ESPnet2 TTS model
saefro991/tts_bytes_css10_7lang_textpretrain_residual_freeze
This model was trained by Takaaki-Saeki using masmultts recipe in espnet.
Demo: How to use in ESPnet2
Follow the ESPnet installation instructions if you haven't done that already.
cd espnet
git checkout 11a7d61312439111d4996d55935ede718d494262
pip install -e .
cd egs2/masmultts/tts_byte_css10_adap_residual_freeze
./run.sh --skip_data_prep false --skip_train true --download_model saefro991/tts_bytes_css10_7lang_textpretrain_residual_freeze
TTS config
expand
config: conf/train.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/tts_train_raw_byte
ngpu: 1
seed: 0
num_workers: 1
num_att_plot: 1
dist_backend: nccl
dist_init_method: env://
dist_world_size: null
dist_rank: null
local_rank: 0
dist_master_addr: null
dist_master_port: null
dist_launcher: null
multiprocessing_distributed: false
unused_parameters: false
sharded_ddp: false
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: 3
nbest_averaging_interval: 0
grad_clip: 2.0
grad_clip_type: 2.0
grad_noise: false
accum_grad: 4
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_matplotlib: true
use_tensorboard: true
create_graph_in_tensorboard: false
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
pretrain_path: null
init_param:
- ../tts_pretrain_byte_residual/exp/tts_train_byte/2epoch.pth:tts_pretrain.encoder:tts.encoder
- ../tts_pretrain_byte_residual/exp/tts_train_byte/2epoch.pth:tts_pretrain.lid_emb:tts.lid_emb
ignore_init_mismatch: false
freeze_param:
- tts.encoder.adapter
- tts.encoder.embed
- tts.lid_emb
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 400000
valid_batch_bins: null
train_shape_file:
- exp/tts_stats_raw_byte/train/text_shape.byte
- exp/tts_stats_raw_byte/train/speech_shape
valid_shape_file:
- exp/tts_stats_raw_byte/valid/text_shape.byte
- exp/tts_stats_raw_byte/valid/speech_shape
batch_type: numel
valid_batch_type: null
fold_length:
- 150
- 204800
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:
- - /local/11399690.1.gpu/dump/raw/train/text
- text
- text
- - /local/11399690.1.gpu/dump/raw/train/wav.scp
- speech
- sound
- - /local/11399690.1.gpu/dump/xvector/train/xvector.scp
- spembs
- kaldi_ark
- - /local/11399690.1.gpu/dump/raw/train/utt2lid
- lids
- text_int
valid_data_path_and_name_and_type:
- - /local/11399690.1.gpu/dump/raw/dev/text
- text
- text
- - /local/11399690.1.gpu/dump/raw/dev/wav.scp
- speech
- sound
- - /local/11399690.1.gpu/dump/xvector/dev/xvector.scp
- spembs
- kaldi_ark
- - /local/11399690.1.gpu/dump/raw/dev/utt2lid
- lids
- text_int
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: 50000
token_list:
- <blank>
- <unk>
- '32'
- '101'
- '97'
- '105'
- '110'
- '116'
- '111'
- '115'
- '114'
- '108'
- '100'
- '117'
- '109'
- '99'
- '195'
- '112'
- '104'
- '118'
- '107'
- '103'
- '98'
- '122'
- '102'
- '106'
- '121'
- '119'
- '164'
- '169'
- '197'
- '196'
- '161'
- '113'
- '179'
- '173'
- '188'
- '182'
- '190'
- '208'
- '120'
- '141'
- '153'
- '160'
- '155'
- '189'
- '131'
- '186'
- '168'
- '133'
- '209'
- '130'
- '181'
- '159'
- '151'
- '175'
- '177'
- '145'
- '171'
- '174'
- '165'
- '135'
- '200'
- '180'
- '170'
- '178'
- '176'
- '163'
- '184'
- '185'
- '187'
- '129'
- '132'
- '128'
- '136'
- '143'
- '162'
- '191'
- '150'
- '206'
- '183'
- '140'
- '172'
- '167'
- '207'
- '139'
- '142'
- '147'
- '134'
- '137'
- '148'
- '194'
- '149'
- '166'
- '49'
- '50'
- '48'
- '51'
- '138'
- '56'
- '53'
- '55'
- '52'
- '54'
- '57'
- '199'
- '226'
- '210'
- '144'
- '203'
- '225'
- '202'
- '232'
- '201'
- '157'
- '231'
- '156'
- '220'
- <sos/eos>
odim: null
model_conf: {}
use_preprocessor: true
token_type: byte
bpemodel: null
non_linguistic_symbols: null
cleaner: null
g2p: byte
feats_extract: fbank
feats_extract_conf:
n_fft: 1024
hop_length: 256
win_length: null
fs: 16000
fmin: 80
fmax: 7600
n_mels: 80
normalize: global_mvn
normalize_conf:
stats_file: exp/tts_stats_raw_byte/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
spk_embed_dim: 192
spk_embed_integration_type: add
use_gst: true
gst_heads: 4
gst_tokens: 16
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
langs: 21
lang_family_encoding: false
num_lang_family: 7
use_adapter: true
adapter_type: residual
use_encoder_w_lid: true
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
version: '202209'
distributed: false
Citing ESPnet
@inproceedings{watanabe2018espnet,
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
title={{ESPnet}: End-to-End Speech Processing Toolkit},
year={2018},
booktitle={Proceedings of Interspeech},
pages={2207--2211},
doi={10.21437/Interspeech.2018-1456},
url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={7654--7658},
year={2020},
organization={IEEE}
}
or arXiv:
@misc{watanabe2018espnet,
title={ESPnet: End-to-End Speech Processing Toolkit},
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
year={2018},
eprint={1804.00015},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
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