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Automatic transcription of pitched and unpitched sounds from polyphonic music

Benetos, E., Ewert, S. and Weyde, T. (2014). Automatic transcription of pitched and unpitched sounds from polyphonic music. Paper presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing, 4 - 9 May 2014, Florence, Italy.

Abstract

Automatic transcription of polyphonic music has been an active research field for several years and is considered by many to be a key enabling technology in music signal processing. However, current transcription approaches either focus on detecting pitched sounds (from pitched musical instruments) or on detecting unpitched sounds (from drum kits). In this paper, we propose a method that jointly transcribes pitched and unpitched sounds from polyphonic music recordings. The proposed model extends the probabilistic latent component analysis algorithm and supports the detection of pitched sounds from multiple instruments as well as the detection of unpitched sounds from drum kit components, including bass drums, snare drums, cymbals, hi-hats, and toms. Our experiments based on polyphonic Western music containing both pitched and unpitched instruments led to very encouraging results in multi-pitch detection and drum transcription tasks.

Publication Type: Conference or Workshop Item (Paper)
Subjects: M Music and Books on Music > M Music
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
URI: http://openaccess.city.ac.uk/id/eprint/3268
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