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.
ChoralSynth: Synthetic Dataset of Choral Singing
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
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.
fields
cs.SD 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Music I Care About: Automated Multimodal Benchmarking of LLM Music Perception Skills on (Almost) Any Music
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.