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--- |
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license: mit |
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task_categories: |
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- audio-classification |
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- image-classification |
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language: |
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- en |
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tags: |
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- music |
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- art |
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pretty_name: Piano Sound Quality Dataset |
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size_categories: |
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- 10K<n<100K |
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viewer: false |
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--- |
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# Dataset Card for Piano Sound Quality Dataset |
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The raw dataset comprises 12 full-range audio files in .wav/.mp3/.m4a format representing seven models of pianos: Kawai upright piano, Kawai grand piano, Young Change upright piano, Hsinghai upright piano, Grand Theatre Steinway piano, Steinway grand piano, and Pearl River upright piano. Additionally, there are 1,320 split monophonic audio files in .wav/.mp3/.m4a format, bringing the total number of files to 1,332. Furthermore, the dataset includes a score sheet in .xls format containing subjective evaluations of piano sound quality provided by 29 participants with musical backgrounds. |
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## Usage |
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### Raw Subset |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("ccmusic-database/pianos", name="default") |
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for item in ds["train"]: |
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print(item) |
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for item in ds["validation"]: |
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print(item) |
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for item in ds["test"]: |
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print(item) |
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``` |
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### Eval Subset |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("ccmusic-database/pianos", name="eval") |
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for item in ds["train"]: |
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print(item) |
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for item in ds["validation"]: |
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print(item) |
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for item in ds["test"]: |
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print(item) |
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``` |
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## Maintenance |
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```bash |
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GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/ccmusic-database/pianos |
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cd pianos |
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``` |
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## Dataset Description |
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- **Homepage:** <https://ccmusic-database.github.io> |
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- **Repository:** <https://huggingface.co/datasets/CCMUSIC/pianos> |
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- **Paper:** <https://doi.org/10.5281/zenodo.5676893> |
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- **Leaderboard:** <https://www.modelscope.cn/datasets/ccmusic/pianos> |
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- **Point of Contact:** <https://arxiv.org/abs/2310.04722> |
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### Dataset Summary |
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Due to the need to increase the dataset size and the absence of a popular piano brand, Yamaha, the dataset is expanded by recording an upright Yamaha piano in [[1]](https://arxiv.org/pdf/2310.04722.pdf), in which the recording details can be found. This results in a total of 2,020 audio files. As models used in that article require a larger dataset, data augmentation was performed. The original audio was transformed into Mel spectrograms and sliced into 0.18-second segments, a parameter chosen based on empirical experience. This results in 18,745 spectrogram slices. Although 0.18 seconds may seem narrow, this duration is sufficient for the task at hand, as the classification of piano sound quality does not heavily rely on the temporal characteristics of the audio segments. |
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### Supported Tasks and Leaderboards |
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Piano Sound Classification, pitch detection |
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### Languages |
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English |
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## Dataset Structure |
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### Eval Subset |
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<style> |
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.pianos td { |
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vertical-align: middle !important; |
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text-align: center; |
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} |
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.pianos th { |
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text-align: center; |
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} |
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</style> |
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<table class="pianos"> |
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<tr> |
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<th>mel(.jpg, 0.18s)</th> |
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<th>label(8-class)</th> |
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<th>pitch(88-class)</th> |
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</tr> |
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<tr> |
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<td><img src="./data/TYYnuJqndeWzXLJMmOyXJ.jpeg"></td> |
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<td>PearlRiver / YoungChang / Steinway-T / Hsinghai / Kawai / Steinway / Kawai-G / Yamaha</td> |
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<td>88 pitches on piano</td> |
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</tr> |
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<tr> |
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<td>...</td> |
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<td>...</td> |
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<td>...</td> |
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</tr> |
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</table> |
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### Raw Subset |
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<table class="pianos"> |
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<tr> |
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<th>audio(.wav, 22050Hz)</th> |
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<th>mel(.jpg)</th> |
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<th>label(8-class)</th> |
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<th>pitch(88-class)</th> |
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</tr> |
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<tr> |
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<td><audio controls src="./data/3800.wav"></audio></td> |
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<td><img src="./data/3800.jpg"></td> |
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<td>PearlRiver / YoungChang / Steinway-T / Hsinghai / Kawai / Steinway / Kawai-G / Yamaha</td> |
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<td>88 pitches on piano</td> |
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</tr> |
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<tr> |
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<td>...</td> |
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<td>...</td> |
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<td>...</td> |
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<td>...</td> |
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</tr> |
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</table> |
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### Data Instances |
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.zip(.wav, jpg) |
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### Data Fields |
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``` |
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1_PearlRiver |
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2_YoungChang |
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3_Steinway-T |
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4_Hsinghai |
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5_Kawai |
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6_Steinway |
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7_Kawai-G |
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8_Yamaha |
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``` |
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### Data Splits for Eval Subset |
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| Split | Eval | Eval | |
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| :-------------: | :---: | :---: | |
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| total | 18745 | 668 | |
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| train(80%) | 14996 | 534 | |
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| validation(10%) | 1874 | 67 | |
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| test(10%) | 1875 | 67 | |
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## Dataset Creation |
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### Curation Rationale |
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Lack of a dataset for piano sound quality |
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### Source Data |
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#### Initial Data Collection and Normalization |
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Zhaorui Liu, Shaohua Ji, Monan Zhou |
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#### Who are the source language producers? |
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Students from CCMUSIC & CCOM |
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### Annotations |
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#### Annotation process |
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Students from CCMUSIC recorded different piano sounds and labeled them, and then a subjective survey of sound quality was conducted to score them. |
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#### Who are the annotators? |
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Students from CCMUSIC & CCOM |
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### Personal and Sensitive Information |
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Piano brands |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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Help develop piano sound quality scoring apps |
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### Discussion of Biases |
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Only for pianos |
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### Other Known Limitations |
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Lack of black keys for Steinway, data imbalance |
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## Additional Information |
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### Dataset Curators |
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Zijin Li |
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### Evaluation |
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[1] [Monan Zhou, Shangda Wu, Shaohua Ji, Zijin Li, and Wei Li. A Holistic Evaluation of Piano Sound Quality[C]//Proceedings of the 10th Conference on Sound and Music Technology (CSMT). Springer, Singapore, 2023.](https://arxiv.org/pdf/2310.04722.pdf) |
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(Note: this paper only uses the first 7 piano classes in the dataset, its future work has finished the 8-class evaluation) |
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### Licensing Information |
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``` |
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MIT License |
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Copyright (c) CCMUSIC |
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Permission is hereby granted, free of charge, to any person obtaining a copy |
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of this software and associated documentation files (the "Software"), to deal |
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in the Software without restriction, including without limitation the rights |
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell |
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copies of the Software, and to permit persons to whom the Software is |
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furnished to do so, subject to the following conditions: |
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The above copyright notice and this permission notice shall be included in all |
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copies or substantial portions of the Software. |
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
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SOFTWARE. |
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``` |
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### Citation Information |
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```bibtex |
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@dataset{zhaorui_liu_2021_5676893, |
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author = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han}, |
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title = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research}, |
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month = {mar}, |
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year = {2024}, |
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publisher = {HuggingFace}, |
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version = {1.2}, |
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url = {https://huggingface.co/ccmusic-database} |
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} |
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``` |
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### Contributions |
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Provide a dataset for piano sound quality |