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Running
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Zero
mrfakename
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src/f5_tts/infer/utils_infer.py
CHANGED
@@ -186,17 +186,17 @@ def preprocess_ref_audio_text(ref_audio_orig, ref_text, show_info=print, device=
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non_silent_segs = silence.split_on_silence(aseg, min_silence_len=1000, silence_thresh=-50, keep_silence=1000)
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non_silent_wave = AudioSegment.silent(duration=0)
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for non_silent_seg in non_silent_segs:
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-
if len(non_silent_wave) >
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show_info("Audio is over 15s, clipping short.")
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break
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non_silent_wave += non_silent_seg
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# 2. try to find short silence for clipping if 1. failed
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if len(non_silent_wave) > 15000:
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-
non_silent_segs = silence.split_on_silence(aseg, min_silence_len=
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non_silent_wave = AudioSegment.silent(duration=0)
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for non_silent_seg in non_silent_segs:
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-
if len(non_silent_wave) >
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show_info("Audio is over 15s, clipping short.")
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break
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non_silent_wave += non_silent_seg
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non_silent_segs = silence.split_on_silence(aseg, min_silence_len=1000, silence_thresh=-50, keep_silence=1000)
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non_silent_wave = AudioSegment.silent(duration=0)
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for non_silent_seg in non_silent_segs:
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+
if len(non_silent_wave) > 6000 and len(non_silent_wave + non_silent_seg) > 16000:
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show_info("Audio is over 15s, clipping short.")
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break
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non_silent_wave += non_silent_seg
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# 2. try to find short silence for clipping if 1. failed
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if len(non_silent_wave) > 15000:
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+
non_silent_segs = silence.split_on_silence(aseg, min_silence_len=100, silence_thresh=-40, keep_silence=1000)
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non_silent_wave = AudioSegment.silent(duration=0)
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for non_silent_seg in non_silent_segs:
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+
if len(non_silent_wave) > 6000 and len(non_silent_wave + non_silent_seg) > 16000:
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show_info("Audio is over 15s, clipping short.")
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break
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non_silent_wave += non_silent_seg
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