Add VITS model recipe for LjSpeech

recipes/ljspeech/vits_tts/train_vits.py

@@ -0,0 +1,52 @@
+import os
+
+from TTS.config.shared_configs import BaseAudioConfig
+from TTS.trainer import Trainer, TrainingArgs, init_training
+from TTS.tts.configs import BaseDatasetConfig, VitsConfig
+
+output_path = os.path.dirname(os.path.abspath(__file__))
+dataset_config = BaseDatasetConfig(
+    name="ljspeech", meta_file_train="metadata.csv", path=os.path.join(output_path, "../LJSpeech-1.1/")
+)
+audio_config = BaseAudioConfig(
+    sample_rate=22050,
+    win_length=1024,
+    hop_length=256,
+    num_mels=80,
+    preemphasis=0.0,
+    ref_level_db=20,
+    log_func="np.log",
+    do_trim_silence=True,
+    trim_db=45,
+    mel_fmin=0,
+    mel_fmax=None,
+    spec_gain=1.0,
+    signal_norm=False,
+    do_amp_to_db_linear=False,
+)
+config = VitsConfig(
+    audio=audio_config,
+    run_name="vits_ljspeech",
+    batch_size=48,
+    eval_batch_size=16,
+    batch_group_size=0,
+    num_loader_workers=4,
+    num_eval_loader_workers=4,
+    run_eval=True,
+    test_delay_epochs=-1,
+    epochs=1000,
+    text_cleaner="english_cleaners",
+    use_phonemes=True,
+    phoneme_language="en-us",
+    phoneme_cache_path=os.path.join(output_path, "phoneme_cache"),
+    compute_input_seq_cache=True,
+    print_step=25,
+    print_eval=True,
+    mixed_precision=True,
+    max_seq_len=5000,
+    output_path=output_path,
+    datasets=[dataset_config],
+)
+args, config, output_path, _, c_logger, tb_logger = init_training(TrainingArgs(), config)
+trainer = Trainer(args, config, output_path, c_logger, tb_logger, cudnn_benchmark=True)
+trainer.fit()