Subject: Musical style recognition. From: Pino Buzzanca <g_buzzanca(at)VIRGILIO.IT> Date: Tue, 21 Sep 2004 22:17:02 +0200Dear List, I'm using a back-propagation neural network to recognize musical style. The idea is to provide the network with several vectors, each vector representing a musical phrase. Training test consists of several musical phrases belonging to 5 different composers (who all lived in the 17th century). Input layer consists of neurons with Vector Input (out of four input units for each note, two encode rhythmic information, and two encode pitch information). I'm now concerned with the necessity to account for musical input of varying length in an even manner: in other words the problem is that the network's structure requires me to encode musical phrases in fixed-width representations (!) and this is not realistic in comparison to real life (I mean the 'amputation' of musical stimuli into fixed-width sequences, cfr. Sloboda 1985). Any ideas on segmentation possibilities that seem plausible from the cognitive/auditory/methodological standpoint? Thanks a lot in advance, Giuseppe Buzzanca. ========================================== Giuseppe Buzzanca Professor of Music State Conservatory of Music Via Brigata Bari, 26 70124 Bari ITALY tel. +39 (080) 574 0022 fax +39 (080) 579 4461 g_buzzanca(at)virgilio.it