|
| 1 | +# This config contains the default values for training FastPitch model with aligner using 22KHz sampling |
| 2 | +# rate. If you want to train model on other dataset, you can change config values according to your dataset. |
| 3 | +# Most dataset-specific arguments are in the head of the config file, see below. |
| 4 | + |
| 5 | +name: FastPitch |
| 6 | + |
| 7 | +train_dataset: ??? |
| 8 | +validation_datasets: ??? |
| 9 | +sup_data_path: ??? |
| 10 | +sup_data_types: [ "align_prior_matrix", "pitch" ] |
| 11 | + |
| 12 | +# Default values from librosa.pyin |
| 13 | +pitch_fmin: 65.40639132514966 |
| 14 | +pitch_fmax: 1986.977294921875 |
| 15 | + |
| 16 | +# these frame-wise values depend on pitch_fmin and pitch_fmax, you can get values |
| 17 | +# by running `scripts/dataset_processing/tts/extract_sup_data.py` |
| 18 | +pitch_mean: ??? # e.g. 221.4948272705078 for SFbilingual dataset. |
| 19 | +pitch_std: ??? # e.g. 64.6528930664063 for SFbilingual dataset. |
| 20 | + |
| 21 | +# Default values for dataset with sample_rate=22050 |
| 22 | +sample_rate: 22050 |
| 23 | +n_mel_channels: 80 |
| 24 | +n_window_size: 1024 |
| 25 | +n_window_stride: 256 |
| 26 | +n_fft: 1024 |
| 27 | +lowfreq: 0 |
| 28 | +highfreq: null |
| 29 | +window: hann |
| 30 | + |
| 31 | +phoneme_dict_path: "scripts/tts_dataset_files/zh/24finals/ipa_dict_nv23.05.txt" |
| 32 | + |
| 33 | +model: |
| 34 | + learn_alignment: true |
| 35 | + bin_loss_warmup_epochs: 100 |
| 36 | + |
| 37 | + n_speakers: 1 |
| 38 | + max_token_duration: 75 |
| 39 | + symbols_embedding_dim: 384 |
| 40 | + pitch_embedding_kernel_size: 3 |
| 41 | + |
| 42 | + pitch_fmin: ${pitch_fmin} |
| 43 | + pitch_fmax: ${pitch_fmax} |
| 44 | + |
| 45 | + pitch_mean: ${pitch_mean} |
| 46 | + pitch_std: ${pitch_std} |
| 47 | + |
| 48 | + sample_rate: ${sample_rate} |
| 49 | + n_mel_channels: ${n_mel_channels} |
| 50 | + n_window_size: ${n_window_size} |
| 51 | + n_window_stride: ${n_window_stride} |
| 52 | + n_fft: ${n_fft} |
| 53 | + lowfreq: ${lowfreq} |
| 54 | + highfreq: ${highfreq} |
| 55 | + window: ${window} |
| 56 | + |
| 57 | + text_normalizer: |
| 58 | + _target_: nemo_text_processing.text_normalization.normalize.Normalizer |
| 59 | + lang: zh |
| 60 | + input_case: cased |
| 61 | + |
| 62 | + text_normalizer_call_kwargs: |
| 63 | + verbose: false |
| 64 | + punct_pre_process: true |
| 65 | + punct_post_process: true |
| 66 | + |
| 67 | + text_tokenizer: |
| 68 | + _target_: nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers.ChinesePhonemesTokenizer |
| 69 | + punct: true |
| 70 | + apostrophe: true |
| 71 | + pad_with_space: true |
| 72 | + g2p: |
| 73 | + _target_: nemo.collections.tts.g2p.models.zh_cn_pinyin.ChineseG2p |
| 74 | + phoneme_dict: ${phoneme_dict_path} |
| 75 | + word_segmenter: jieba # Only jieba is supported now. |
| 76 | + phoneme_prefix: "" |
| 77 | + phoneme_case: lower |
| 78 | + tone_prefix: "#" |
| 79 | + ascii_letter_prefix: "" |
| 80 | + ascii_letter_case: upper |
| 81 | + |
| 82 | + train_ds: |
| 83 | + dataset: |
