Jingju a cappella singing dataset part1
Creators
- 1. Music Technology Group - Universitat Pompeu Fabra
Description
Description:
This dataset is a collection of boundary annotations of a cappella singing performed by Beijing Opera (Jingju, 京剧) professional and amateur singers.
The boundaries have been annotated in Praat TextGrid format and in a hierarchical way:
- Line (phrase),
- syllable,
- phoneme
singing units have been annotated to a jingju a cappella singing audio dataset.
The corresponding audio files are the a-cappella singing arias recordings, which are stereo or mono, sampled at 44.1 kHz, and stored as wav files. The wav files are recorded by two institutes: those file names ending with ‘qm’ are recorded by C4DM Queen Mary University of London; others file names ending with ‘upf’ or ‘lon’ are recorded by MTG-UPF. Additionally, another collection of 15 clean singing recordings is included in this dataset. They are extracted from the commercial recordings which originally contains karaoke accompaniment and mixed versions. Please contact the authors to obtain these 15 recordings.
If you use this audio dataset in your work, please cite as well the following publication:
D. A. A. Black, M. Li, and M. Tian, “Automatic Identification of Emotional Cues in Chinese Opera Singing,” in 13th Int. Conf. on Music Perception and Cognition (ICMPC-2014), 2014, pp. 250–255.
Details:
Annotation format, units, parsing code and other details please refer to https://github.com/MTG/jingjuPhonemeAnnotation
License:
Textgrid annotations are licensed under Creative Commons Attribution-NonCommercial 4.0 International License.
Wav audio ending with ‘upf’ or ‘lon’ are licensed under Creative Commons Attribution-NonCommercial 4.0 International.
For the license of .wav audio ending with ‘qm’ from C4DM Queen Mary University of London, please refer to this page http://isophonics.org/SingingVoiceDataset
Contact information:
Rong Gong: rong<dot>gong<at>upf<dot>edu
Rafael Caro Repetto: rafael<dot>caro<at>upf<dot>edu
Files
jingju_a_cappella_singing_dataset.zip
Files
(870.2 MB)
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