TY - GEN
T1 - Instrument equalizer for query-by-example retrieval
T2 - 9th International Conference on Music Information Retrieval, ISMIR 2008
AU - Itoyama, Katsutoshi
AU - Goto, Masataka
AU - Komatani, Kazunori
AU - Ogata, Tetsuya
AU - Okuno, Hiroshi G.
PY - 2008
Y1 - 2008
N2 - This paper describes a music remixing interface, called Instrument Equalizer, that allows users to control the volume of each instrument part within existing audio recordings in real time. Although query-by-example retrieval systems need a user to prepare favorite examples (songs) in general, our interface gives a user to generate examples from existing ones by cutting or boosting some instrument/vocal parts, resulting in a variety of retrieved results. To change the volume, all instrument parts are separated from the input sound mixture using the corresponding standard MIDI file. For the separation, we used an integrated tone (timbre) model consisting of harmonic and inharmonic models that are initialized with template sounds recorded from a MIDI sound generator. The remaining but critical problem here is to deal with various performance styles and instrument bodies that are not given in the template sounds. To solve this problem, we train probabilistic distributions of timbre features by using various sounds. By adding a new constraint of maximizing the likelihood of timbre features extracted from each tone model, we succeeded in estimating model parameters that better express actual timbre.
AB - This paper describes a music remixing interface, called Instrument Equalizer, that allows users to control the volume of each instrument part within existing audio recordings in real time. Although query-by-example retrieval systems need a user to prepare favorite examples (songs) in general, our interface gives a user to generate examples from existing ones by cutting or boosting some instrument/vocal parts, resulting in a variety of retrieved results. To change the volume, all instrument parts are separated from the input sound mixture using the corresponding standard MIDI file. For the separation, we used an integrated tone (timbre) model consisting of harmonic and inharmonic models that are initialized with template sounds recorded from a MIDI sound generator. The remaining but critical problem here is to deal with various performance styles and instrument bodies that are not given in the template sounds. To solve this problem, we train probabilistic distributions of timbre features by using various sounds. By adding a new constraint of maximizing the likelihood of timbre features extracted from each tone model, we succeeded in estimating model parameters that better express actual timbre.
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M3 - Conference contribution
AN - SCOPUS:80052051446
SN - 9780615248493
T3 - ISMIR 2008 - 9th International Conference on Music Information Retrieval
SP - 133
EP - 138
BT - ISMIR 2008 - 9th International Conference on Music Information Retrieval
Y2 - 14 September 2008 through 18 September 2008
ER -