| 84 | + _target_: nemo.collections.tts.data.dataset.TTSDataset |
| 85 | + manifest_filepath: ${train_dataset} |
| 86 | + sample_rate: ${model.sample_rate} |
| 87 | + sup_data_path: ${sup_data_path} |
| 88 | + sup_data_types: ${sup_data_types} |
| 89 | + n_fft: ${model.n_fft} |
| 90 | + win_length: ${model.n_window_size} |
| 91 | + hop_length: ${model.n_window_stride} |
| 92 | + window: ${model.window} |
| 93 | + n_mels: ${model.n_mel_channels} |
| 94 | + lowfreq: ${model.lowfreq} |
| 95 | + highfreq: ${model.highfreq} |
| 96 | + max_duration: null # change to null to include longer audios. |
| 97 | + min_duration: 0.1 |
| 98 | + ignore_file: null |
| 99 | + trim: true |
| 100 | + trim_top_db: 50 |
| 101 | + trim_frame_length: ${model.n_window_size} |
| 102 | + trim_hop_length: ${model.n_window_stride} |
| 103 | + pitch_fmin: ${model.pitch_fmin} |
| 104 | + pitch_fmax: ${model.pitch_fmax} |
| 105 | + pitch_norm: true |
| 106 | + pitch_mean: ${model.pitch_mean} |
| 107 | + pitch_std: ${model.pitch_std} |
| 108 | + |
| 109 | + dataloader_params: |
| 110 | + drop_last: false |
| 111 | + shuffle: true |
| 112 | + batch_size: 32 |
| 113 | + num_workers: 12 |
| 114 | + pin_memory: true |
| 115 | + |
| 116 | + validation_ds: |
| 117 | + dataset: |
| 118 | + _target_: nemo.collections.tts.data.dataset.TTSDataset |
| 119 | + manifest_filepath: ${validation_datasets} |
| 120 | + sample_rate: ${model.sample_rate} |
| 121 | + sup_data_path: ${sup_data_path} |
| 122 | + sup_data_types: ${sup_data_types} |
| 123 | + n_fft: ${model.n_fft} |
| 124 | + win_length: ${model.n_window_size} |
| 125 | + hop_length: ${model.n_window_stride} |
| 126 | + window: ${model.window} |
| 127 | + n_mels: ${model.n_mel_channels} |
| 128 | + lowfreq: ${model.lowfreq} |
| 129 | + highfreq: ${model.highfreq} |
| 130 | + max_duration: null # change to null to include longer audios. |
| 131 | + min_duration: 0.1 |
| 132 | + ignore_file: null |
| 133 | + trim: true |
| 134 | + trim_top_db: 50 |
| 135 | + trim_frame_length: ${model.n_window_size} |
| 136 | + trim_hop_length: ${model.n_window_stride} |
| 137 | + pitch_fmin: ${model.pitch_fmin} |
| 138 | + pitch_fmax: ${model.pitch_fmax} |
| 139 | + pitch_norm: true |
| 140 | + pitch_mean: ${model.pitch_mean} |
| 141 | + pitch_std: ${model.pitch_std} |
| 142 | + |
| 143 | + dataloader_params: |
| 144 | + drop_last: false |
| 145 | + shuffle: false |
| 146 | + batch_size: 32 |
| 147 | + num_workers: 2 |
| 148 | + pin_memory: true |
| 149 | + |
| 150 | + preprocessor: |
| 151 | + _target_: nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor |
| 152 | + features: ${model.n_mel_channels} |
| 153 | + lowfreq: ${model.lowfreq} |
| 154 | + highfreq: ${model.highfreq} |
| 155 | + n_fft: ${model.n_fft} |
| 156 | + n_window_size: ${model.n_window_size} |
| 157 | + window_size: false |
| 158 | + n_window_stride: ${model.n_window_stride} |
| 159 | + window_stride: false |
| 160 | + pad_to: 1 |
| 161 | + pad_value: 0 |
| 162 | + sample_rate: ${model.sample_rate} |
