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This paper addresses the topic of note, cut and strike detection in Irish traditional music (ITM). In order to do this we first evaluate state of the art onset detection methods for identifying note boundaries. Our method utilises the results from manually and automatically segmented flute recordings. We then demonstrate how this information may be utilised for the detection of notes and single note articulations idiomatic of this genre for the purposes of player style identification. Results for manually annotated onsets achieve 86%, 70% and 74% accuracies for note, cut and strike classification respectively. Results for automatically segmented recordings are considerably, lower therefore we perform an analysis of the onset detection results per event class to establish which musical patterns contain the most errors.
Ali-MacLachlan, I., Tomczak, M., Southall, C., Hockman, J. (2016). Note, cut and strike detection for traditional Irish flute recordings.6th International Workshop on Folk Music Analysis, Dublin, 15-17 June, 2016.