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We propose a new method for detecting the musical instruments 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 grouping sinusoidal trajectories according to common onsets, and comparing each group's overall amplitude evolution with a set of pre-trained probabilistic templates describing the temporal evolution of the spectral envelopes of a given set of instruments. Classification is based on either an Euclidean or a probabilistic definition of timbral similarity, both of which are compared with respect to detection accuracy.