AES Store

Journal Forum

Reflecting on Reflections - June 2014

Audibility of a CD-Standard A/DA/A Loop Inserted into High-Resolution Audio Playback - September 2007

Quiet Thoughts on a Deafening Problem - May 2014
1 comment

Access Journal Forum

AES E-Library

Co-talker Separation Using the 'Cocktail Party Effect'

An artificial neural network (ANN) speech-classifier-controlled iterative filtering system is described, which simulates the cocktail party effect for speech separation. The ANN speech classifier controls a modified iterative Wiener filter to cancel the interference by setting the filter's parameter's and the convergence criterion for the iteration. The proposed system has been employed successfully with multiple-microphone speech acquisition systems for co-talker speech separation. The simulation results have shown that the iterative processing controlled by the neural network consistently provides speech of good quality and intelligibility.

JAES Volume 44 Issue 12 pp. 1084-1096; December 1996
Publication Date:

Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $20 for non-members, $5 for AES members and is free for E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:

Start a discussion about this paper!

Facebook   Twitter   LinkedIn   Google+   YouTube   RSS News Feeds  
AES - Audio Engineering Society