Improving multiple-F0 estimation by onset detection for polyphonic music transcription

In a monaural polyphonic context, music transcription and specifically, multiple-F0 estimation systems have achieved promising results in the last decade. However, most of these systems present intermittent misses of pitch within a note or inaccurate definitions about onsets and offsets due to frame-by-frame analysis. In this paper, we propose a multiple-F0 estimation system which extracts a set of active pitches at each frame (analysis frame) but note tracking is performed defining temporal intervals by an accurate onset detector. Our system shows promising results, in terms of onset and multiple-F0 estimation, to be evaluated using real-world and synthesized polyphonic music recordings taken from MAPS music database.

[1]  Valentin Emiya.  Transcription automatique de la musique de piano , 2008 .

[2]  France,et al.  Onset Detection in Polyphonic Signals by means of Transient Peak Classification , 2005 .

[3]  Matija Marolt.  Transcription of polyphonic piano music with neural networks , 2000, 2000 10th Mediterranean Electrotechnical Conference. Information Technology and Electrotechnology for the Mediterranean Countries. Proceedings. MeleCon 2000 (Cat. No.00CH37099).

[4]  Richard Heusdens,et al.  A new psychoacoustical masking model for audio coding applications , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  J. J. Carabias-Orti,et al.  Note-event Detection in Polyphonic Musical Signals based on Harmonic Matching Pursuit and Spectral Smoothness , 2008 .

[6]  P. Vera-Candeas,et al.  Sinusoidal modelling using perceptual matching pursuits in the bark scale for parametric audio coding , 2006 .

[7]  Roland Badeau,et al.  Automatic transcription of piano music based on HMM tracking of jointly-estimated pitches , 2008, 2008 16th European Signal Processing Conference.

[8]  Yannis Stylianou,et al.  Beat Tracking using Group Delay Based Onset Detection , 2008, ISMIR.

[9]  Mark R. Every,et al.  Separation of synchronous pitched notes by spectral filtering of harmonics , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[10]  Andreas Jakobsson,et al.  Linear AM decomposition for sinusoidal audio coding , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[11]  Enrique Alexandre,et al.  Musical-Inspired Features for Automatic Sound Classification in Digital Hearing Aids , 2008 .

[12]  Daniel P. W. Ellis,et al.  A Discriminative Model for Polyphonic Piano Transcription , 2007, EURASIP J. Adv. Signal Process..

[13]  Jürgen Herre,et al.  Temporal Noise Shaping, Qualtization and Coding Methods in Perceptual Audio Coding: A Tutorial Introduction , 1999 .

[14]  M.P. Ryynanen,et al.  Polyphonic music transcription using note event modeling , 2005, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2005..

[15]  Mert Bay,et al.  Evaluation of Multiple-F0 Estimation and Tracking Systems , 2009, ISMIR.

[16]  Axel Röbel,et al.  Multiple fundamental frequency estimation of polyphonic music signals , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[17]  Barry Vercoe,et al.  Folk Music Classification Using Hidden Markov Models , 2001 .

[18]  F. J. Cañadas Quesada,et al.  A Multiple-F0 Estimation Approach Based on Gaussian Spectral Modelling for Polyphonic Music Transcription , 2010 .

[19]  José Manuel Iñesta Quereda,et al.  Multiple fundamental frequency estimation using Gaussian smoothness , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[20]  Thomas Sikora,et al.  Monaural Source Separation from Musical Mixtures Based on Time-Frequency Timbre Models , 2007, ISMIR.

[21]  Guoning Hu,et al.  Monaural speech organization and segregation , 2006 .