NDLI: A linear phase unwrapping method for binaural sound source localization on a robot

Content Provider	IEEE Xplore Digital Library
Author	Danfeng Li Levinson, S.E.
Copyright Year	2002
Description	Author affiliation: Language Acquisition & Robotics Lab., Illinois Univ., Urbana, IL, USA (Danfeng Li; Levinson, S.E.)
Abstract	A robust linear phase unwrapping method is proposed to solve the 2/spl pi/ discontinuities in the phase of the cross power spectrum from the binaural inputs using two omnidirectional microphones. The relative incident angle of the interested sound is then estimated according to the time difference of arrival (TDOA) which is obtained from the unwrapped phase of the cross power spectrum. The frequency components associated with the high power are clustered into groups by the phase and frequency distance, and the dominant group is then used to obtain the initial slope estimation. The phase is unwrapped by checking the difference between the actual and the predicted phase by the estimated slope. The re-estimation is then performed by the unwrapped phase. The algorithm is tested under different incident angles and signal to noise ratio (SNR) using real speech signal and white Gaussian noise. The simulation results show the high accuracy and the robustness. This method is also Implemented to control a robot to adaptively adjust itself to the position facing the sound source directly. The satisfactory result was achieved in an open house demonstration.
Sponsorship	IEEE Robotics & Autom. Soc
Starting Page	19
Ending Page	23
File Size	403228
Page Count	5
File Format	PDF
ISBN	0780372727
DOI	10.1109/ROBOT.2002.1013333
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-05-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robots Phase estimation Frequency estimation Signal to noise ratio Robustness Microphones Time difference of arrival Testing Speech enhancement Gaussian noise
Content Type	Text
Resource Type	Article

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