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Skip SOS and EOS when processing sliced sentances (#179)

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This commit is contained in:
OedoSoldier
2023-11-14 08:45:00 +08:00
committed by GitHub
parent 52f895aa9f
commit ad694ee050
2 changed files with 54 additions and 10 deletions
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48
webui.py
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@@ -40,11 +40,15 @@ def generate_audio(
length_scale,
speaker,
language,
skip_start=False,
skip_end=False,
):
audio_list = []
silence = np.zeros(hps.data.sampling_rate // 2, dtype=np.int16)
# silence = np.zeros(hps.data.sampling_rate // 2, dtype=np.int16)
with torch.no_grad():
for piece in slices:
for idx, piece in enumerate(slices):
skip_start = (idx != 0) and skip_start
skip_end = (idx != len(slices) - 1) and skip_end
audio = infer(
piece,
sdp_ratio=sdp_ratio,
@@ -56,10 +60,12 @@ def generate_audio(
hps=hps,
net_g=net_g,
device=device,
skip_start=skip_start,
skip_end=skip_end,
)
audio16bit = gr.processing_utils.convert_to_16_bit_wav(audio)
audio_list.append(audio16bit)
audio_list.append(silence) # 将静音添加到列表中
# audio_list.append(silence) # 将静音添加到列表中
return audio_list
@@ -82,7 +88,9 @@ def tts_split(
para_list = re_matching.cut_para(text)
audio_list = []
if not cut_by_sent:
for p in para_list:
for idx, p in enumerate(para_list):
skip_start = idx != 0
skip_end = idx != len(para_list) - 1
audio = infer(
p,
sdp_ratio=sdp_ratio,
@@ -94,16 +102,22 @@ def tts_split(
hps=hps,
net_g=net_g,
device=device,
skip_start=skip_start,
skip_end=skip_end,
)
audio16bit = gr.processing_utils.convert_to_16_bit_wav(audio)
audio_list.append(audio16bit)
silence = np.zeros((int)(44100 * interval_between_para), dtype=np.int16)
audio_list.append(silence)
else:
for p in para_list:
for idx, p in enumerate(para_list):
skip_start = idx != 0
skip_end = idx != len(para_list) - 1
audio_list_sent = []
sent_list = re_matching.cut_sent(p)
for s in sent_list:
for idx, s in enumerate(sent_list):
skip_start = (idx != 0) and skip_start
skip_end = (idx != len(sent_list) - 1) and skip_end
audio = infer(
s,
sdp_ratio=sdp_ratio,
@@ -115,6 +129,8 @@ def tts_split(
hps=hps,
net_g=net_g,
device=device,
skip_start=skip_start,
skip_end=skip_end,
)
audio_list_sent.append(audio)
silence = np.zeros((int)(44100 * interval_between_sent))
@@ -150,9 +166,13 @@ def tts_fn(
np.concatenate([np.zeros(hps.data.sampling_rate // 2)]),
)
result = re_matching.text_matching(text)
for one in result:
for idx, one in enumerate(result):
skip_start = idx != 0
skip_end = idx != len(result) - 1
_speaker = one.pop()
for lang, content in one:
for idx, (lang, content) in enumerate(one):
skip_start = (idx != 0) and skip_start
skip_end = (idx != len(one) - 1) and skip_end
audio_list.extend(
generate_audio(
content.split("|"),
@@ -162,16 +182,22 @@ def tts_fn(
length_scale,
_speaker,
lang,
skip_start,
skip_end,
)
)
elif language.lower() == "auto":
sentences_list = split_by_language(text, target_languages=["zh", "ja", "en"])
for sentences, lang in sentences_list:
for idx, (sentences, lang) in enumerate(sentences_list):
skip_start = idx != 0
skip_end = idx != len(sentences_list) - 1
lang = lang.upper()
if lang == "JA":
lang = "JP"
sentences = sentence_split(sentences, max=250)
for content in sentences:
for idx, content in enumerate(sentences):
skip_start = (idx != 0) and skip_start
skip_end = (idx != len(sentences) - 1) and skip_end
audio_list.extend(
generate_audio(
content.split("|"),
@@ -181,6 +207,8 @@ def tts_fn(
length_scale,
speaker,
lang,
skip_start,
skip_end,
)
)
else: