New high capacity optical discs and high bandwidth networks provide the capability for delivering multichannel audio. Although there are many one-and two-channel recordings in existence, only a handful of multichannel recordings exist. In this paper we propose a neural network approach that can synthesize microphone signals with the correct acoustical characteristics of specific venues that have been characterized in advance. These signals can be used to generate a multichannel recording with the acoustical characteristics of the original venue. The complex semi-cepstrum technique is employed to extract features from musical signals recorded in a venue and these signals are sent into the fuzzy cerebellar model articulation controller (FCMAC) for training.

Authors: Kyriakakis, Chris; Lin, Ching-Shun
Affiliation: Immersive Audio Laboratory, Integrated Media Systems Center, Univ. of Southern California, Los Angeles, CA
AES Convention: 113 (October 2002) Paper Number: 5675
Publication Date: October 1, 2002
Subject: Multichannel Sound

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