| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - feature-extraction |
| tags: |
| - music |
| size_categories: |
| - 1K<n<10K |
| viewer: false |
| --- |
| |
| # CHAD-Hummings Subset |
|
|
| This repository contains the hummings subset of the dataset from ["A Semi-Supervised Deep Learning Approach to Dataset Collection for Query-by-Humming Task"]() (ISMIR 2023). |
|
|
| For the complete dataset and further details, please visit the main [GitHub repository](https://github.com/amanteur/CHAD#hummings). |
|
|
| --- |
| # Overview |
|
|
| The `chad_hummings_subset.tar.gz` archive provided in this repository contains a collection of 5,314 humming audio files. |
|
|
| These audio files are sorted into groups of 693 distinct humming fragments originating from 311 unique songs (groups). |
|
|
| Audio format - `.wav`. |
|
|
| --- |
|
|
| # Dataset Structure |
|
|
| Upon extracting the dataset from `chad_hummings_subset.tar.gz`, you will find the following structured hierarchy: |
|
|
| ``` |
| ├── {GROUP_ID} |
| │ ├── {FRAGMENT_ID} |
| │ ├── {ID}.wav |
| │ └── ... |
| │ └── ... |
| └── ... |
| ``` |
| where |
| - `GROUP_ID` - the unique identifier for each song, |
| - `FRAGMENT_ID` - the identifier for individual fragments within a song, |
| - `ID` - the version identifier for a specific fragment of the song. |
| |
| This structured hierarchy organizes the audio files and fragments, making it easier to navigate and work with the dataset. |
| |
| --- |
|
|
| # Citation |
|
|
| Please cite the following paper if you use the code or dataset provided in this repository. |
|
|
| ```bibtex |
| @inproceedings{Amatov2023, |
| title={A Semi-Supervised Deep Learning Approach to Dataset Collection for Query-by-Humming Task}, |
| author={Amatov, Amantur and Lamanov, Dmitry and Titov, Maksim and Vovk, Ivan and Makarov, Ilya and Kudinov, Mikhail}, |
| year={2023}, |
| } |
| ``` |
