Music recognition using note transition context

As a typical example of sound-mixture recognition, the recognition of ensemble music is addressed. Here music recognition is defined as recognizing the pitch and the name of an instrument for each musical note in monaural or stereo recordings of real music performances. The first key part of the pro...

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Bibliographic Details
Published inProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181) Vol. 6; pp. 3593 - 3596 vol.6
Main Authors Kashino, K., Murase, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1998
Subjects
Disk recording
Frequency
History
Indexing
Instruments
Laboratories
Multiple signal classification
Performance analysis
Signal analysis
Signal processing
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Summary:As a typical example of sound-mixture recognition, the recognition of ensemble music is addressed. Here music recognition is defined as recognizing the pitch and the name of an instrument for each musical note in monaural or stereo recordings of real music performances. The first key part of the proposed method is adaptive template matching that can cope with variability in musical sounds. This is employed in the hypothesis-generation stage. The second key part of the proposed method is musical context integration based on the probabilistic networks. This is employed in the hypothesis-verification stage. The evaluation results clearly show the advantages of these two processes.
ISBN:9780780344280
0780344286
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.1998.679655