@conference{22009,
author = "Toni Heittola and Anssi Klapuri and Tuomas Virtanen",
abstract = "This paper proposes a novel approach to musical instrument recognition in polyphonic audio signals by using a source-filter model and an augmented non-negative matrix factorization algorithm for sound separation. The mixture signal is decomposed into a sum of spectral bases modeled as a product of excitations and filters. The excitations are restricted to harmonic spectra and their fundamental frequencies are estimated in advance using a multipitch estimator, whereas the filters are restricted to have smooth frequency responses by modeling them as a sum of elementary functions on the Mel-frequency scale. The pitch and timbre information are used in organizing individual notes into sound sources. In the recognition, Mel-frequency cepstral coefficients are used to represent the coarse shape of the power spectrum of sound sources and Gaussian mixture models are used to model instrument-conditional densities of the extracted features. The method is evaluated with polyphonic signals, randomly generated from 19 instrument classes. The recognition rate for signals having six note polyphony reaches 59%.",
address = "Kobe, Japan",
booktitle = "in Proc. 10th Int. Society for Music Information Retrieval Conf. (ISMIR 2009)",
keywords = "instruments;separation;source-filter model",
organization = "International Society for Music Information Retrieval (ISMIR)",
pages = "327-332",
title = "{M}usical {I}nstrument {R}ecognition in {P}olyphonic {A}udio {U}sing {S}ource-{F}ilter {M}odel for {S}ound {S}eparation",
url = "https://www.cs.tut.fi/sgn/arg/klap/ismir09-heittola.pdf",
year = "2009",
}