sepformer-libri3mix / hyperparams.yaml
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# ################################
# Model: Pretrained SepFormer for source separation
# Dataset : Libri3Mix
# ################################
# Experiment params
sample_rate: 8000
num_spks: 3
# Encoder parameters
N_encoder_out: 256
out_channels: 256
kernel_size: 16
kernel_stride: 8
# Specifying the network
Encoder: &id003 !new:speechbrain.lobes.models.dual_path.Encoder
kernel_size: 16
out_channels: 256
SBtfintra: &id001 !new:speechbrain.lobes.models.dual_path.SBTransformerBlock
num_layers: 8
d_model: 256
nhead: 8
d_ffn: 1024
dropout: 0
use_positional_encoding: true
norm_before: true
SBtfinter: &id002 !new:speechbrain.lobes.models.dual_path.SBTransformerBlock
num_layers: 8
d_model: 256
nhead: 8
d_ffn: 1024
dropout: 0
use_positional_encoding: true
norm_before: true
MaskNet: &id005 !new:speechbrain.lobes.models.dual_path.Dual_Path_Model
num_spks: 3
in_channels: 256
out_channels: 256
num_layers: 2
K: 250
intra_model: *id001
inter_model: *id002
norm: ln
linear_layer_after_inter_intra: false
skip_around_intra: true
Decoder: &id004 !new:speechbrain.lobes.models.dual_path.Decoder
in_channels: 256
out_channels: 1
kernel_size: 16
stride: 8
bias: false
modules:
encoder: *id003
decoder: *id004
masknet: *id005
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
encoder: !ref <Encoder>
masknet: !ref <MaskNet>
decoder: !ref <Decoder>