Tracking melodic patterns in flamenco singing by analyzing polyphonic music recordings

Abstract

The purpose of this paper is to present an algorithmic pipeline for melodic pattern detection in audio files. Our method follows a two-stage approach: first, vocal pitch sequences are extracted from the audio recordings by means of a predominant fundamental frequency estimation technique; second, instances of the patterns are detected directly in the pitch sequences by means of a dynamic programming algorithm which is robust to pitch estimation errors. In order to test the proposed method, an analysis of characteristic melodic patterns in the context of the flamenco fandango style was performed. To this end, a number of such patterns were defined in symbolic format by flamenco experts and were later detected in music corpora, which were composed of un-segmented audio recordings taken from two fandango styles, namely Valverde fandangos and Huelva capital fandangos. These two styles are representative of the fandango tradition and also differ with respect to their musical characteristics. Finally, the strategy in the evaluation of the algorithm performance was discussed by flamenco experts and their conclusions are presented in this paper.