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arxiv 2311.08350 v2 pith:JLXMBQNE submitted 2023-11-14 cs.SD cs.IReess.AS

ChoralSynth: Synthetic Dataset of Choral Singing

classification cs.SD cs.IReess.AS
keywords singingchoralcuratedatasetmethodologyresearchworkaddress
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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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  1. Music I Care About: Automated Multimodal Benchmarking of LLM Music Perception Skills on (Almost) Any Music

    cs.SD 2026-07 unverdicted novelty 6.0

    A meta-benchmark that auto-generates multimodal music-perception multiple-choice tests from user symbolic music, demonstrated on ChoraleBricks with text-only and white-noise controls.