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Erkomaishvili Dataset: A Curated Corpus of Traditional Georgian Vocal Music for Computational Musicology
Author(s) -
Sebastian Rosenzweig,
Frank Scherbaum,
David Shugliashvili,
Vlora Arifi-Müller,
Meinard Müller
Publication year - 2020
Publication title -
transactions of the international society for music information retrieval
Language(s) - English
Resource type - Journals
ISSN - 2514-3298
DOI - 10.5334/tismir.44
Subject(s) - georgian , musicology , computer science , speech recognition , music information retrieval , natural language processing , sound recording and reproduction , artificial intelligence , information retrieval , linguistics , musical , art , visual arts , acoustics , philosophy , physics
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.

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