Hierarchical neuro-fuzzy systems

Authors:
M. Vellasco;M. Pacheco;K. Figueiredo
Affiliations:
Applied Computational Intelligence Lab., Department of Electrical Engineering, PUC-Rio, Rio de Janeiro, RJ, Brazil and Department of Computer and Systems Engineering, UERJ;Applied Computational Intelligence Lab., Department of Electrical Engineering, PUC-Rio, Rio de Janeiro, RJ, Brazil and Department of Computer and Systems Engineering, UERJ;Applied Computational Intelligence Lab., Department of Electrical Engineering, PUC-Rio, Rio de Janeiro, RJ, Brazil
Venue:
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Year:
2003

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Abstract

Robot audition in the real world should cope with environment noises and reverberation and motor noises caused by the robot's own movements. This paper presents the active direction-pass filter (ADPF) to separate sounds originating from the specified direction with a pair of microphones. The ADPF is implemented by hierarchical integration of visual and auditory processing with hypothetical reasoning on interaural phase difference (IPD) and interaural intensity difference (IID) for each subband. In creating hypotheses, the reference data of IPD and IID is calculated by the auditory epipolar geometry on demand. Since the performance of the ADPF depends on the direction, the ADPF controls the direction by motor movement. The human tracking and sound source separation based on the ADPF is implemented on an upper-torso humanoid and runs in realtime with 4 PCs connected over Gigabit ethernet. The signal-to-noise ratio (SNR) of each sound separated by the ADPF from a mixture of two speeches with the same loudness is improved to about 10 dB from 0 dB.