Papers › ChoralSynth: Synthetic Dataset of Choral Singing
ChoralSynth: Synthetic Dataset of Choral Singing
Jyoti Narang, Viviana De La Vega, Xavier Lizarraga, Oscar Mayor, Hector Parra, Jordi Janer, Xavier Serra
Choral singing, a widely practiced form of ensemble singing, lacks comprehensive datasets in the realm of Music Information Retrieval (MIR) research, due to challenges arising from the requirement to curate multitrack recordings. To address this, we devised a novel methodology, leveraging state-of-the-art synthesizers to create and curate quality renditions. The scores were sourced from Choral Public Domain Library(CPDL). This work is done in collaboration with a diverse team of musicians, software engineers and researchers. The resulting dataset, complete with its associated metadata, and methodology is released as part of this work, opening up new avenues for exploration and advancement in the field of singing voice research.
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