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Erkomaishvili Dataset: A Curated Corpus of Traditional Georgian Vocal Music for Computational Musicology Cover

Erkomaishvili Dataset: A Curated Corpus of Traditional Georgian Vocal Music for Computational Musicology

Open Access
|Apr 2020

Abstract

The analysis of recorded audio material using computational methods has received increased attention in ethnomusicological research. We present a curated dataset of traditional Georgian vocal music for computational musicology. The corpus is based on historic tape recordings of three-voice Georgian songs performed by the the former master chanter Artem Erkomaishvili. In this article, we give a detailed overview of the audio material, transcriptions, and annotations contained in the dataset. Beyond its importance for ethnomusicological research, this carefully organized and annotated corpus constitutes a challenging scenario for music information retrieval tasks such as fundamental frequency estimation, onset detection, and score-to-audio alignment. The corpus is publicly available and accessible through score-following web-players.
DOI: https://doi.org/10.5334/tismir.44 | Journal eISSN: 2514-3298
Language: English
Submitted on: Oct 21, 2019
Accepted on: Feb 3, 2020
Published on: Apr 10, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 Sebastian Rosenzweig, Frank Scherbaum, David Shugliashvili, Vlora Arifi-Müller, Meinard Müller, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.