TY - GEN
T1 - Instrogram
T2 - 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
AU - Kitahara, Tetsuro
AU - Goto, Masataka
AU - Komatani, Kazunori
AU - Ogata, Tetsuya
AU - Okuno, Hiroshi G.
PY - 2006/12/1
Y1 - 2006/12/1
N2 - This paper describes a new technique for recognizing musical instruments in polyphonic music. Because the conventional framework for musical instrument recognition in polyphonic music had to estimate the onset time and fundamental frequency (F0) of each note, instrument recognition strictly suffered from errors of onset detection and F0 estimation. Unlike such a note-based processing framework, our technique calculates the temporal trajectory of instrument existence probabilities for every possible F0, and the results are visualized with a spectrogram-like graphical representation called instrogram. The instrument existence probability is defined as the product of a nonspecific instrument existence probability calculated using PreFEst and a conditional instrument existence probability calculated using the hidden Markov model. Experimental results show that the obtained instrograms reflect the actual instrumentations and facilitate instrument recognition.
AB - This paper describes a new technique for recognizing musical instruments in polyphonic music. Because the conventional framework for musical instrument recognition in polyphonic music had to estimate the onset time and fundamental frequency (F0) of each note, instrument recognition strictly suffered from errors of onset detection and F0 estimation. Unlike such a note-based processing framework, our technique calculates the temporal trajectory of instrument existence probabilities for every possible F0, and the results are visualized with a spectrogram-like graphical representation called instrogram. The instrument existence probability is defined as the product of a nonspecific instrument existence probability calculated using PreFEst and a conditional instrument existence probability calculated using the hidden Markov model. Experimental results show that the obtained instrograms reflect the actual instrumentations and facilitate instrument recognition.
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M3 - Conference contribution
AN - SCOPUS:33947657531
SN - 142440469X
SN - 9781424404698
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - V229-V232
BT - 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
Y2 - 14 May 2006 through 19 May 2006
ER -