speechbrain
English
Tacotron2
zero-shot
multi-speaker-tts
File size: 3,353 Bytes
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################################
# Audio Parameters             #
################################
sample_rate: 22050
hop_length: 256
win_length: 1024
n_mel_channels: 80
n_fft: 1024
mel_fmin: 0.0
mel_fmax: 8000.0
mel_normalized: False
power: 1
norm: "slaney"
mel_scale: "slaney"
dynamic_range_compression: True

################################
# Speaker Embedding Parameters #
################################

spk_emb_size: 192
spk_emb_sample_rate: 16000
custom_mel_spec_encoder: True
spk_emb_encoder: speechbrain/spkrec-ecapa-voxceleb-mel-spec

################################
# Optimization Hyperparameters #
################################
mask_padding: True


################################
# Model Parameters and model   #
################################
n_symbols: 148 #fixed depending on symbols in textToSequence
symbols_embedding_dim: 1024

# Encoder parameters
encoder_kernel_size: 5
encoder_n_convolutions: 6
encoder_embedding_dim: 1024

# Decoder parameters
# The number of frames in the target per encoder step
n_frames_per_step: 1
decoder_rnn_dim: 2048
prenet_dim: 512
max_decoder_steps: 1500
gate_threshold: 0.5
p_attention_dropout: 0.1
p_decoder_dropout: 0.1
decoder_no_early_stopping: False

# Attention parameters
attention_rnn_dim: 2048
attention_dim: 256

# Location Layer parameters
attention_location_n_filters: 32
attention_location_kernel_size: 31

# Mel-post processing network parameters
postnet_embedding_dim: 1024
postnet_kernel_size: 5
postnet_n_convolutions: 10

mel_spectogram: !name:speechbrain.lobes.models.Tacotron2.mel_spectogram
  sample_rate: !ref <sample_rate>
  hop_length: !ref <hop_length>
  win_length: !ref <win_length>
  n_fft: !ref <n_fft>
  n_mels: !ref <n_mel_channels>
  f_min: !ref <mel_fmin>
  f_max: !ref <mel_fmax>
  power: !ref <power>
  normalized: !ref <mel_normalized>
  norm: !ref <norm>
  mel_scale: !ref <mel_scale>
  compression: !ref <dynamic_range_compression>

#model
model: !new:speechbrain.lobes.models.MSTacotron2.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>
  # speaker embeddings
  spk_emb_size: !ref <spk_emb_size>


modules:
    model: !ref <model>

pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
    loadables:
        model: !ref <model>