VocalSet: A Singing Voice Dataset

By J. Wilkins, Prem Seetharaman, Alison Wahl, Bryan Pardo. 2018

123 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Icassp 2022 Deep Noise Suppression Challenge (2022, background): “English singing voice data consists of high-quality audio recordings from professional singers contained in VocalSet corpus [10].”
Interspeech 2021 Deep Noise Suppression Challenge (2021, methodology): “This subset is derived from VocalSet corpus [13] with Creative Commons Attribution 4.”
ICASSP 2021 Deep Noise Suppression Challenge (2020, methodology): “This subset is derived from VocalSet corpus [12] with Creative Commons Attribution 4.”
A Survey on Recent Deep Learning-driven Singing Voice Synthesis Systems (2021, background): “Furthermore, due to copyright concerns, there are very few such datasets and those that are publicly available are usually conﬁned to singing old folk songs without copy-right [24]–[26].”
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training (2023, methodology): “Vocal technique detection and singer identification are performed using the VocalSet dataset (Wilkins et al., 2018), with accuracy as the evaluation metric.”