Generation of Musical Scores of Percussive Un-Pitched Instruments from Automatically Detected Events

This publication addresses the generation of a musical score of percussive un-pitched instruments. A musical event is defined as the occurrence of a sound of a musical instrument. The presented method is restricted to events of percussive instruments without determinate pitch. Events are detected in the audio signal and classified into instrument classes, the temporal positions of the events are quantized on a tatum grid, musical meter is estimated and preparatory beats are identified. The identification of rhythmic patterns on basis of the frequency of their occurrence enables a robust identification of the tempo and gives valuable cues for the positioning of the bar lines using musical knowledge.

[1]  Jean Laroche,et al.  Audio segmentation by feature-space clustering using linear discriminant analysis and dynamic programming , 2003, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684).

[2]  Judith C. Brown.  Determination of the meter of musical scores by autocorrelation , 1993 .

[3]  Mark D. Plumbley.  Algorithms for nonnegative independent component analysis , 2003, IEEE Trans. Neural Networks.

[4]  I. Shmulevich,et al.  A system for machine recognition of music patterns , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[5]  Richard W. Hamming,et al.  Coding and Information Theory , 1980 .

[6]  Jonathan Foote,et al.  Automatic audio segmentation using a measure of audio novelty , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[7]  J. Beauchamp,et al.  Fundamental frequency estimation of musical signals using a two‐way mismatch procedure , 1994 .

[8]  Christian Uhle,et al.  Further Steps towards Drum Transcription of Polyphonic Music , 2004 .

[9]  Anssi Klapuri,et al.  Measuring the similarity of Rhythmic Patterns , 2002, ISMIR.

[10]  Mark Sandler,et al.  Segmentation of Musical Signals Using Hidden Markov Models. , 2001 .

[11]  Mark D. Plumbley.  Algorithms for Non-Negative Independent Component Analysis , 2002 .

[12]  Fabien Gouyon,et al.  Determination of the meter of musical audio signals: Seeking recurrences in beat segment descriptors , 2003 .

[13]  Hideki Kawahara,et al.  YIN, a fundamental frequency estimator for speech and music. , 2002, The Journal of the Acoustical Society of America.

[14]  A. Klapuri,et al.  MUSICAL METER ESTIMATION AND MUSIC TRANSCRIPTION , 2000 .

[15]  R. Jackendoff,et al.  A Generative Theory of Tonal Music , 1985 .

[16]  Joseph T. Wells.  Timing Is of the Essence , 2001 .

[17]  Grosvenor W. Cooper,et al.  The Rhythmic Structure of Music , 1971 .

[18]  Jarno Sepp nen.  TATUM GRID ANALYSIS OF MUSICAL SIGNALS , 2001 .

[19]  Eric D. Scheirer,et al.  Tempo and beat analysis of acoustic musical signals. , 1998, The Journal of the Acoustical Society of America.

[20]  Godfried T. Toussaint,et al.  A Mathematical Analysis of African, Brazilian, and Cuban Clave Rhythms , 2002 .