revert(splitter): output pure text, VibeVoice auto-wrap handles [1]: prefix
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@@ -100,10 +100,10 @@ class AIIA_Podcast_Splitter:
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else:
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print(f"{log} 跳过第三个说话人 '{speaker}' 的台词: {text[:30]}...")
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# 拼接每个说话人的文本,加上 [1]: 身份前缀
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# 每个 speaker 独立 TTS,所以统一用 [1]:(VibeVoice 官方格式)
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speaker_A_text = "\n".join(f"[1]: {t}" for t in texts_A)
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speaker_B_text = "\n".join(f"[1]: {t}" for t in texts_B)
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# 拼接每个说话人的文本
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# 每句之间用换行分隔(TTS 会在换行处产生自然停顿)
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speaker_A_text = "\n".join(texts_A)
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speaker_B_text = "\n".join(texts_B)
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split_map_json = json.dumps(split_map, ensure_ascii=False, indent=2)
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