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PaddleSpeech/examples/aishell3/vc0/conf/default.yaml

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###########################################################
# FEATURE EXTRACTION SETTING #
###########################################################
fs: 24000 # sr
n_fft: 2048 # FFT size (samples).
n_shift: 300 # Hop size (samples). 12.5ms
win_length: 1200 # Window length (samples). 50ms
# If set to null, it will be the same as fft_size.
window: "hann" # Window function.
# Only used for feats_type != raw
fmin: 80 # Minimum frequency of Mel basis.
fmax: 7600 # Maximum frequency of Mel basis.
n_mels: 80 # The number of mel basis.
###########################################################
# DATA SETTING #
###########################################################
batch_size: 64
num_workers: 2
###########################################################
# MODEL SETTING #
###########################################################
model: # keyword arguments for the selected model
embed_dim: 512 # char or phn embedding dimension
elayers: 1 # number of blstm layers in encoder
eunits: 512 # number of blstm units
econv_layers: 3 # number of convolutional layers in encoder
econv_chans: 512 # number of channels in convolutional layer
econv_filts: 5 # filter size of convolutional layer
atype: location # attention function type
adim: 512 # attention dimension
aconv_chans: 32 # number of channels in convolutional layer of attention
aconv_filts: 15 # filter size of convolutional layer of attention
cumulate_att_w: True # whether to cumulate attention weight
dlayers: 2 # number of lstm layers in decoder
dunits: 1024 # number of lstm units in decoder
prenet_layers: 2 # number of layers in prenet
prenet_units: 256 # number of units in prenet
postnet_layers: 5 # number of layers in postnet
postnet_chans: 512 # number of channels in postnet
postnet_filts: 5 # filter size of postnet layer
output_activation: null # activation function for the final output
use_batch_norm: True # whether to use batch normalization in encoder
use_concate: True # whether to concatenate encoder embedding with decoder outputs
use_residual: False # whether to use residual connection in encoder
dropout_rate: 0.5 # dropout rate
zoneout_rate: 0.1 # zoneout rate
reduction_factor: 1 # reduction factor
spk_embed_dim: 256 # speaker embedding dimension
spk_embed_integration_type: concat # how to integrate speaker embedding
###########################################################
# UPDATER SETTING #
###########################################################
updater:
use_masking: True # whether to apply masking for padded part in loss calculation
bce_pos_weight: 5.0 # weight of positive sample in binary cross entropy calculation
use_guided_attn_loss: True # whether to use guided attention loss
guided_attn_loss_sigma: 0.4 # sigma of guided attention loss
guided_attn_loss_lambda: 1.0 # strength of guided attention loss
##########################################################
# OPTIMIZER SETTING #
##########################################################
optimizer:
optim: adam # optimizer type
learning_rate: 1.0e-03 # learning rate
epsilon: 1.0e-06 # epsilon
weight_decay: 0.0 # weight decay coefficient
###########################################################
# TRAINING SETTING #
###########################################################
max_epoch: 100
num_snapshots: 5
###########################################################
# OTHER SETTING #
###########################################################
seed: 42