphone SNR ranging between 10-20 dB. Using a 24-element microphone array, a weighted version of the SRP-PHAT algorithm is found to give an average localization error of 13.7 cm with 3.7% anomalies, compared to 14.7 cm and 7.8% anomalies with the standard SRP-PHAT technique.