Update inference_webui.py
Browse files- inference_webui.py +6 -1
inference_webui.py
CHANGED
@@ -424,19 +424,24 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
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print(i18n("实际输入的目标文本(切句后):"), text)
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texts = text.split("\n")
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texts = process_text(texts)
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texts = merge_short_text_in_array(texts, 5)
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audio_opt = []
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if not ref_free:
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phones1,bert1,norm_text1=get_phones_and_bert(prompt_text, prompt_language, version)
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-
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for i_text,text in enumerate(texts):
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# 解决输入目标文本的空行导致报错的问题
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if (len(text.strip()) == 0):
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continue
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if (text[-1] not in splits): text += "。" if text_language != "en" else "."
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print(i18n("实际输入的目标文本(每句):"), text)
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phones2,bert2,norm_text2=get_phones_and_bert(text, text_language, version)
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print(i18n("前端处理后的文本(每句):"), norm_text2)
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if not ref_free:
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bert = torch.cat([bert1, bert2], 1)
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all_phoneme_ids = torch.LongTensor(phones1+phones2).to(device).unsqueeze(0)
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print(i18n("实际输入的目标文本(切句后):"), text)
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texts = text.split("\n")
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texts = process_text(texts)
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print(2)
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texts = merge_short_text_in_array(texts, 5)
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print(3)
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audio_opt = []
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if not ref_free:
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phones1,bert1,norm_text1=get_phones_and_bert(prompt_text, prompt_language, version)
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print(4)
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for i_text,text in enumerate(texts):
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# 解决输入目标文本的空行导致报错的问题
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if (len(text.strip()) == 0):
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continue
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print(5)
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if (text[-1] not in splits): text += "。" if text_language != "en" else "."
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print(i18n("实际输入的目标文本(每句):"), text)
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print(6)
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phones2,bert2,norm_text2=get_phones_and_bert(text, text_language, version)
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print(i18n("前端处理后的文本(每句):"), norm_text2)
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print(7)
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if not ref_free:
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bert = torch.cat([bert1, bert2], 1)
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all_phoneme_ids = torch.LongTensor(phones1+phones2).to(device).unsqueeze(0)
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