gpt_tts

ESPnet2 TTS model

Lance-yang/gpt_tts

This model was trained by Li-Jen using chatbot 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 7403795abbc881759076f4d6bfb8784a57031b31
pip install -e .
cd egs2/chatbot/tts1
./run.sh --skip_data_prep false --skip_train true --download_model Lance-yang/gpt_tts

TTS config

<details><summary>expand</summary>

config: conf/tuning/train_gst+xvector_conformer_fastspeech2.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/tts_finetune_fastpeech2_g2pw
ngpu: 1
seed: 0
num_workers: 1
num_att_plot: 3
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: 100
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
nbest_averaging_interval: 0
grad_clip: 1.0
grad_clip_type: 2.0
grad_noise: false
accum_grad: 1
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:
- ../../aishell3/tts1/exp/tts_train_gst+xvector_conformer_fastspeech2_raw_phn_pypinyin_g2p_phone/train.loss.ave_5best.pth:tts:tts
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: null
batch_size: 50
valid_batch_size: null
batch_bins: 1000000
valid_batch_bins: null
train_shape_file:
- exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/train/text_shape.phn
- exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/train/speech_shape
valid_shape_file:
- exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/valid/text_shape.phn
- exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/valid/speech_shape
batch_type: sorted
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/train_no_dev_test_phn/text
    - text
    - text
-   - exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/decode_use_teacher_forcingtrue_train.loss.ave//train_no_dev_test_phn/durations
    - durations
    - text_int
-   - dump/raw/train_no_dev_test_phn/wav.scp
    - speech
    - sound
-   - exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/train/collect_feats/pitch.scp
    - pitch
    - npy
-   - exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/train/collect_feats/energy.scp
    - energy
    - npy
-   - dump/xvector/train_no_dev_test_phn/xvector.scp
    - spembs
    - kaldi_ark
valid_data_path_and_name_and_type:
-   - dump/raw/dev_phn/text
    - text
    - text
-   - exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/decode_use_teacher_forcingtrue_train.loss.ave//dev_phn/durations
    - durations
    - text_int
-   - dump/raw/dev_phn/wav.scp
    - speech
    - sound
-   - exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/valid/collect_feats/pitch.scp
    - pitch
    - npy
-   - exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/valid/collect_feats/energy.scp
    - energy
    - npy
-   - dump/xvector/dev_phn/xvector.scp
    - spembs
    - kaldi_ark
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: 384
    warmup_steps: 2000
token_list:
- <blank>
- <unk>
- d
- sh
- j
- i4
- zh
- l
- x
- e
- b
- g
- i1
- h
- q
- m
- t
- i2
- u4
- z
- ch
- i3
- f
- s
- n
- iou3
- r
- ian4
- ong1
- uei4
- e4
- en2
- ai4
- k
- ing2
- a1
- uo3
- u3
- ao4
- p
- an1
- eng2
- e2
- in1
- c
- ai2
- an4
- ian2
- u2
- ang4
- ian1
- ai3
- ing1
- ao3
- uo4
- ian3
- ing4
- ü4
- ang1
- u1
- iao4
- eng1
- iou4
- a4
- üan2
- ie4
- ou4
- er4
- en1
- ong2
- e1
- an3
- ei4
- uo2
- ou3
- ang2
- iang4
- ou1
- ang3
- an2
- eng4
- ong4
- uan4
- a3
- ia4
- ia1
- iao1
- iang1
- iou2
- uo1
- ei3
- iao3
- in4
- e3
- ü3
- iang3
