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Dataset Card for Piano Sound Quality Dataset

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.

Usage

Raw Subset

from datasets import load_dataset

ds = load_dataset("ccmusic-database/pianos", name="default")
for item in ds["train"]:
    print(item)

for item in ds["validation"]:
    print(item)

for item in ds["test"]:
    print(item)

Eval Subset

from datasets import load_dataset

ds = load_dataset("ccmusic-database/pianos", name="eval")
for item in ds["train"]:
    print(item)

for item in ds["validation"]:
    print(item)

for item in ds["test"]:
    print(item)

Maintenance

GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/ccmusic-database/pianos
cd pianos

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], 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
... ... ...

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
... ... ... ...

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.

(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

@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

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