# This configuration tested on 8 GPUs (A100) with 80GB GPU memory.
# It takes around 2 days to finish the training,You can adjust
# batch_size、num_workers here and ngpu in local/train.sh for your machine
###########################################################
#                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.

mean_phn_span: 8
mlm_prob: 0.8

###########################################################
#                       DATA SETTING                      #
###########################################################
batch_size: 40
num_workers: 8

###########################################################
#                       MODEL SETTING                     #
###########################################################
model:
    text_masking: false
    postnet_layers: 5
    postnet_filts: 5
    postnet_chans: 256
    encoder_type: conformer
    decoder_type: conformer
    enc_input_layer: sega_mlm
    enc_pre_speech_layer: 0
    enc_cnn_module_kernel: 7
    enc_attention_dim: 384
    enc_attention_heads: 2
    enc_linear_units: 1536
    enc_num_blocks: 4
    enc_dropout_rate: 0.2
    enc_positional_dropout_rate: 0.2
    enc_attention_dropout_rate: 0.2
    enc_normalize_before: true
    enc_macaron_style: true
    enc_use_cnn_module: true
    enc_selfattention_layer_type: legacy_rel_selfattn
    enc_activation_type: swish
    enc_pos_enc_layer_type: legacy_rel_pos
    enc_positionwise_layer_type: conv1d
    enc_positionwise_conv_kernel_size: 3
    dec_cnn_module_kernel: 31
    dec_attention_dim: 384
    dec_attention_heads: 2
    dec_linear_units: 1536
    dec_num_blocks: 4
    dec_dropout_rate: 0.2
    dec_positional_dropout_rate: 0.2
    dec_attention_dropout_rate: 0.2
    dec_macaron_style: true
    dec_use_cnn_module: true
    dec_selfattention_layer_type: legacy_rel_selfattn
    dec_activation_type: swish
    dec_pos_enc_layer_type: legacy_rel_pos
    dec_positionwise_layer_type: conv1d
    dec_positionwise_conv_kernel_size: 3

###########################################################
#                     OPTIMIZER SETTING                   #
###########################################################
scheduler_params:
    d_model: 384
    warmup_steps: 4000
grad_clip: 1.0

###########################################################
#                     TRAINING SETTING                    #
###########################################################
max_epoch: 1500
num_snapshots: 50

###########################################################
#                       OTHER SETTING                     #
###########################################################
seed: 0

token_list:
- <blank>
- <unk>
- AH0
- T
- N
- sp
- D
- S
- R
- L
- IH1
- DH
- AE1
- M
- EH1
- K
- Z
- W
- HH
- ER0
- AH1
- IY1
- P
- V
- F
- B
- AY1
- IY0
- EY1
- AA1
- AO1
- UW1
- IH0
- OW1
- NG
- G
- SH
- ER1
- Y
- TH
- AW1
- CH
- UH1
- IH2
- JH
- OW0
- EH2
- OY1
- AY2
- EH0
- EY2
- UW0
- AE2
- AA2
- OW2
- AH2
- ZH
- AO2
- IY2
- AE0
- UW2
- AY0
- AA0
- AO0
- AW2
- EY0
- UH2
- ER2
- OY2
- UH0
- AW0
- OY0
- <sos/eos>