Title :
Automatic music transcription supporting different instruments
Author :
Bruno, I. ; Monni, S.L. ; Nesi, P.
Author_Institution :
Dept. of Syst. & Inf., Florence Univ., Italy
Abstract :
The automatic music recognition from an audio performance is a key problem and a challenge for coding music in western music notation in the digital world. This problem has been addressed in several manners and suitable results obtained when a single and specific instrument and monophonic music are processed. The aim is the development of a system for the automatic music transcription being able to recognise and cope with different music instruments. Experimental results have shown that for monophonic pieces the recognition is quite viable, while for polyphonic pieces several problems still exist.
Keywords :
audio signal processing; music; musical acoustics; musical instruments; neural nets; audio processing; automatic music recognition; beat tracking; monophonic music; pitch recognition; Acoustic signal detection; Autocorrelation; Data mining; Detection algorithms; Frequency domain analysis; Humans; Informatics; Instruments; Multiple signal classification; Psychology;
Conference_Titel :
Web Delivering of Music, 2003. 2003 WEDELMUSIC. Proceedings. Third International Conference on
Print_ISBN :
0-7695-1935-0
DOI :
10.1109/WDM.2003.1233871