| 163 | + window: ${model.window} |
| 164 | + normalize: null |
| 165 | + preemph: null |
| 166 | + dither: 0.0 |
| 167 | + frame_splicing: 1 |
| 168 | + log: true |
| 169 | + log_zero_guard_type: add |
| 170 | + log_zero_guard_value: 1e-05 |
| 171 | + mag_power: 1.0 |
| 172 | + |
| 173 | + input_fft: #n_embed and padding_idx are added by the model |
| 174 | + _target_: nemo.collections.tts.modules.transformer.FFTransformerEncoder |
| 175 | + n_layer: 6 |
| 176 | + n_head: 1 |
| 177 | + d_model: ${model.symbols_embedding_dim} |
| 178 | + d_head: 64 |
| 179 | + d_inner: 1536 |
| 180 | + kernel_size: 3 |
| 181 | + dropout: 0.1 |
| 182 | + dropatt: 0.1 |
| 183 | + dropemb: 0.0 |
| 184 | + d_embed: ${model.symbols_embedding_dim} |
| 185 | + |
| 186 | + output_fft: |
| 187 | + _target_: nemo.collections.tts.modules.transformer.FFTransformerDecoder |
| 188 | + n_layer: 6 |
| 189 | + n_head: 1 |
| 190 | + d_model: ${model.symbols_embedding_dim} |
| 191 | + d_head: 64 |
| 192 | + d_inner: 1536 |
| 193 | + kernel_size: 3 |
| 194 | + dropout: 0.1 |
| 195 | + dropatt: 0.1 |
| 196 | + dropemb: 0.0 |
| 197 | + |
| 198 | + alignment_module: |
| 199 | + _target_: nemo.collections.tts.modules.aligner.AlignmentEncoder |
| 200 | + n_text_channels: ${model.symbols_embedding_dim} |
| 201 | + |
| 202 | + duration_predictor: |
| 203 | + _target_: nemo.collections.tts.modules.fastpitch.TemporalPredictor |
| 204 | + input_size: ${model.symbols_embedding_dim} |
| 205 | + kernel_size: 3 |
| 206 | + filter_size: 256 |
| 207 | + dropout: 0.1 |
| 208 | + n_layers: 2 |
| 209 | + |
| 210 | + pitch_predictor: |
| 211 | + _target_: nemo.collections.tts.modules.fastpitch.TemporalPredictor |
| 212 | + input_size: ${model.symbols_embedding_dim} |
| 213 | + kernel_size: 3 |
| 214 | + filter_size: 256 |
| 215 | + dropout: 0.1 |
| 216 | + n_layers: 2 |
| 217 | + |
| 218 | + optim: |
| 219 | + name: adamw |
| 220 | + lr: 1e-3 |
| 221 | + betas: [0.9, 0.999] |
| 222 | + weight_decay: 1e-6 |
| 223 | + |
| 224 | + sched: |
| 225 | + name: NoamAnnealing |
| 226 | + warmup_steps: 1000 |
| 227 | + last_epoch: -1 |
| 228 | + d_model: 1 # Disable scaling based on model dim |
| 229 | + |
| 230 | +trainer: |
| 231 | + num_nodes: 1 |
| 232 | + devices: -1 # number of gpus |
| 233 | + accelerator: gpu |
| 234 | + strategy: ddp |
| 235 | + precision: 16 |
| 236 | + max_epochs: 5000 |
| 237 | + accumulate_grad_batches: 1 |
| 238 | + gradient_clip_val: 1000.0 |
| 239 | + enable_checkpointing: false # Provided by exp_manager |
| 240 | + logger: false # Provided by exp_manager |
| 241 | + log_every_n_steps: 100 |
| 242 | + check_val_every_n_epoch: 5 |
| 243 | + benchmark: false |
| 244 | + |
| 245 | +exp_manager: |
| 246 | + exp_dir: null |
| 247 | + name: ${name} |
| 248 | + create_tensorboard_logger: true |
| 249 | + create_checkpoint_callback: true |
| 250 | + checkpoint_callback_params: |
| 251 | + monitor: val_loss |
| 252 | + resume_if_exists: false |
| 253 | + resume_ignore_no_checkpoint: false |
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