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ESPnet2 pretrained model, kan-bayashi/jsut_tts_train_transformer_raw_phn_jaconv_pyopenjtalk_accent_with_pause_train.loss.ave, fs=24000, lang=jp

kan-bayashi


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    <subfield code="a">speech-recognition</subfield>
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    <subfield code="a">speech-synthesis</subfield>
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    <subfield code="a">speech-translation</subfield>
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    <subfield code="a">ESPnet2 pretrained model, kan-bayashi/jsut_tts_train_transformer_raw_phn_jaconv_pyopenjtalk_accent_with_pause_train.loss.ave, fs=24000, lang=jp</subfield>
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    <subfield code="a">&lt;p&gt;This model was trained by kan-bayashi using jsut/tts1 recipe in &lt;a href="https://github.com/espnet/espnet/"&gt;espnet&lt;/a&gt;.&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;&lt;strong&gt;Python API&lt;/strong&gt;

	&lt;pre&gt;&lt;code class="language-python"&gt;See https://github.com/espnet/espnet_model_zoo&lt;/code&gt;&lt;/pre&gt;
	&lt;/li&gt;
	&lt;li&gt;&lt;strong&gt;Evaluate in the recipe&lt;/strong&gt;
	&lt;pre&gt;&lt;code class="language-bash"&gt;git clone https://github.com/espnet/espnet
cd espnet
git checkout 18fb6edb7b14911730337baa05f0e40c4dde9002
pip install -e .
cd egs2/jsut/tts1
# Download the model file here
./run.sh --skip_data_prep false --skip_train true --download_model kan-bayashi/jsut_tts_train_transformer_raw_phn_jaconv_pyopenjtalk_accent_with_pause_train.loss.ave&lt;/code&gt;
&lt;/pre&gt;
	&lt;/li&gt;
	&lt;li&gt;&lt;strong&gt;Config&lt;/strong&gt;
	&lt;pre&gt;&lt;code&gt;config: conf/tuning/train_transformer.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/tts_train_transformer_raw_phn_jaconv_pyopenjtalk_accent_with_pause
ngpu: 1
seed: 0
num_workers: 1
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: 4
dist_rank: 0
local_rank: 0
dist_master_addr: localhost
dist_master_port: 58625
dist_launcher: null
multiprocessing_distributed: true
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 200
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - loss
    - min
-   - train
    - loss
    - min
keep_nbest_models: 5
grad_clip: 1.0
grad_clip_type: 2.0
grad_noise: false
accum_grad: 2
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
unused_parameters: false
use_tensorboard: true
use_wandb: false
wandb_project: null
wandb_id: null
pretrain_path: null
init_param: []
freeze_param: []
num_iters_per_epoch: 1000
batch_size: 20
valid_batch_size: null
batch_bins: 9000000
valid_batch_bins: null
train_shape_file:
- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_accent_with_pause/train/text_shape.phn
- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_accent_with_pause/train/speech_shape
valid_shape_file:
- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_accent_with_pause/valid/text_shape.phn
- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_accent_with_pause/valid/speech_shape
batch_type: numel
valid_batch_type: null
fold_length:
- 150
- 240000
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
train_data_path_and_name_and_type:
-   - dump/raw/tr_no_dev/text
    - text
    - text
-   - dump/raw/tr_no_dev/wav.scp
    - speech
    - sound
valid_data_path_and_name_and_type:
-   - dump/raw/dev/text
    - text
    - text
-   - dump/raw/dev/wav.scp
    - speech
    - sound
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adam
optim_conf:
    lr: 1.0
scheduler: noamlr
scheduler_conf:
    model_size: 512
    warmup_steps: 8000
token_list:
- 
- 
- '1'
- '2'
- '0'
- '3'
- '4'
- '-1'
- '5'
- a
- o
- '-2'
- i
- '-3'
- u
- e
- k
- n
- t
- '6'
- r
- '-4'
- s
- N
- m
- pau
- '7'
- sh
- d
- g
- w
- '8'
- U
- '-5'
- I
- cl
- h
- y
- b
- '9'
- j
- ts
- ch
- '-6'
- z
- p
- '-7'
- f
- ky
- ry
- '-8'
- gy
- '-9'
- hy
- ny
- '-10'
- by
- my
- '-11'
- '-12'
- '-13'
- py
- '-14'
- '-15'
- v
- '10'
- '-16'
- '-17'
- '11'
- '-21'
- '-20'
- '12'
- '-19'
- '13'
- '-18'
- '14'
- dy
- '15'
- ty
- '-22'
- '16'
- '18'
- '19'
- '17'
- 
odim: null
model_conf: {}
use_preprocessor: true
token_type: phn
bpemodel: null
non_linguistic_symbols: null
cleaner: jaconv
g2p: pyopenjtalk_accent_with_pause
feats_extract: fbank
feats_extract_conf:
    fs: 24000
    fmin: 80
    fmax: 7600
    n_mels: 80
    hop_length: 300
    n_fft: 2048
    win_length: 1200
normalize: global_mvn
normalize_conf:
    stats_file: exp/tts_stats_raw_phn_jaconv_pyopenjtalk_accent_with_pause/train/feats_stats.npz
tts: transformer
tts_conf:
    embed_dim: 0
    eprenet_conv_layers: 0
    eprenet_conv_filts: 0
    eprenet_conv_chans: 0
    dprenet_layers: 2
    dprenet_units: 256
    adim: 512
    aheads: 8
    elayers: 6
    eunits: 1024
    dlayers: 6
    dunits: 1024
    positionwise_layer_type: conv1d
    positionwise_conv_kernel_size: 1
    postnet_layers: 5
    postnet_filts: 5
    postnet_chans: 256
    use_masking: true
    bce_pos_weight: 5.0
    use_scaled_pos_enc: true
    encoder_normalize_before: true
    decoder_normalize_before: true
    reduction_factor: 1
    init_type: xavier_uniform
    init_enc_alpha: 1.0
    init_dec_alpha: 1.0
    eprenet_dropout_rate: 0.0
    dprenet_dropout_rate: 0.5
    postnet_dropout_rate: 0.5
    transformer_enc_dropout_rate: 0.1
    transformer_enc_positional_dropout_rate: 0.1
    transformer_enc_attn_dropout_rate: 0.1
    transformer_dec_dropout_rate: 0.1
    transformer_dec_positional_dropout_rate: 0.1
    transformer_dec_attn_dropout_rate: 0.1
    transformer_enc_dec_attn_dropout_rate: 0.1
    use_guided_attn_loss: true
    num_heads_applied_guided_attn: 2
    num_layers_applied_guided_attn: 2
    modules_applied_guided_attn:
    - encoder-decoder
    guided_attn_loss_sigma: 0.4
    guided_attn_loss_lambda: 10.0
pitch_extract: null
pitch_extract_conf: {}
pitch_normalize: null
pitch_normalize_conf: {}
energy_extract: null
energy_extract_conf: {}
energy_normalize: null
energy_normalize_conf: {}
required:
- output_dir
- token_list
distributed: true&lt;/code&gt;&lt;/pre&gt;
	&lt;/li&gt;
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