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TTS
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update `extract_tts_spec...` using `SpeakerManager`

pull/602/head
Eren Gölge 2021-06-01 10:49:48 +02:00
parent 830306d2fd
commit 667bb708b6
1 changed files with 12 additions and 12 deletions
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24
TTS/bin/extract_tts_spectrograms.py
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@ -13,7 +13,7 @@ from TTS.config import load_config
from TTS.tts.datasets import load_meta_data
from TTS.tts.datasets.TTSDataset import TTSDataset
from TTS.tts.models import setup_model
from TTS.tts.utils.speakers import parse_speakers
from TTS.tts.utils.speakers import get_speaker_manager
from TTS.tts.utils.text.symbols import make_symbols, phonemes, symbols
from TTS.utils.audio import AudioProcessor
from TTS.utils.generic_utils import count_parameters
@ -39,7 +39,9 @@ def setup_loader(ap, r, verbose=False):
enable_eos_bos=c.enable_eos_bos_chars,
use_noise_augment=False,
verbose=verbose,
speaker_mapping=speaker_mapping if c.use_speaker_embedding and c.use_external_speaker_embedding_file else None,
speaker_mapping=speaker_manager.speaker_ids
if c.use_speaker_embedding and c.use_external_speaker_embedding_file
else None,
)
if c.use_phonemes and c.compute_input_seq_cache:
@ -91,7 +93,7 @@ def format_data(data):
speaker_embeddings = data[8]
speaker_ids = None
else:
speaker_ids = [speaker_mapping[speaker_name] for speaker_name in speaker_names]
speaker_ids = [speaker_manager.speaker_ids[speaker_name] for speaker_name in speaker_names]
speaker_ids = torch.LongTensor(speaker_ids)
speaker_embeddings = None
else:
@ -134,12 +136,11 @@ def inference(
text_lengths,
mel_input,
mel_lengths,
attn_mask=None,
speaker_ids=None,
speaker_embeddings=None,
):
if model_name == "glow_tts":
mel_input = mel_input.permute(0, 2, 1) # B x D x T
# mel_input = mel_input.permute(0, 2, 1) # B x D x T
speaker_c = None
if speaker_ids is not None:
speaker_c = speaker_ids
@ -147,9 +148,9 @@ def inference(
speaker_c = speaker_embeddings
outputs = model.inference_with_MAS(
text_input, text_lengths, mel_input, mel_lengths, attn_mask, g=speaker_c
text_input, text_lengths, mel_input, mel_lengths, cond_input={"x_vectors": speaker_c}
)
model_output = outputs['model_outputs']
model_output = outputs["model_outputs"]
model_output = model_output.transpose(1, 2).detach().cpu().numpy()
elif "tacotron" in model_name:
@ -193,7 +194,7 @@ def extract_spectrograms(
speaker_embeddings,
_,
_,
attn_mask,
_,
item_idx,
) = format_data(data)
@ -205,7 +206,6 @@ def extract_spectrograms(
text_lengths,
mel_input,
mel_lengths,
attn_mask,
speaker_ids,
speaker_embeddings,
)
@ -242,7 +242,7 @@ def extract_spectrograms(
def main(args): # pylint: disable=redefined-outer-name
# pylint: disable=global-variable-undefined
global meta_data, symbols, phonemes, model_characters, speaker_mapping
global meta_data, symbols, phonemes, model_characters, speaker_manager
# Audio processor
ap = AudioProcessor(**c.audio)
@ -260,10 +260,10 @@ def main(args): # pylint: disable=redefined-outer-name
meta_data = meta_data_train + meta_data_eval
# parse speakers
num_speakers, speaker_embedding_dim, speaker_mapping = parse_speakers(c, args, meta_data_train, None)
speaker_manager = get_speaker_manager(c, args, meta_data_train)
# setup model
model = setup_model(num_chars, num_speakers, c, speaker_embedding_dim=speaker_embedding_dim)
model = setup_model(num_chars, speaker_manager.num_speakers, c, speaker_embedding_dim=speaker_manager.x_vector_dim)
# restore model
checkpoint = torch.load(args.checkpoint_path, map_location="cpu")