Based on WandB and PyTorch Lightning
Modified data preprocessing to MARBLE Benchmark
Preparation
- Download VocalSet from https://zenodo.org/record/1193957
- Run the code
python prepare.py
Then, split files will be created.
Main program
python main.py
The detailed experiment conditions are contained in run.sh.
- APSIPA 2021: Refer to the line "OblongCNN"
- Interspeech 2022: Refer to the line "OblongDeformableCNN"
- The Best Version: Refer to the line "dcnv2 crt stft", which uses Multi-resolution spectrogram, classifier retraining, and modulated deformable convolution (DCNv2)
Reference:
@inproceedings{yamamoto22_interspeech,
author={Yuya Yamamoto and Juhan Nam and Hiroko Terasawa},
title={{Deformable CNN and Imbalance-Aware Feature Learning for Singing Technique Classification}},
year=2022,
booktitle={Proc. Interspeech 2022},
pages={2778--2782},
doi={10.21437/Interspeech.2022-11137}
}