Abstract
Notating a music piece is not a trivial task. It requires
training and experience. This is challenging for new and inexperienced musicians. Automated transcription systems can be very useful in such cases. A piece generally consists of multiple instruments and it is essential to separate them prior to transcription. The challenge aggravates even more when multiples modulations or varieties of the same instrument are present. This is common in the nowadays and hence, it is essential to distinguish different varieties of the same instrument prior to transcription. In this paper, a line spectral frequency-based approach is presented for this task. Experiments were performed with clips of different lengths from 6 and a highest accuracy of 97.06% was obtained.
Keywords Inter instrument variety ·Music signal processing ·Lead
instrument identification ·Line spectral frequency.
training and experience. This is challenging for new and inexperienced musicians. Automated transcription systems can be very useful in such cases. A piece generally consists of multiple instruments and it is essential to separate them prior to transcription. The challenge aggravates even more when multiples modulations or varieties of the same instrument are present. This is common in the nowadays and hence, it is essential to distinguish different varieties of the same instrument prior to transcription. In this paper, a line spectral frequency-based approach is presented for this task. Experiments were performed with clips of different lengths from 6 and a highest accuracy of 97.06% was obtained.
Keywords Inter instrument variety ·Music signal processing ·Lead
instrument identification ·Line spectral frequency.
| Original language | English (US) |
|---|---|
| Number of pages | 7 |
| State | Published - Nov 2 2021 |