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mask_padding: True
n_mel_channels: 80
n_symbols: 148
symbols_embedding_dim: 512
encoder_kernel_size: 5
encoder_n_convolutions: 3
encoder_embedding_dim: 512
attention_rnn_dim: 1024
attention_dim: 128
attention_location_n_filters: 32
attention_location_kernel_size: 31
n_frames_per_step: 1
decoder_rnn_dim: 1024
prenet_dim: 256
max_decoder_steps: 1000
gate_threshold: 0.5
p_attention_dropout: 0.1
p_decoder_dropout: 0.1
postnet_embedding_dim: 512
postnet_kernel_size: 5
postnet_n_convolutions: 5
decoder_no_early_stopping: False
sample_rate: 22050
# Model
model: !new:speechbrain.lobes.models.Tacotron2.Tacotron2
mask_padding: !ref <mask_padding>
n_mel_channels: !ref <n_mel_channels>
# symbols
n_symbols: !ref <n_symbols>
symbols_embedding_dim: !ref <symbols_embedding_dim>
# encoder
encoder_kernel_size: !ref <encoder_kernel_size>
encoder_n_convolutions: !ref <encoder_n_convolutions>
encoder_embedding_dim: !ref <encoder_embedding_dim>
# attention
attention_rnn_dim: !ref <attention_rnn_dim>
attention_dim: !ref <attention_dim>
# attention location
attention_location_n_filters: !ref <attention_location_n_filters>
attention_location_kernel_size: !ref <attention_location_kernel_size>
# decoder
n_frames_per_step: !ref <n_frames_per_step>
decoder_rnn_dim: !ref <decoder_rnn_dim>
prenet_dim: !ref <prenet_dim>
max_decoder_steps: !ref <max_decoder_steps>
gate_threshold: !ref <gate_threshold>
p_attention_dropout: !ref <p_attention_dropout>
p_decoder_dropout: !ref <p_decoder_dropout>
# postnet
postnet_embedding_dim: !ref <postnet_embedding_dim>
postnet_kernel_size: !ref <postnet_kernel_size>
postnet_n_convolutions: !ref <postnet_n_convolutions>
decoder_no_early_stopping: !ref <decoder_no_early_stopping>
# Function that converts the text into a sequence of valid characters.
text_to_sequence: !name:speechbrain.utils.text_to_sequence.text_to_sequence
modules:
model: !ref <model>
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
model: !ref <model> |