TY - CONF
T1 - Spotting a query phrase from polyphonic music audio signals based on semi-supervised nonnegative matrix factorization
AU - Masuda, Taro
AU - Yoshii, Kazuyoshi
AU - Goto, Masataka
AU - Morishima, Shigeo
N1 - Funding Information:
Acknowledgment: This study was supported in part by the JST OngaCREST project.
Funding Information:
This study was supported in part by the JST OngaCREST project.
Publisher Copyright:
© Taro Masuda, Kazuyoshi Yoshii, Masataka Goto, Shigeo Morishima.
PY - 2014
Y1 - 2014
N2 - This paper proposes a query-by-audio system that aims to detect temporal locations where a musical phrase given as a query is played in musical pieces. The “phrase” in this paper means a short audio excerpt that is not limited to a main melody (singing part) and is usually played by a single musical instrument. A main problem of this task is that the query is often buried in mixture signals consisting of various instruments. To solve this problem, we propose a method that can appropriately calculate the distance between a query and partial components of a musical piece. More specifically, gamma process nonnegative matrix factorization (GaP-NMF) is used for decomposing the spectrogram of the query into an appropriate number of basis spectra and their activation patterns. Semi-supervised GaP-NMF is then used for estimating activation patterns of the learned basis spectra in the musical piece by presuming the piece to partially consist of those spectra. This enables distance calculation based on activation patterns. The experimental results showed that our method outperformed conventional matching methods.
AB - This paper proposes a query-by-audio system that aims to detect temporal locations where a musical phrase given as a query is played in musical pieces. The “phrase” in this paper means a short audio excerpt that is not limited to a main melody (singing part) and is usually played by a single musical instrument. A main problem of this task is that the query is often buried in mixture signals consisting of various instruments. To solve this problem, we propose a method that can appropriately calculate the distance between a query and partial components of a musical piece. More specifically, gamma process nonnegative matrix factorization (GaP-NMF) is used for decomposing the spectrogram of the query into an appropriate number of basis spectra and their activation patterns. Semi-supervised GaP-NMF is then used for estimating activation patterns of the learned basis spectra in the musical piece by presuming the piece to partially consist of those spectra. This enables distance calculation based on activation patterns. The experimental results showed that our method outperformed conventional matching methods.
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M3 - Paper
AN - SCOPUS:84973290458
SP - 227
EP - 232
T2 - 15th International Society for Music Information Retrieval Conference, ISMIR 2014
Y2 - 27 October 2014 through 31 October 2014
ER -