Comunicació presentada al 8th International Workshop on Folk Music Analysis celebrat del 26 al 29 de juny de 2018 a Tessalònica, Grècia.

This work deals with the automatic transcription and characterization of flamenco guitar, with a focus on short melodic interludes improvised between sung verses. These are called falsetas in the flamenco argot and are very challenging for manual and automatic transcription due to their fast and highly ornamented nature. However, they are a key resource for guitar players to practice. We adapted a state of the art singing transcription algorithm to process an audio signal containing one or several guitar falsetas and extract their symbolic representation. The algorithms first perform a segmentation to locate the guitar fragments and then a symbolic transcription of these segments into symbolic representation. In order to evaluate it, we collected the first (to our knowledge) annotated falseta datasets. Our results confirm the difficulty of the task, and a detailed study of two transcriptions revealed that combining the algorithm with specific musical knowledge about the scale used by the song, improves the performance of the system. Our approach follows the principles of research reproducibility, and the system is integrated in a computer-assisted paradigm, where the user complements the automatic annotation with a priory knowledge to generate a final transcription.

This work is partially supported by the Spanish Ministry of Economy and Competitiveness under the CASAS project (TIN2015-70816-R).