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Self-organized adaptive processor for solving the cocktail party problem

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14:00-15:00 Monday Mar 27, 2006
IMM BUILDING 321 ROOM 053
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Prof. Simon Haykin
Director, Adaptive Systems Laboratory
McMaster University,
Hamilton, ON Canada
	    

Abstract

In this lecture, I first highlight the important aspects of the cocktail party problem (CCP). These highlights set the stage of the description of a self-organized adaptive processor for solving the CPP. Design of the processor is motivated by neurobiological considerations of the human auditory system. Specifically, the processor is binaural, consisting of three functional blocks: 1. Pre-processor for extracting four acoustic cues: Interaural time difference (ITD), Interaural intensity difference (IID), Onset and Pitch. The cues provide the basis for separating the target signal from background noise. Moreover, the two spatial cues provide the means for focusing attention on the target signal. 2. Fusion scheme for combining the cues considered to belong to the target signal. 3. Adaptive smoother for suppressing musical noise, a function that is achieved by feeding back the extracted spatial cues to the input of the smoother. The lecture will finish by presenting audio recordings under different signal-to-noise ratios and varying reverberant conditions. The recordings will demonstrate the impressive performance of the new processor. Simon Haykin is a pioneer in signal processing and machine learning, author of several widely used textbooks, for more information:

http://soma.mcmaster.ca/Haykin/Haykin.html

Host

Prof. Lars Kai Hansen
Informatics and Mathematical Modelling
Technical University of Denmark B321
DK-2800 Kgs. Lyngby - DENMARK
Tel: (+45) 45253889 Fax: (+45) 45872599
WWW: www.imm.dtu.dk/~lkh
	      

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