Performance Configuration Analysis in Portuguese Traditional Music: A Computational Approach

Abstract

I present an analysis of performance configurations in Portuguese traditional music, using computational methods to process field recordings from the A Música Portuguesa A Gostar Dela Própria (MPAGDP) archive. Our approach employs YOLOv11s ("You Only Look Once"), a computer vision system that can detect and count performers in archival footage, allowing us to automatically classify performances into meaningful categories: solo, duo, small, and large ensembles. This computational classification method processed 8122 field recordings with 96% classification accuracy, enabling systematic examination of performance contexts that would be time-consuming through manual analysis. Our analysis reveals significant relationships between performance configuration and musical practice across Portuguese traditions. Solo performers, com- prising 48% of vocal recordings, predominantly appear in narrative and poetic traditions requiring individual expression. Large ensem- bles (21%) maintain collective practices like polyphonic singing tra- ditions. The geographic distribution shows regional traits-Alentejo features large-ensemble singing traditions, while northern regions favor solo performances. The temporal analysis traces how tra- ditional forms maintain continuity through specific performance configurations, while contemporary adaptations emerge primarily in small group formats, illuminating the social dimensions of musi- cal transmission and adaptation in Portuguese traditional music.