espnet/english_male_ryanspeech_conformer_fastspeech2

RyanSpeech model (based on ESPnet2)

espnet/english_male_ryanspeech_conformer_fastspeech2

This model was trained by Rohola Zandie using ryanspeech recipe in espnet. For the best results you need to download the vocoder separately from here and then use the following code:

from espnet2.bin.tts_inference import Text2Speech
from scipy.io.wavfile import write

model = Text2Speech.from_pretrained(
    model_file="espnet/english_male_ryanspeech_conformer_fastspeech2",
    vocoder_file="path_to_vocoder/train_nodev_parallel_wavegan.v1.long/checkpoint-1000000steps.pkl"
)

output = model("This is a simple test.")

write("x.wav", 22050, output['wav'].numpy())

Download the dataset

You can download RyanSpeech dataset from here or here.

TTS config

expand

config: conf/tuning/train_conformer_fastspeech2.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/tts_train_conformer_fastspeech2_raw_phn_tacotron_g2p_en_no_space
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
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 1000
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: 10
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
pretrain_path: []
pretrain_key: []
num_iters_per_epoch: 500
batch_size: 20
valid_batch_size: null
batch_bins: 2400000
valid_batch_bins: null
train_shape_file:
- exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/train/text_shape.phn
- exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/train/speech_shape
valid_shape_file:
- exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/valid/text_shape.phn
- exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/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:
-   - dump/raw/tr_no_dev/text
    - text
    - text
-   - exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/tr_no_dev/durations
    - durations
    - text_int
-   - dump/raw/tr_no_dev/wav.scp
    - speech
    - sound
-   - exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/train/collect_feats/pitch.scp
    - pitch
    - npy
-   - exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/train/collect_feats/energy.scp
    - energy
    - npy
valid_data_path_and_name_and_type:
-   - dump/raw/dev/text
    - text
    - text
-   - exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/dev/durations
    - durations
    - text_int
-   - dump/raw/dev/wav.scp
    - speech
    - sound
-   - exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/valid/collect_feats/pitch.scp
    - pitch
    - npy
-   - exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/valid/collect_feats/energy.scp
    - energy
    - npy
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: 4000
token_list:
- <blank>
- <unk>
- AH0
- T
- N
- S
- R
- D
- L
- K
- IH1
- M
- EH1
- Z
- DH
- UW1
- AE1
- IH0
- AY1
- AH1
- W
- .
- P
- F
- IY1
- V
- ER0
- AA1
- B
- AO1
- HH
- EY1
- IY0
- ','
- Y
- NG
- OW1
- G
- AW1
- TH
- SH
- UH1
- '?'
- ER1
- JH
- CH
- OW0
- OW2
- EH2
- IH2
- EY2
- AA2
- AE2
- AY2
- ''''
- OY1
- UW0
- '!'
- AO2
- EH0
- ZH
- AH2
- AE0
- UW2
- AA0
- AY0
- IY2
- AW2
- AO0
- EY0
- ER2
- UH2
- '...'
- AW0
- UH0
- OY2
- <sos/eos>
odim: null
model_conf: {}
use_preprocessor: true
token_type: phn
bpemodel: null
non_linguistic_symbols: null
cleaner: tacotron
g2p: g2p_en_no_space
feats_extract: fbank
feats_extract_conf:
    fs: 22050
    fmin: 80
    fmax: 7600
    n_mels: 80
    hop_length: 256
    n_fft: 1024
    win_length: null
normalize: global_mvn
normalize_conf:
    stats_file: exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/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
pitch_extract: dio
pitch_extract_conf:
    fs: 22050
    n_fft: 1024
    hop_length: 256
    f0max: 400
    f0min: 80
pitch_normalize: global_mvn
pitch_normalize_conf:
    stats_file: exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/train/pitch_stats.npz
energy_extract: energy
energy_extract_conf:
    fs: 22050
    n_fft: 1024
    hop_length: 256
    win_length: null
energy_normalize: global_mvn
energy_normalize_conf:
    stats_file: exp/tts_train_raw_phn_tacotron_g2p_en_no_space/decode_use_teacher_forcingtrue_train.loss.ave/stats/train/energy_stats.npz
required:
- output_dir
- token_list
distributed: false

Citing RyanSpeech

@inproceedings{Zandie2021RyanSpeechAC,
  title={RyanSpeech: A Corpus for Conversational Text-to-Speech Synthesis},
  author={Rohola Zandie and Mohammad H. Mahoor and Julia Madsen and Eshrat S. Emamian},
  booktitle={Interspeech},
  year={2021}
}