Dataset Card for Erhu Playing Technique

Name: erhu_playing_tech
Creator: CCMUSIC
License: https://choosealicense.com/licenses/cc-by-nc-nd-4.0/

The original dataset is sourced from ErhuPT and all performances are conducted by professional erhu players. These clips are categorized by annotators with proficiency in erhu performance into 11 classes, namely: split bow, pad bow, overtone, legato & glissando & slur, strike bow, plucked string, throw bow, staccato bow, tremolo, and vibrato. For certain playing techniques, multiple audio clips are available, each played at different dynamics. This dataset was created and has been utilized for erhu playing technique detection. The label system is hierarchical and contains three levels in the original dataset. The first level consists of four categories: trill, staccato, slide, and others; the second level comprises seven categories: trill/short/up, trill/long, staccato, slide up, slide/legato, slide/down, and others; the third level consists of 11 categories, representing the 11 playing techniques described earlier.

After organizing the aforementioned data, we constructed the default subset of the current integrated version dataset based on its 11 classification data and optimized the names of the 11 categories. The data structure can be seen in the viewer. Although the original dataset has been cited in some articles, the experiments in those articles lack reproducibility. In order to demonstrate the effectiveness of the default subset, we further processed the data and constructed the eval subset to supplement the evaluation of this integrated version dataset. The results of the evaluation can be viewed in the erhu_playing_tech. In addition, the labels of categories 4 and 7 in the original dataset were not discarded. Instead, they were separately constructed into 4_class subset and 7_class subset. However, these two subsets have not been evaluated and therefore are not reflected in our paper. The following are the statistical charts for the 11_class (Default), 7_class, and 4_class subsets:

Viewer

https://www.modelscope.cn/datasets/ccmusic-database/erhu_playing_tech/dataPeview

Dataset Structure

Default subset

audio	mel	label
.wav, 44100Hz	.jpg, 44100Hz	4/7/11-class
...	...	...

Eval subset

mel	cqt	chroma	label
.jpg, 44100Hz	.jpg, 44100Hz	.jpg, 44100Hz	11-class
...	...	...	...

Data Instances

.zip(.wav, .jpg)

Data Fields

+ detache 分弓 (72)
  + forte (8)
  + medium (8)
  + piano (56)
+ diangong 垫弓 (28)
+ harmonic 泛音 (18)
  + natural 自然泛音 (6)
  + artificial 人工泛音 (12)
+ legato&slide&glissando 连弓&滑音&大滑音 (114)
  + glissando_down 大滑音 下行 (4)
  + glissando_up 大滑音 上行 (4)
  + huihuayin_down 下回滑音 (18)
  + huihuayin_long_down 后下回滑音 (12)
  + legato&slide_up 向上连弓 包含滑音 (24)
    + forte (8)
    + medium (8)
    + piano (8)
  + slide_dianzhi 垫指滑音 (4)
  + slide_down 向下滑音 (16)
  + slide_legato 连线滑音 (16)
  + slide_up 向上滑音 (16)
+ percussive 打击类音效 (21)
  + dajigong 大击弓 (11)
  + horse 马嘶 (2)
  + stick 敲击弓 (8)
+ pizzicato 拨弦 (96)
  + forte (30)
  + medium (29)
  + piano (30)
  + left 左手勾弦 (6)
+ ricochet 抛弓 (36)
+ staccato 顿弓 (141)
  + forte (47)
  + medium (46)
  + piano (48)
+ tremolo 颤弓 （144）
  + forte (48)
  + medium (48)
  + piano (48)
+ trill 颤音 (202)
  + long 长颤音 (141)
    + forte (46)
    + medium (47)
    + piano (48)
  + short 短颤音 (61)
    + down 下颤音 (30)
    + up 上颤音 (31)
+ vibrato 揉弦 (56)
  + late (13)
  + press 压揉 (6)
  + roll 滚揉 (28)
  + slide 滑揉 (9)

Data Splits

train, validation, test

Dataset Summary

The label system is hierarchical and contains three levels in the raw dataset. The first level consists of four categories: trill, staccato, slide, and others; the second level comprises seven categories: trill\short\up, trill\long, staccato, slide up, slide\legato, slide\down, and others; the third level consists of 11 categories, representing the 11 playing techniques described earlier. Although it also employs a three-level label system, the higher-level labels do not exhibit complete downward compatibility with the lower-level labels. Therefore, we cannot merge these three-level labels into the same split but must treat them as three separate subsets.

Supported Tasks and Leaderboards

Erhu Playing Technique Classification

Languages

Chinese, English

Usage

Eval

from datasets import load_dataset

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

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

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

4-class

from datasets import load_dataset

dataset = load_dataset("ccmusic-database/erhu_playing_tech", name="4_classes")
for item in ds["train"]:
    print(item)

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

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

7-class

from datasets import load_dataset

ds = load_dataset("ccmusic-database/erhu_playing_tech", name="7_classes")
for item in ds["train"]:
    print(item)

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

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

11-class

from datasets import load_dataset
# default
ds = load_dataset("ccmusic-database/erhu_playing_tech", name="11_classes")
for item in ds["train"]:
    print(item)

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

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

Maintenance

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

Dataset Creation

Curation Rationale

Lack of a dataset for Erhu playing tech

Source Data

Initial Data Collection and Normalization

Zhaorui Liu, Monan Zhou

Who are the source language producers?

Students from CCMUSIC

Annotations

Annotation process

This dataset is an audio dataset containing 927 audio clips recorded by the China Conservatory of Music, each with a performance technique of erhu.

Who are the annotators?

Students from CCMUSIC

Personal and Sensitive Information

None

Considerations for Using the Data

Social Impact of Dataset

Advancing the Digitization Process of Traditional Chinese Instruments

Discussion of Biases

Only for Erhu

Other Known Limitations

Not Specific Enough in Categorization

Additional Information

Dataset Curators

Zijin Li

Evaluation

Wang, Zehao et al. “Musical Instrument Playing Technique Detection Based on FCN: Using Chinese Bowed-Stringed Instrument as an Example.” ArXiv abs/1910.09021 (2019): n. pag.

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 Erhu playing tech