Creating an A Cappella Singing Audio Dataset for Automatic Jingju Singing Evaluation Research

TL;DR

This paper introduces a comprehensive a cappella jingju singing dataset with 120 arias and detailed annotations, aimed at advancing automatic singing evaluation research in Beijing opera.

Contribution

It provides the first extensive, annotated a cappella jingju singing dataset, extending existing resources for research and development in this field.

Findings

Dataset includes 120 arias and 1265 melodic lines.

Contains annotations suitable for automatic singing evaluation.

Data is openly available online.

Abstract

The data-driven computational research on automatic jingju (also known as Beijing or Peking opera) singing evaluation lacks a suitable and comprehensive a cappella singing audio dataset. In this work, we present an a cappella singing audio dataset which consists of 120 arias, accounting for 1265 melodic lines. This dataset is also an extension our existing CompMusic jingju corpus. Both professional and amateur singers were invited to the dataset recording sessions, and the most common jingju musical elements have been covered. This dataset is also accompanied by metadata per aria and melodic line annotated for automatic singing evaluation research purpose. All the gathered data is openly available online.