DocumentCode :
1296126
Title :
Multiple Fundamental Frequency Estimation and Polyphony Inference of Polyphonic Music Signals
Author :
Yeh, Chunghsin ; Roebel, Axel ; Rodet, Xavier
Author_Institution :
Inst. de Rech. et Coordination Acoust./Musique (IRCAM), Paris, France
Volume :
18
Issue :
6
fYear :
2010
Firstpage :
1116
Lastpage :
1126
Abstract :
This paper presents a frame-based system for estimating multiple fundamental frequencies (F0s) of polyphonic music signals based on the short-time Fourier transform (STFT) representation. To estimate the number of sources along with their F0s, it is proposed to estimate the noise level beforehand and then jointly evaluate all the possible combinations among pre-selected F0 candidates. Given a set of F0 hypotheses, their hypothetical partial sequences are derived, taking into account where partial overlap may occur. A score function is used to select the plausible sets of F0 hypotheses. To infer the best combination, hypothetical sources are progressively combined and iteratively verified. A hypothetical source is considered valid if it either explains more energy than the noise, or improves significantly the envelope smoothness once the overlapping partials are treated. The proposed system has been submitted to Music Information Retrieval Evaluation eXchange (MIREX) 2007 and 2008 contests where the accuracy has been evaluated with respect to the number of sources inferred and the precision of the F0s estimated. The encouraging results demonstrate its competitive performance among the state-of-the-art methods.
Keywords :
Fourier transforms; acoustic signal processing; frequency estimation; MIREX; STFT; hypothetical source; multiple fundamental frequency estimation; music information retrieval evaluation exchange; polyphonic music signals; polyphony inference; short-time Fourier transform; Automatic music transcription; frequency estimation; music information retrieval; noise estimation; signal analysis; source separation;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TASL.2009.2030006
Filename :
5200519
Link To Document :
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