File size: 1,957 Bytes
6fe50d8 96022c3 4cbd6ed 00e6e62 4cbd6ed 6fe50d8 54df116 7bcbdf5 54df116 a734731 4cbd6ed a734731 7bcbdf5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
---
license: cc-by-nc-4.0
language:
- ja
tags:
- music
- speech
- audio
- audio-to-audio
- a cappella
- vocal ensemble
datasets:
- jaCappella
metrics:
- SI-SDR
---
# DPTNet trained with the jaCappella corpus for vocal ensemble separation
This model was trained by Tomohiko Nakamura using [the codebase](https://github.com/TomohikoNakamura/asteroid_jaCappella)).
It was trained on the vocal ensemble separation task of [the jaCappella dataset](https://tomohikonakamura.github.io/jaCappella_corpus/).
[The paper](https://doi.org/10.1109/ICASSP49357.2023.10095569) was published in ICASSP 2023 ([arXiv](https://arxiv.org/abs/2211.16028)).
# License
See [the jaCappella dataset page](https://tomohikonakamura.github.io/jaCappella_corpus/).
# Citation
See [the jaCappella dataset page](https://tomohikonakamura.github.io/jaCappella_corpus/).
# Configuration
```yaml
data:
num_workers: 12
sample_rate: 48000
samples_per_track: 13
seed: 42
seq_dur: 5.046
source_augmentations:
- gain
sources:
- vocal_percussion
- bass
- alto
- tenor
- soprano
- lead_vocal
filterbank:
kernel_size: 32
n_filters: 64
stride: 16
masknet:
bidirectional: true
chunk_size: 174
dropout: 0
ff_activation: relu
ff_hid: 256
hop_size: 128
in_chan: 64
mask_act: sigmoid
n_repeats: 8
n_src: 6
norm_type: gLN
out_chan: 64
optim:
lr: 0.005
optimizer: adam
weight_decay: 1.0e-05
training:
batch_size: 1
early_stop: true
epochs: 600
gradient_clipping: 5
half_lr: true
loss_func: pit_sisdr
```
# Results (SI-SDR [dB]) on vocal ensemble separation
| Method | Lead vocal | Soprano | Alto | Tenor | Bass |Vocal percussion|
|:---------------:|:--------------:|:--------------:|:--------------:|:--------------:|:--------------:|:--------------:|
| DPTNet | 8.9 | 8.5 | 11.9 | 14.9 | 19.7 | 21.9 | |