TY - GEN
T1 - Second fiddle is important too
T2 - 13th International Society for Music Information Retrieval Conference, ISMIR 2012
AU - Bay, Mert
AU - Ehmann, Andreas F.
AU - Beauchamp, James W.
AU - Smaragdis, Paris
AU - Stephen Downie, J.
PY - 2012
Y1 - 2012
N2 - Recently, there has been much interest in automatic pitch estimation and note tracking of polyphonic music. To date, however, most techniques produce a representation where pitch estimates are not associated with any particular instrument or voice. Therefore, the actual tracks for each instrument are not readily accessible. Access to individual tracks is needed for more complete music transcription and additionally will provide a window to the analysis of higher constructs such as counterpoint and instrument theme imitation during a composition. In this paper, we present a method for tracking the pitches (F0s) of individual instruments in polyphonic music. The system uses a pre-learned dictionary of spectral basis vectors for each note for a variety of musical instruments. The method then formulates the tracking of pitches of individual voices in a probabilistic manner by attempting to explain the input spectrum as the most likely combination of musical instruments and notes drawn from the dictionary. The method has been evaluated on a subset of the MIREX multiple-F0 estimation test dataset, showing promising results.
AB - Recently, there has been much interest in automatic pitch estimation and note tracking of polyphonic music. To date, however, most techniques produce a representation where pitch estimates are not associated with any particular instrument or voice. Therefore, the actual tracks for each instrument are not readily accessible. Access to individual tracks is needed for more complete music transcription and additionally will provide a window to the analysis of higher constructs such as counterpoint and instrument theme imitation during a composition. In this paper, we present a method for tracking the pitches (F0s) of individual instruments in polyphonic music. The system uses a pre-learned dictionary of spectral basis vectors for each note for a variety of musical instruments. The method then formulates the tracking of pitches of individual voices in a probabilistic manner by attempting to explain the input spectrum as the most likely combination of musical instruments and notes drawn from the dictionary. The method has been evaluated on a subset of the MIREX multiple-F0 estimation test dataset, showing promising results.
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M3 - Conference contribution
AN - SCOPUS:84873461145
SN - 9789727521449
T3 - Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012
SP - 319
EP - 324
BT - Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012
Y2 - 8 October 2012 through 12 October 2012
ER -