--- license: mit task_categories: - audio-classification - image-classification language: - zh - en tags: - music - art pretty_name: Bel Conto and Chinese Folk Song Singing Tech size_categories: - 1K - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary This database contains hundreds of acapella singing clips that are sung in two styles, Bel Conto and Chinese national singing style by professional vocalists. All of them are sung by professional vocalists and were recorded in professional commercial recording studios. ### Supported Tasks and Leaderboards Audio classification, Image classification, singing method classification, voice classification ### Languages Chinese, English ## Dataset Structure ### Eval Subset
mel
(.jpg, 1.6s, 48000Hz)
cqt
(.jpg, 1.6s, 48000Hz)
chroma
(.jpg, 1.6s, 48000Hz)
label
(4-class)
gender
(2-class)
singing_method
(2-class)
m_bel, f_bel, m_folk, f_folk male, female Folk_Singing, Bel_Canto
... ... ... ... ... ...
### Raw Subset
audio(.wav, 22050Hz) mel(spectrogram, .jpg, 22050Hz) label(4-class) gender(2-class) singing_method(2-class)
m_bel, f_bel, m_folk, f_folk male, female Folk_Singing, Bel_Canto
... ... ... ... ...
### Data Instances .zip(.wav, .jpg) ### Data Fields m_bel, f_bel, m_folk, f_folk ### Data Splits | Split | Eval | Raw | | :-------------: | :---: | :---: | | total | 9603 | 203 | | train(80%) | 7682 | 162 | | validation(10%) | 960 | 20 | | test(10%) | 961 | 21 | ## Dataset Creation ### Curation Rationale Lack of a dataset for Bel Conto and Chinese folk song singing tech ### Source Data #### Initial Data Collection and Normalization Zhaorui Liu, Monan Zhou #### Who are the source language producers? Students from CCMUSIC ### Annotations #### Annotation process All of them are sung by professional vocalists and were recorded in professional commercial recording studios. #### Who are the annotators? professional vocalists ### Personal and Sensitive Information None ## Considerations for Using the Data ### Social Impact of Dataset Promoting the development of AI in the music industry ### Discussion of Biases Only for Chinese songs ### Other Known Limitations Some singers may not have enough professional training in classical or ethnic vocal techniques. ## Additional Information ### Dataset Curators Zijin Li ### Evaluation ### Licensing Information ``` MIT License Copyright (c) CCMUSIC Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ``` ### Citation Information ```bibtex @dataset{zhaorui_liu_2021_5676893, author = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han}, title = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research}, month = {mar}, year = {2024}, publisher = {HuggingFace}, version = {1.2}, url = {https://huggingface.co/ccmusic-database} } ``` ### Contributions Provide a dataset for distinguishing Bel Conto and Chinese folk song singing tech