ccmusic-database/CTIS

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Dataset Card for Chinese Traditional Instrument Sound

Original Content

The original dataset is created by [1], with no evaluation provided. The original CTIS dataset contains recordings from 287 varieties of Chinese traditional instruments, reformed Chinese musical instruments, and instruments from ethnic minority groups. Notably, some of these instruments are rarely encountered by the majority of the Chinese populace. The dataset was later utilized by [2] for Chinese instrument recognition, where only 78 instruments—approximately one-third of the total instrument classes—were used.

Integration

We begin by performing data cleaning to remove recordings without specific instrument labels. Additionally, recordings that are not instrumental sounds, such as interview recordings, are removed to enhance usability. Finally, instrument categories lacking specific labels are excluded. The filtered dataset contains recordings of 209 types of Chinese traditional musical instruments. Compared to the original 287 instrument types, 78 were removed due to missing instrument labels. Among the remaining instruments, seven have two variants each, and one instrument, Yangqin, has four variants. We treat variants as separate classes, thus 219 labels are included at last.

In the original dataset, the Chinese character label for each instrument was represented by the folder name housing its audio files. During integration, we add Chinese pinyin label to make the dataset more accessible to researchers who are not familiar in Chinese. Then, we've reorganized the data into a dictionary with five columns, which includes: audio with a sampling rate of 44,100 Hz, pre-processed mel spectrogram, numerical label, instrument name in Chinese, and instrument name in Chinese pinyin. The provision of mel spectrograms primarily serves to enhance the visualization of the audio in the viewer. For the remaining datasets, these mel spectrograms will also be included in the integrated data structure. The total data number is 4,956, with a duration of 32.63 hours. The average duration of the recordings is 23.7 seconds.

We have constructed the default subset of the current integrated version of the dataset. Building on the default subset, we applied silence removal with a threshold of top_db=40 to the audio files, converting them into mel, CQT, and chroma spectrograms. The audio was then segmented into 2-second clips, with segments shorter than 2 seconds padded using circular padding. This process resulted in the construction of the eval subset for dataset evaluation experiments.

Statistics

Fig. 1	Fig. 2

Due to the large number of categories in this dataset, we are unable to provide the audio duration per category and the proportion of audio clips by category, as we have done for the other datasets. Instead, we provide a chart showing the distribution of the number of audio clips across different durations, as shown in Fig. 1. A second graph, shown in Fig. 2, shows the distribution of instrument categories over various durations. From Fig. 1, 3611 clips (73%) are concentrated in the range 0-27.5 s, with a steep drop in the number of samples in longer durations. In Fig. 2, about half of the instruments, totaling 117, have a duration of less than 437 seconds, while 102 instruments have a duration greater than this number. After the total duration exceeds 881 seconds, the number of instruments drops sharply. This indicates that the dataset has a certain degree of class imbalance.

Statistical items	Values
Total count	4956
Total duration(s)	117482.75025085056
Mean duration(s)	23.705155417847124
Min duration(s)	0.27639583333333334
Max duration(s)	494.2522902494331
Instrument types	209
Label Numbers	219
Eval subset total	43054
Class with the longest audio duartion	中阮 (Zhong1 ruan3)
Class in the longest audio duartion interval	箜篌 (Kong1 hou2)

Default Subset Structure

audio	mel	label (200+class)	cname (string)
.wav, 44100Hz	.jpg, 44100Hz	C0090/ C0091/ ... T0323	大笒/ 高音横笛/ ... 都它尔

Dataset Description

Maintenance

git clone [email protected]:datasets/ccmusic-database/CTIS
cd CTIS

Dataset Summary

During the integration, we first performed data cleaning to remove recordings with no specific instrument labels. The filtered dataset comprises recordings of 200 types of Chinese traditional musical instruments, totaling 3,974 audio clips. On average, there are approximately 20 audio clips per instrument. The data structure of the integrated dataset consists of three columns: an audio column containing audio files in .wav format, all sampled at a uniform rate of 22,050 Hz, a label column with 200 categories corresponding to the Chinese pinyin of the instrument names, and an additional column for the Chinese instrument names. This integrated dataset can be utilized for tasks such as Chinese instrument recognition or instrument acoustic analysis.

Supported Tasks and Leaderboards

MIR, audio classification

Languages

Chinese, English

Usage

Default Subset

from datasets import load_dataset

dataset = load_dataset("ccmusic-database/CTIS", split="train")
for item in dataset:
    print(item)

Eval Subset

from datasets import load_dataset

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

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

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

Data Instances

.zip(.wav), .csv

Data Fields

Up to 287 kinds of Chinese traditional musical instruments, improved Chinese musical instruments and Chinese ethnic musical instruments

Data Splits

instruments, percussion

Additional Information

Dataset Curators

Zijin Li

Evaluation

[1] Liang, Xiaojing et al. “Constructing a Multimedia Chinese Musical Instrument Database.” Lecture Notes in Electrical Engineering (2019): n. pag.
[2] Li, R., & Zhang, Q. (2022). Audio recognition of Chinese traditional instruments based on machine learning. Cogn. Comput. Syst., 4, 108-115.
[3] https://huggingface.co/ccmusic-database/CTIS
[4] Li Z, Liang X, Liu J, et al. DCMI: A Database of Chinese Musical Instruments[J].

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 Music Information Retrieval Research},
  month        = {mar},
  year         = {2024},
  publisher    = {HuggingFace},
  version      = {1.2},
  url          = {https://huggingface.co/ccmusic-database}
}

Contributions

Provide a dataset for Chinese Traditional Instrument Sounds