--- license: mit task_categories: - audio-classification - image-classification language: - en tags: - music - art pretty_name: Piano Sound Quality Dataset size_categories: - 10K - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary 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. ### Supported Tasks and Leaderboards Piano Sound Classification, pitch detection ### Languages English ## Dataset Structure ### Eval Subset
mel(.jpg, 0.18s 48000Hz) label(8-class) pitch(88-class)
PearlRiver / YoungChang / Steinway-T / Hsinghai / Kawai / Steinway / Kawai-G / Yamaha 88 pitches on piano
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### Raw Subset
audio(.wav, 22050Hz) mel(.jpg, 22050Hz) label(8-class) pitch(88-class)
PearlRiver / YoungChang / Steinway-T / Hsinghai / Kawai / Steinway / Kawai-G / Yamaha 88 pitches on piano
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### Data Instances .zip(.wav, jpg) ### Data Fields ``` 1_PearlRiver 2_YoungChang 3_Steinway-T 4_Hsinghai 5_Kawai 6_Steinway 7_Kawai-G 8_Yamaha ``` ### Data Splits for Eval Subset | Split | Eval | Eval | | :-------------: | :---: | :---: | | total | 18745 | 668 | | train(80%) | 14996 | 534 | | validation(10%) | 1874 | 67 | | test(10%) | 1875 | 67 | ## Dataset Creation ### Curation Rationale Lack of a dataset for piano sound quality ### Source Data #### Initial Data Collection and Normalization Zhaorui Liu, Shaohua Ji, Monan Zhou #### Who are the source language producers? Students from CCMUSIC & CCOM ### Annotations #### Annotation process Students from CCMUSIC recorded different piano sounds and labeled them, and then a subjective survey of sound quality was conducted to score them. #### Who are the annotators? Students from CCMUSIC & CCOM ### Personal and Sensitive Information Piano brands ## Considerations for Using the Data ### Social Impact of Dataset Help develop piano sound quality scoring apps ### Discussion of Biases Only for pianos ### Other Known Limitations Lack of black keys for Steinway, data imbalance ## Additional Information ### Dataset Curators Zijin Li ### Evaluation [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) (Note: this paper only uses the first 7 piano classes in the dataset, its future work has finished the 8-class 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 piano sound quality