readme: ---
  license: cc-by-nc-4.0
  language:
  - ja
  tags:
  - music
  - speech
  - audio
  - audio-to-audio
  - a cappella
  datasets:
  - jaCappella
  metrics:
  - SI-SDR
  ---
  
  # X-UMX 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/).
  
  # 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: 6.0
    source_augmentations:
    - gain
    sources:
    - vocal_percussion
    - bass
    - alto
    - tenor
    - soprano
    - lead_vocal
  model:
    bandwidth: 16000
    bidirectional: true
    hidden_size: 512
    in_chan: 4096
    nb_channels: 1
    nhop: 1024
    pretrained: null
    spec_power: 1
    window_length: 4096
  optim:
    lr: 0.001
    lr_decay_gamma: 0.3
    lr_decay_patience: 80
    optimizer: adam
    patience: 1000
    weight_decay: 1.0e-05
  training:
    batch_size: 16
    epochs: 1000
    loss_combine_sources: true
    loss_use_multidomain: true
    mix_coef: 10.0
    val_dur: 80.0
  ```
  
  # Results (SI-SDR [dB]) on vocal ensemble separation
  
  
  |     Method      |   Lead vocal   |    Soprano     |      Alto      |     Tenor      |      Bass      |Vocal percussion|
  |:---------------:|:--------------:|:--------------:|:--------------:|:--------------:|:--------------:|:--------------:|
  |     X-UMX       |       7.5      |      10.7      |      13.5      |      10.2      |       9.1      |      21.0      |