Music transcription consists of transforming an audio signal encoding a music performance in a symbolic representation such as a music score. In this paper, a multimodal and interactive prototype to perform music transcription is presented. The system is oriented to monotimbral transcription, its working domain is music played by a single instrument. This prototype uses three different sources of information to detect notes in a musical audio excerpt. It has been developed to allow a human expert to interact with the system to improve its results. In its current implementation, it offers a limited range of interaction and multimodality. Further development aimed at full interactivity and multimodal interactions is discussed.
[Show abstract][Hide abstract] ABSTRACT: A simple note onset detection system for music is presented in this work. To detect onsets, a 1/12 octave filterbank is simulated
in the frequency domain and the band derivatives in time are considered. The first harmonics of a tuned instrument are close
to the center frequency of these bands and, in most instruments, these harmonics are those with the highest amplitudes. The
goal of this work is to make a musically motivated system which is sensitive on onsets in music but robust against the spectrum
variations that occur at times that do not represent onsets. Therefore, the system tries to find semitone variations, which
correspond to note onsets. Promising results are presented for this real time onset detection system.
Progress in Pattern Recognition, Image Analysis and Applications, 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Havana, Cuba, November 15-18, 2005, Proceedings; 01/2005
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