This article deals with automatic transcription of flamenco music recordings—more specifically, a cappella singing. We first study the specifics of flamenco singing and propose a transcription system based on fundamental frequency and energy estimation, which incorporates an iterative strategy for note segmentation and labeling. The proposed approach is evaluated on a music collection of 72 performances, including a variety of singers and recording conditions, and the presence or absence of percussion, background voices, and noise. We obtain satisfying results for the different approaches tested, and our system outperforms a state-of-the-art approach designed for other singing styles. In this study, we discuss the difficulties found in transcribing flamenco singing and in evaluating the obtained transcriptions, we analyze the influence of the different steps of the algorithm, and we state the main limitations of our approach and discuss challenges for future studies.

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