https://github.com/csteinmetz1/mixing_secrets_v2

A NEW VERSION OF MIXING SECRETS DATASET FOR MUSIC SOURCE SEPARATION

https://github.com/csteinmetz1/mixing_secrets_v2

Repository

A NEW VERSION OF MIXING SECRETS DATASET FOR MUSIC SOURCE SEPARATION

https://github.com/csteinmetz1/mixing_secrets_v2/blob/main/

# MS500: A NEW VERSION OF MIXING SECRETS DATASET FOR MUSIC SOURCE SEPARATION

This is an accompanying repository of my my [master thesis](https://zenodo.org/record/7116102#.YzR0L3ZBzBU) and a submission to Late Breaking Demo of International Society of Music Information Retrieval 2022: MS500: A MULTI-TRACK DATASET FOR HIERARCHICAL MUSIC SOURCE SEPARATION

## Citation
```
@phdthesis{huicheng_zhang_2022_7116102,
  author       = {Huicheng Zhang},
  title        = {{Hierarchical Music Source Separation Using Mixing 
                   Secret Multi-track Dataset}},
  school       = {Universitat Pompeu Fabra},
  year         = 2022,
  month        = sep,
  doi          = {10.5281/zenodo.7116102},
  url          = {https://doi.org/10.5281/zenodo.7116102}
}
```
The link to my presentation: https://docs.google.com/presentation/d/1BD4iTVwp2obUxl8mThp9g8DmRBhJg3G42zwxMGK_bLg/edit?usp=sharing
## Download the published MS500 dataset from zenodo:
The link to the dataset from zenodo is coming soon!! It is big and I need to contact zenodo to increase my quota.

After Downloading the dataset from Zenodo, unzip it and go to my forked slakh-utils [repository](https://github.com/felixCheungcheung/slakh-utils/tree/master/conversion) to convert the audio files from `.flac` to `.wav` format (Total ~532GB). Then jump to the Automatic Stem generation and Dataset Formatting section to run `ms21_generate_yaml.py`

## Purpose of this repository:
This repository contains the scripts for constructing MS500. This data is only for **research purpose**.
The material contained in it should not be used for any commercial purpose without the express permission of the copyright holders. Please refer to www.cambridge-mt.com for further details.

For evaluation experiment, our code is in a branch of Asteroid which called [ms21](https://github.com/felixCheungcheung/asteroid/tree/ms21/egs/musdb18/X-UMX).

## Constructing MS500 Dataset: Step by Step
* **Creat a conda environment:**
```
conda env create -f environment.yml
conda activate ms21db
```

* **Data Gathering** from [The 'Mixing Secrets' Free Multitrack Download Library](https://cambridge-mt.com/ms/mtk/); 
```
python geturl.py                               # To generate downloadurls.txt, which will be stored in the same folder
python download_zip.py  "path_to_storage"      # To download the zipped multi-track archives and mp3 mixtures using the urls in downloadurls.txt
python unrar.py "path_to_storage"              # To unzip the zipped archives in the "multitrack_zip" folder and put them in the "unzip_multitrack" folder
python unzip_folder_setup.py "path_to_unzip_multitrack_directory"         # To unify the folder structure
```

* **Semi-automatically annotation generation**;
```
python instrument_classify.py "path_to_unzip_multitrack"                 # To generate annotation .csv
```
* **Basic DSP** for audio files :Resampling, zero-padding, "monorizing";
```

python soundfile_check.py -h
  --path PATH, -p PATH  Dataset directory
  --samplerate SAMPLERATE, -sr SAMPLERATE
                        Target Sampling Rates
  --bitrate BITRATE, -bt BITRATE
                        Target Bit Rate
  --mono, -m            Stereo: False, Mono: True
  --pad, -pd            For zero-padding, boolean
```
* After splitting the dataset. we can do track-level **loudness normalization**:
```
python ms21_normalization.py "path_to_dataset" "output_path" -25      # Default target_loudness = -25 LUFS
```
* **Automatic Stem generation and Dataset Formatting**: Same folder structure of MedleyDB and special automatic mixing algorithm for generating stereo backing vocal stem. 
```
python ms21_generate_yaml.py "path_to_the_splitted_and_normalized_dataset" "outpath_to_the_well_structured_dataset" num_threads      #Note that within the script target loudness is set to -25 LUFS
```
## TODO: Design automatic mixing algorithm for each instrument
## TODO: A Function to only use non-bleeding multi-tracks for stem generation
## TODO: A dataloader for Hierarchical Music Source Separation (HMSS) and MSS training
## Statistics of MS500
### Instrument Level Bleeding Annotation
![plot1](https://github.com/felixCheungcheung/mixing_secrets_v2/blob/main/dataset_plots/14inst%20Level%20Bleeding%20Statistics.png)

Owner

GitHub Events