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---
license: mit
task_categories:
- audio-classification
language:
- ja
- en
tags:
- music
pretty_name: NeuroPiano
size_categories:
- 1K<n<10K
---
# Dataset Card for NeuroPiano-data
<!-- Provide a quick summary of the dataset. -->
This dataset contains 2255 entries of audio-question-answer pairs that specializes in music education. Questions ranges from cleaness of attack to hands balancing, each one come with verbal response as well as a rating within 6. There are 104 unique student recordings of piano excercises and part of them are rated by multiple teachers.
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** Hayato Nishioka, Vincent Cheung, Huan Zhang, Shinichi Furuya
- **Funded by [optional]:** Japan Science and Technology Agency CREST grant [number JPMJCR20D4]
- **Shared by [optional]:** Huan Zhang
- **Language(s) :** Japanese, English
- **License:** MIT License
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [Coming Soon]
- **Paper:** [Coming Soon]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
This is a great resource in analyzing performance and piano education.
## Dataset Structure
Each entry contains:
- audio_path:
- array: loaded audio in 48000
- piece: name of the excercise. pdf score of the excercises is attached in repo.
- subject: the id of rater
- question: The question in Japanese
- answer: The answer in Japanese
- q_eng: The question in English
- a_eng: The answer in English
- score: numerical score that rates the question, in a scale of 6.
## Dataset Creation
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
The pianists and raters in this dataset are student and teachers from the NeuroPiano Academy (https://www.neuropiano.org/).
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
There should no be any sensitive or personal information, as the identities are all anonimized in the dataset.
## Citation
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
```
@inproceedings{Zhang2024HowDataset,
author = {Zhang, Huan and Cheung, Vincent and Nishioka, Hayato and Dixon, Simon and Furuya, Shinichi},
booktitle = {International Society for Music Information Retrieval (ISMIR) Late Breaking Demo (LBD)},
title = {How does the teacher rate? Observations from the NeuroPiano dataset},
year = {2024}
}
```
## Dataset Card Contact
huan.zhang@qmul.ac.uk |