Computer-assisted Analysis of Field Recordings: A Case Study of Georgian Funeral Songs

Abstract

Three-voiced funeral songs from Svaneti in North-West Georgia (also referred to as Zär) are believed to represent one of Georgia’s oldest preserved forms of collective music-making. Throughout a Zär performance, the singers often jointly and intentionally drift upwards in pitch. Furthermore, the singers tend to use pitch slides at the beginning and end of sung notes. Musicological studies on tonal analysis or transcription have to account for such musical peculiarities, e.g., by compensating for pitch drifts or identifying stable note events (located between pitch slides). These tasks typically require labor-intensive annotation processes with manual corrections executed by experts with domain knowledge. For instance, in the context of a previous musicological study on pitch inventories (or pitch-class histograms) of Zär performances, ethnomusicologists tediously annotated fundamental frequency (F0) trajectories, stable note events, and pitch drifts for a set of 11 multitrack field recordings. In this article, we study how musicological studies on field recordings can benefit from interactive computational tools that support such annotation processes. As one contribution of this article, we compile a dataset from the previously annotated audio material, which we release under an open-source license for research purposes. As a second contribution, we introduce two computational tools for removing pitch slides and compensating pitch drifts in performances. Our tools were developed in close collaboration with ethnomusicologists and allow for incorporating domain knowledge (e.g., on singing styles or musically relevant harmonic intervals) in the different processing steps. In a case study using our Zär dataset, we evaluate our tools by reproducing the pitch inventories from the original musicological study and subsequently discuss the potential of computer-assisted approaches for interdisciplinary research.