- uei2
- en3
- uan1
- ie3
- ao1
- ai1
- üe4
- ü2
- ing3
- en4
- uei1
- er2
- uan3
- ü1
- in3
- en
- üe2
- ie2
- ei2
- ua4
- uan2
- in2
- a2
- ie1
- iang2
- ou2
- ong3
- uang3
- eng3
- uen1
- uai4
- ün4
- uang4
- uei3
- uen2
- uen4
- i
- iong4
- v3
- iao2
- üan4
- uang1
- ei1
- o2
- iou1
- uang2
- a
- ao2
- o1
- ua2
- uen3
- ua1
- v4
- üan3
- ün1
- üe1
- ün2
- o4
- er3
- iong3
- üan1
- ia3
- ia2
- iong1
- üe3
- ve4
- iong2
- uai2
- er
- ua3
- uai1
- ou
- ün3
- uai3
- ia
- uo
- o3
- v2
- ueng1
- o
- ei
- ua
- io1
- <sos/eos>
odim: null
model_conf: {}
use_preprocessor: true
token_type: phn
bpemodel: null
non_linguistic_symbols: null
cleaner: null
g2p: null
feats_extract: fbank
feats_extract_conf:
    n_fft: 2048
    hop_length: 300
    win_length: 1200
    fs: 24000
    fmin: 80
    fmax: 7600
    n_mels: 80
normalize: global_mvn
normalize_conf:
    stats_file: exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/train/feats_stats.npz
tts: fastspeech2
tts_conf:
    adim: 384
    aheads: 2
    elayers: 4
    eunits: 1536
    dlayers: 4
    dunits: 1536
    positionwise_layer_type: conv1d
    positionwise_conv_kernel_size: 3
    duration_predictor_layers: 2
    duration_predictor_chans: 256
    duration_predictor_kernel_size: 3
    postnet_layers: 5
    postnet_filts: 5
    postnet_chans: 256
    use_masking: true
    encoder_normalize_before: true
    decoder_normalize_before: true
    reduction_factor: 1
    encoder_type: conformer
    decoder_type: conformer
    conformer_pos_enc_layer_type: rel_pos
    conformer_self_attn_layer_type: rel_selfattn
    conformer_activation_type: swish
    use_macaron_style_in_conformer: true
    use_cnn_in_conformer: true
    conformer_enc_kernel_size: 7
    conformer_dec_kernel_size: 31
    init_type: xavier_uniform
    transformer_enc_dropout_rate: 0.2
    transformer_enc_positional_dropout_rate: 0.2
    transformer_enc_attn_dropout_rate: 0.2
    transformer_dec_dropout_rate: 0.2
    transformer_dec_positional_dropout_rate: 0.2
    transformer_dec_attn_dropout_rate: 0.2
    pitch_predictor_layers: 5
    pitch_predictor_chans: 256
    pitch_predictor_kernel_size: 5
    pitch_predictor_dropout: 0.5
    pitch_embed_kernel_size: 1
    pitch_embed_dropout: 0.0
    stop_gradient_from_pitch_predictor: true
    energy_predictor_layers: 2
    energy_predictor_chans: 256
    energy_predictor_kernel_size: 3
    energy_predictor_dropout: 0.5
    energy_embed_kernel_size: 1
    energy_embed_dropout: 0.0
    stop_gradient_from_energy_predictor: false
    spk_embed_dim: 512
    spk_embed_integration_type: add
    use_gst: true
    gst_heads: 4
    gst_tokens: 16
pitch_extract: dio
pitch_extract_conf:
    fs: 24000
    n_fft: 2048
    hop_length: 300
    f0max: 400
    f0min: 80
    reduction_factor: 1
pitch_normalize: global_mvn
pitch_normalize_conf:
    stats_file: exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/train/pitch_stats.npz
energy_extract: energy
energy_extract_conf:
    fs: 24000
    n_fft: 2048
    hop_length: 300
    win_length: 1200
    reduction_factor: 1
energy_normalize: global_mvn
energy_normalize_conf:
    stats_file: exp/tts_finetune_tacotron2_raw_phn_chatbot_own_model/stats_phn/train/energy_stats.npz
required:
- output_dir
- token_list
version: '202211'
distributed: false

</details>

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}
}