DocumentCode :
231590
Title :
Novel approach to separation of musical signal sources by NMF
Author :
Yazawa, Sakurako ; Hamanaka, Masatoshi ; Utsuro, Takehito
Author_Institution :
Grad. Sch. of Syst. & Inf. Eng., Univ. of Tsukuba, Tsukuba, Japan
fYear :
2014
fDate :
19-23 Oct. 2014
Firstpage :
610
Lastpage :
615
Abstract :
This paper proposes a method to separate polyphonic music signal into signals of each musical instrument by NMF: Non-negative Matrix Factorization based on preservation of spectrum envelope. Sound source separation is taken as a fundamental issue in music signal processing and NMF is becoming common to solve it because of its versatility and compatibility with music signal processing. Our method bases on a common feature of harmonic signal: spectrum envelopes of musical signal in close pitches played by the harmonic music instrument would be similar. We estimate power spectrums of each instrument by NMF with restriction to synchronize spectrum envelope of bases which are allocated to all possible center frequencies of each instrument. This manipulation means separation of components which refers to tones of each instrument and realizes both of separation without pre-training and separation of signal including harmonic and non-harmonic sound. We had an experiment to decompose mixture sound signal of MIDI instruments into each instrument and evaluated the result by SNR of single MIDI instrument sound signals and separated signals. As a result, SNR of lead guitar and drums approximately marked 3.6 and 6.0 dB and showed significance of our method.
Keywords :
acoustic signal processing; source separation; NMF; harmonic music instrument; music signal processing; musical signal sources separation; nonnegative matrix factorization; polyphonic music signal; sound source separation; spectrum envelope preservation; Cost function; Harmonic analysis; Instruments; Lead; Multiple signal classification; Source separation; Spectrogram; NMF; polyphonic music signal separation; spectrum envelope preservation; unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing (ICSP), 2014 12th International Conference on
Conference_Location :
Hangzhou
ISSN :
2164-5221
Print_ISBN :
978-1-4799-2188-1
Type :
conf
DOI :
10.1109/ICOSP.2014.7015076
Filename :
7015076
Link To Document :
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