Polyphonic musical instrument recognition based on a dynamic model of the spectral envelope

We propose a new method for detecting the musical instru-ments that are present in single-channel mixtures. Such a task is of interest for audio and multimedia content analysis and indexing applications. The approach is based on group-ing sinusoidal trajectories according to common onsets, and comparing each group’s overall amplitude evolution with a set of pre-trained probabilistic templates describing the tem-poral evolution of the spectral envelopes of a given set of in-struments. Classification is based on either an Euclidean or a probabilistic definition of timbral similarity, both of which are compared with respect to detection accuracy