NOTE ONSET DETECTION FOR THE TRANSCRIPTION OF POLYPHONIC PIANO MUSIC

被引：0

作者：

Boogaart, C. G. V. D. ^{[1
]}

Lienhart, R. ^{[1
]}

机构：

[1] Univ Augsburg, Multimedia Comp Lab, D-86159 Augsburg, Germany

来源：

ICME: 2009 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-3 | 2009年

关键词：

Acoustic signal detection; Spectral analysis; Feature extraction; Pattern classification; AUDIO SIGNALS; EXTRACTION; MODELS; MELODY;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Transcription of music is the process of generating a symbolic representation such as a score sheet or a MIDI file from an audio recording of a piece of music. A statistical machine learning approach for detecting note onsets in polyphonic piano music is presented. An area from the spectrogram of the sound is concatenated into one feature vector. A cascade of boosted classifiers is used for dimensionality reduction and classification in an one-versus-all manner The presented system achieves an accuracy of 87.4% in onset detection outperforming the best comparison system by 25.1%.

引用

页码：446 / 449

页数：4

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