Medix-AI/coqui-tts
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Update fastpitche2e recipe

This commit is contained in:
Eren Gölge 2022-04-19 09:18:49 +02:00 committed by Eren G??lge
parent 5f9d559419
commit 4556c61902
2 changed files with 31 additions and 32 deletions
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26
TTS/tts/configs/fast_pitch_e2e_config.py
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@ -2,12 +2,12 @@ from dataclasses import dataclass, field
from typing import List from typing import List
from TTS.tts.configs.shared_configs import BaseTTSConfig from TTS.tts.configs.shared_configs import BaseTTSConfig
from TTS.tts.models.forward_tts_e2e import ForwardTTSE2EArgs from TTS.tts.models.forward_tts_e2e import ForwardTTSE2eArgs
@dataclass @dataclass
class FastPitchE2EConfig(BaseTTSConfig): class FastPitchE2eConfig(BaseTTSConfig):
"""Configure `ForwardTTS` as FastPitch model. """Configure `ForwardTTSE2e` as FastPitchE2e model.
Example: Example:
@ -103,13 +103,13 @@ class FastPitchE2EConfig(BaseTTSConfig):
""" """
model: str = "fast_pitch_e2e_hifigan" model: str = "fast_pitch_e2e_hifigan"
base_model: str = "forward_tts" base_model: str = "forward_tts_e2e"
# model specific params # model specific params
# model_args: ForwardTTSE2EArgs = ForwardTTSE2EArgs(vocoder_config=HifiganConfig()) # model_args: ForwardTTSE2eArgs = ForwardTTSE2eArgs(vocoder_config=HifiganConfig())
model_args: ForwardTTSE2EArgs = ForwardTTSE2EArgs() model_args: ForwardTTSE2eArgs = ForwardTTSE2eArgs()
# # multi-speaker settings # multi-speaker settings
# num_speakers: int = 0 # num_speakers: int = 0
# speakers_file: str = None # speakers_file: str = None
# use_speaker_embedding: bool = False # use_speaker_embedding: bool = False
@ -142,11 +142,19 @@ class FastPitchE2EConfig(BaseTTSConfig):
binary_align_loss_alpha: float = 0.1 binary_align_loss_alpha: float = 0.1
binary_loss_warmup_epochs: int = 150 binary_loss_warmup_epochs: int = 150
# decoder loss params # dvocoder loss params
disc_loss_alpha: float = 1.0 disc_loss_alpha: float = 1.0
gen_loss_alpha: float = 1.0 gen_loss_alpha: float = 1.0
feat_loss_alpha: float = 1.0 feat_loss_alpha: float = 1.0
mel_loss_alpha: float = 45.0 mel_loss_alpha: float = 10.0
multi_scale_stft_loss_alpha: float = 2.5
multi_scale_stft_loss_params: dict = field(
default_factory=lambda: {
"n_ffts": [1024, 2048, 512],
"hop_lengths": [120, 240, 50],
"win_lengths": [600, 1200, 240],
}
)
# data loader params # data loader params
return_wav: bool = True return_wav: bool = True

37
recipes/ljspeech/fast_pitch_e2e/train_fast_pitch_e2e.py
View File

@ -2,12 +2,12 @@ import os
from trainer import Trainer, TrainerArgs from trainer import Trainer, TrainerArgs
from TTS.config.shared_configs import BaseAudioConfig, BaseDatasetConfig from TTS.config.shared_configs import BaseDatasetConfig
from TTS.tts.configs.fast_pitch_e2e_config import FastPitchE2EConfig from TTS.tts.configs.fast_pitch_e2e_config import FastPitchE2eConfig
from TTS.tts.datasets import load_tts_samples from TTS.tts.datasets import load_tts_samples
from TTS.tts.models.forward_tts_e2e import ForwardTTSE2E, ForwardTTSE2EArgs from TTS.tts.models.forward_tts_e2e import ForwardTTSE2e, ForwardTTSE2eArgs, ForwardTTSE2eAudio
from TTS.tts.utils.text.tokenizer import TTSTokenizer from TTS.tts.utils.text.tokenizer import TTSTokenizer
from TTS.utils.audio import AudioProcessor
output_path = os.path.dirname(os.path.abspath(__file__)) output_path = os.path.dirname(os.path.abspath(__file__))
@ -15,30 +15,26 @@ output_path = os.path.dirname(os.path.abspath(__file__))
dataset_config = BaseDatasetConfig( dataset_config = BaseDatasetConfig(
name="ljspeech", name="ljspeech",
meta_file_train="metadata.csv", meta_file_train="metadata.csv",
# meta_file_attn_mask=os.path.join(output_path, "../LJSpeech-1.1/metadata_attn_mask.txt"),
path=os.path.join(output_path, "../LJSpeech-1.1/"), path=os.path.join(output_path, "../LJSpeech-1.1/"),
) )
audio_config = BaseAudioConfig( audio_config = ForwardTTSE2eAudio(
sample_rate=22050, sample_rate=22050,
do_trim_silence=True, hop_length=256,
trim_db=60.0, win_length=1024,
signal_norm=False, fft_size=1024,
mel_fmin=0.0, mel_fmin=0.0,
mel_fmax=8000, mel_fmax=8000,
spec_gain=1.0, pitch_fmax=640.0,
log_func="np.log",
ref_level_db=20,
preemphasis=0.0,
num_mels=80, num_mels=80,
) )
# vocoder_config = HifiganConfig() # vocoder_config = HifiganConfig()
model_args = ForwardTTSE2EArgs() model_args = ForwardTTSE2eArgs()
config = FastPitchE2EConfig( config = FastPitchE2eConfig(
run_name="fast_pitch_e2e_ljspeech", run_name="fast_pitch_e2e_ljspeech",
run_description="don't detach vocoder input.", run_description="Train like in FS2 paper.",
model_args=model_args, model_args=model_args,
audio=audio_config, audio=audio_config,
batch_size=32, batch_size=32,
@ -63,14 +59,9 @@ config = FastPitchE2EConfig(
output_path=output_path, output_path=output_path,
datasets=[dataset_config], datasets=[dataset_config],
start_by_longest=False, start_by_longest=False,
binary_align_loss_alpha=0.0 binary_align_loss_alpha=0.0,
) )
# INITIALIZE THE AUDIO PROCESSOR
# Audio processor is used for feature extraction and audio I/O.
# It mainly serves to the dataloader and the training loggers.
ap = AudioProcessor.init_from_config(config)
# INITIALIZE THE TOKENIZER # INITIALIZE THE TOKENIZER
# Tokenizer is used to convert text to sequences of token IDs. # Tokenizer is used to convert text to sequences of token IDs.
# If characters are not defined in the config, default characters are passed to the config # If characters are not defined in the config, default characters are passed to the config
@ -89,7 +80,7 @@ train_samples, eval_samples = load_tts_samples(
) )
# init the model # init the model
model = ForwardTTSE2E(config, ap, tokenizer, speaker_manager=None) model = ForwardTTSE2e(config=config, tokenizer=tokenizer, speaker_manager=None)
# init the trainer and 🚀 # init the trainer and 🚀
trainer = Trainer( trainer = Trainer(