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Fix bug of importing GST and add more parameters in toolbox

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babysor00 2021-10-21 00:40:00 +08:00
parent aa35fb3139
commit 31bc6656c3
4 changed files with 36 additions and 17 deletions
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4
synthesizer/inference.py
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@ -70,7 +70,7 @@ class Synthesizer:
def synthesize_spectrograms(self, texts: List[str],
embeddings: Union[np.ndarray, List[np.ndarray]],
return_alignments=False, style_idx=0):
return_alignments=False, style_idx=0, min_stop_token=5):
"""
Synthesizes mel spectrograms from texts and speaker embeddings.
@ -125,7 +125,7 @@ class Synthesizer:
speaker_embeddings = torch.tensor(speaker_embeds).float().to(self.device)
# Inference
_, mels, alignments = self._model.generate(chars, speaker_embeddings, style_idx=style_idx)
_, mels, alignments = self._model.generate(chars, speaker_embeddings, style_idx=style_idx, min_stop_token=min_stop_token)
mels = mels.detach().cpu().numpy()
for m in mels:
# Trim silence from end of each spectrogram

10
synthesizer/models/tacotron.py
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@ -419,7 +419,7 @@ class Tacotron(nn.Module):
return mel_outputs, linear, attn_scores, stop_outputs
def generate(self, x, speaker_embedding=None, steps=200, style_idx=0):
def generate(self, x, speaker_embedding=None, steps=200, style_idx=0, min_stop_token=5):
self.eval()
device = next(self.parameters()).device # use same device as parameters
@ -454,9 +454,9 @@ class Tacotron(nn.Module):
scale[:] = 0.3
speaker_embedding = (gst_embed[style_idx] * scale).astype(np.float32)
speaker_embedding = torch.from_numpy(np.tile(speaker_embedding, (x.shape[0], 1))).to(device)
style_embed = self.gst(speaker_embedding)
style_embed = style_embed.expand_as(encoder_seq)
encoder_seq = encoder_seq + style_embed
style_embed = self.gst(speaker_embedding)
style_embed = style_embed.expand_as(encoder_seq)
encoder_seq = encoder_seq + style_embed
encoder_seq_proj = self.encoder_proj(encoder_seq)
# Need a couple of lists for outputs
@ -472,7 +472,7 @@ class Tacotron(nn.Module):
attn_scores.append(scores)
stop_outputs.extend([stop_tokens] * self.r)
# Stop the loop when all stop tokens in batch exceed threshold
if (stop_tokens > 0.5).all() and t > 10: break
if (stop_tokens * 10 > min_stop_token).all() and t > 10: break
# Concat the mel outputs into sequence
mel_outputs = torch.cat(mel_outputs, dim=2)

3
toolbox/__init__.py
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@ -234,7 +234,8 @@ class Toolbox:
texts = processed_texts
embed = self.ui.selected_utterance.embed
embeds = [embed] * len(texts)
specs = self.synthesizer.synthesize_spectrograms(texts, embeds, style_idx=int(self.ui.slider.value()))
min_token = int(self.ui.token_slider.value())
specs = self.synthesizer.synthesize_spectrograms(texts, embeds, style_idx=int(self.ui.style_slider.value()), min_stop_token=min_token)
breaks = [spec.shape[1] for spec in specs]
spec = np.concatenate(specs, axis=1)

36
toolbox/ui.py
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@ -588,18 +588,36 @@ class UI(QDialog):
self.seed_textbox = QLineEdit()
self.seed_textbox.setMaximumWidth(80)
layout_seed.addWidget(self.seed_textbox, 0, 1)
self.slider = QSlider(Qt.Horizontal)
self.slider.setTickInterval(1)
self.slider.setFocusPolicy(Qt.NoFocus)
self.slider.setSingleStep(1)
self.slider.setRange(-1, 9)
self.slider.setValue(-1)
layout_seed.addWidget(QLabel("Style:"), 0, 2)
layout_seed.addWidget(self.slider, 0, 3)
self.trim_silences_checkbox = QCheckBox("Enhance vocoder output")
self.trim_silences_checkbox.setToolTip("When checked, trims excess silence in vocoder output."
" This feature requires `webrtcvad` to be installed.")
layout_seed.addWidget(self.trim_silences_checkbox, 0, 4, 1, 2)
layout_seed.addWidget(self.trim_silences_checkbox, 0, 2, 1, 2)
self.style_slider = QSlider(Qt.Horizontal)
self.style_slider.setTickInterval(1)
self.style_slider.setFocusPolicy(Qt.NoFocus)
self.style_slider.setSingleStep(1)
self.style_slider.setRange(-1, 9)
self.style_value_label = QLabel("-1")
self.style_slider.setValue(-1)
layout_seed.addWidget(QLabel("Style:"), 1, 0)
self.style_slider.valueChanged.connect(lambda s: self.style_value_label.setNum(s))
layout_seed.addWidget(self.style_value_label, 1, 1)
layout_seed.addWidget(self.style_slider, 1, 3)
self.token_slider = QSlider(Qt.Horizontal)
self.token_slider.setTickInterval(1)
self.token_slider.setFocusPolicy(Qt.NoFocus)
self.token_slider.setSingleStep(1)
self.token_slider.setRange(3, 9)
self.token_value_label = QLabel("5")
self.token_slider.setValue(4)
layout_seed.addWidget(QLabel("Accuracy(精度):"), 2, 0)
self.token_slider.valueChanged.connect(lambda s: self.token_value_label.setNum(s))
layout_seed.addWidget(self.token_value_label, 2, 1)
layout_seed.addWidget(self.token_slider, 2, 3)
gen_layout.addLayout(layout_seed)
self.loading_bar = QProgressBar()