hyperparams.yaml

pretrained_path: sahita/language-identification


n_mels: 60
left_frames: 0
right_frames: 0
deltas: false

# Number of languages
out_n_neurons: 3

# Functions
compute_features: &id003 !new:speechbrain.lobes.features.Fbank
  n_mels: 60
  left_frames: 0
  right_frames: 0
  deltas: false

embedding_model: &id004 !new:speechbrain.lobes.models.ECAPA_TDNN.ECAPA_TDNN
  input_size: 60
  channels: [1024, 1024, 1024, 1024, 3072]
  kernel_sizes: [5, 3, 3, 3, 1]
  dilations: [1, 2, 3, 4, 1]
  attention_channels: 128
  lin_neurons: 256

classifier: &id005 !new:speechbrain.lobes.models.Xvector.Classifier
  input_shape: [null, null, 256]
  activation: !name:torch.nn.LeakyReLU
  lin_blocks: 1
  lin_neurons: 512
  out_neurons: !ref <out_n_neurons>

mean_var_norm: &id006 !new:speechbrain.processing.features.InputNormalization

  norm_type: sentence
  std_norm: false

modules:
  compute_features: !ref <compute_features>
  embedding_model: !ref <embedding_model>
  classifier: !ref <classifier>
  mean_var_norm: !ref <mean_var_norm>

label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder

pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
    loadables:
        embedding_model: !ref <embedding_model>
        classifier: !ref <classifier>
        label_encoder: !ref <label_encoder>
    paths:
        embedding_model: !ref <pretrained_path>/embedding_model.ckpt
        classifier: !ref <pretrained_path>/classifier.ckpt
        label_encoder: !ref <pretrained_path>/label_encoder.txt