In this paper we introduce a simple and fast method for realtime recognition of multiple pitches produced by multiple musical instruments. Our proposed method is based on two important facts: (1) that timbral information of any instrument is pitch-dependant and (2) that the modulation spectrum of the same pitch seems to result into a persistent representation of the characteristics of the instrumental family. Using these basic facts, we construct a learning algorithm to obtain pitch templates of all possible notes on various instruments and then devise an online algorithm to decompose a realtime audio buffer using the learned templates. The learning and decomposition proposed here are inspired by non-negative matrix factorization methods but differ by introduction of an explicit sparsity control. Our test results show promising recognition rates for a realtime system on real music recordings. We discuss further improvements that can be made over the proposed system.

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Spectral delays have been used for a long time as a way to colour and shape spectral characteristics of sound. Most of available software is controlled by drawing an envelope on a window that represents spectral bins, and by setting a maximum delay time. Despite its comfort, such a simplistic approach does not imply any methods for allowing symbolic manipulations on spectral data that are often required by composers and sound designers. Chromax proposes an alternative dynamic parameterization of spectral delays, allowing fine and complex compositional manipulations. It implements a bin-synchronous spectral processing using the new Gen~ technology available in Max6 [1], and provides algorithms to dynamically specify a filter, a delay and a feedback level for each bin of a processed sound.

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