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log_dir: "Models/LibriTTS"
first_stage_path: "first_stage.pth"
save_freq: 2
log_interval: 10
device: "cuda"
multigpu: false
epochs_1st: 80 # number of epochs for first stage training
epochs_2nd: 50 # number of peochs for second stage training
batch_size: 32
pretrained_model: ""
second_stage_load_pretrained: false # set to true if the pre-trained model is for 2nd stage
load_only_params: false # set to true if do not want to load epoch numbers and optimizer parameters
train_data: "Data/train_list_libritts.txt"
val_data: "Data/val_list_libritts.txt"
F0_path: "Utils/JDC/bst.t7"
ASR_config: "Utils/ASR/config.yml"
ASR_path: "Utils/ASR/epoch_00080.pth"
preprocess_params:
sr: 24000
spect_params:
n_fft: 2048
win_length: 1200
hop_length: 300
model_params:
hidden_dim: 512
n_token: 178
style_dim: 128
n_layer: 3
dim_in: 64
max_conv_dim: 512
n_mels: 80
dropout: 0.2
loss_params:
lambda_mel: 5. # mel reconstruction loss (1st & 2nd stage)
lambda_adv: 1. # adversarial loss (1st & 2nd stage)
lambda_reg: 1. # adversarial regularization loss (1st & 2nd stage)
lambda_fm: 0.1 # feature matching loss (1st & 2nd stage)
lambda_mono: 1. # monotonic alignment loss (1st stage, TMA)
lambda_s2s: 1. # sequence-to-sequence loss (1st stage, TMA)
TMA_epoch: 20 # TMA starting epoch (1st stage)
# https://github.com/yl4579/StyleTTS/issues/7
TMA_CEloss: false # whether to use cross-entropy (CE) loss for TMA
lambda_F0: 1. # F0 reconstruction loss (2nd stage)
lambda_norm: 1. # norm reconstruction loss (2nd stage)
lambda_dur: 1. # duration loss (2nd stage)
optimizer_params:
lr: 0.0001