Skip to main content
Article thumbnail
Location of Repository

Combining time-delayed decorrelation and ICA: Towards solving the cocktail party problem

By Te-won Lee and Reinhold Orglmeister


We present methods to separate blindly mixed signals recorded in a room. The learning algorithm is based on the information maximization in a single layer neural network. We focus on the implementation of the learning algorithm and on issues that arise when separating speakers in room recordings. We used an infomax approach in a feedforward neural network implemented in the frequency domain using the polynomial filter matrix algebra technique. Fast convergence speed was achieved by using a time-delayed decorrelation method as a preprocessing step. Under minimum-phasemixing conditions this preprocessing step was sufficient for the separation of signals. These methods successfully separated a recorded voice with music in the background(cocktail party problem). Finally, we discuss problems that arise in real world recordings and their potential solutions. 1

Year: 1998
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.