Automatic Transcription of Flamenco Singing from Polyphonic Music Recordings

TL;DR

This paper presents a specialized system for transcribing flamenco singing from polyphonic recordings, overcoming genre-specific challenges by novel melody extraction and segmentation techniques, and outperforming existing systems in accuracy.

Contribution

A new flamenco-specific transcription method that combines melody extraction, contour filtering, and pitch labeling to improve accuracy over existing systems.

Findings

Outperforms state-of-the-art transcription systems in voicing accuracy

Achieves better onset detection in flamenco singing

Demonstrates robustness on flamenco singing datasets

Abstract

Automatic note-level transcription is considered one of the most challenging tasks in music information retrieval. The specific case of flamenco singing transcription poses a particular challenge due to its complex melodic progressions, intonation inaccuracies, the use of a high degree of ornamentation and the presence of guitar accompaniment. In this study, we explore the limitations of existing state of the art transcription systems for the case of flamenco singing and propose a specific solution for this genre: We first extract the predominant melody and apply a novel contour filtering process to eliminate segments of the pitch contour which originate from the guitar accompaniment. We formulate a set of onset detection functions based on volume and pitch characteristics to segment the resulting vocal pitch contour into discrete note events. A quantised pitch label is assigned to each note event by combining global pitch class probabilities with local pitch contour statistics. The proposed system outperforms state of the art singing transcription systems with respect to voicing accuracy, onset detection and overall performance when evaluated on flamenco singing datasets.