#4645 TaskCfgVTT(is_cuda=True, uuid='e979bed083', cache_folder='D:/pyvideotrans/tmp/13044/e979bed083', target_dir='C:/Users/Ad

219.76* Posted at: 4 hours ago 👁13

语音识别阶段出错 [faster-whisper(本地)] 出错了,可能内存或显存不足 [GPU0]
Traceback (most recent call last):
File "videotrans\configure\_base.py", line 281, in _new_process
File "videotrans\process\signelobj.py", line 80, in submit_task_gpu
File "concurrent\futures\process.py", line 720, in submit
concurrent.futures.process.BrokenProcessPool: A child process terminated abruptly, the process pool is not usable anymore

Traceback (most recent call last):
File "videotrans\configure\_base.py", line 281, in _new_process
File "videotrans\process\signelobj.py", line 80, in submit_task_gpu
File "concurrent\futures\process.py", line 720, in submit
concurrent.futures.process.BrokenProcessPool: A child process terminated abruptly, the process pool is not usable anymore

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "videotrans\task\job.py", line 105, in run
File "videotrans\task\trans_create.py", line 360, in recogn
File "videotrans\recognition\__init__.py", line 272, in run
File "videotrans\recognition\_base.py", line 143, in run
File "videotrans\recognition\_overall.py", line 33, in _exec
File "videotrans\recognition\_overall.py", line 105, in _faster
File "videotrans\configure\_base.py", line 299, in _new_process
RuntimeError: 出错了,可能内存或显存不足 [GPU0]
Traceback (most recent call last):
File "videotrans\configure\_base.py", line 281, in _new_process
File "videotrans\process\signelobj.py", line 80, in submit_task_gpu
File "concurrent\futures\process.py", line 720, in submit
concurrent.futures.process.BrokenProcessPool: A child process terminated abruptly, the process pool is not usable anymore
TaskCfgVTT(is_cuda=True, uuid='e979bed083', cache_folder='D:/pyvideotrans/tmp/13044/e979bed083', target_dir='C:/Users/Administrator/Desktop/healthmaneger/_video_out/Battlefield Medicine Is Brutal_1080p-mp4', source_language='英语', source_language_code='en', source_sub='C:/Users/Administrator/Desktop/healthmaneger/_video_out/Battlefield Medicine Is Brutal_1080p-mp4/en.srt', source_wav='D:/pyvideotrans/tmp/13044/e979bed083/en.wav', source_wav_output='C:/Users/Administrator/Desktop/healthmaneger/_video_out/Battlefield Medicine Is Brutal_1080p-mp4/en.m4a', target_language='简体中文', target_language_code='zh-cn', target_sub='C:/Users/Administrator/Desktop/healthmaneger/_video_out/Battlefield Medicine Is Brutal_1080p-mp4/zh-cn.srt', target_wav='D:/pyvideotrans/tmp/13044/e979bed083/target.wav', target_wav_output='C:/Users/Administrator/Desktop/healthmaneger/_video_out/Battlefield Medicine Is Brutal_1080p-mp4/zh-cn.m4a', name='C:/Users/Administrator/Desktop/healthmaneger/Battlefield Medicine Is Brutal_1080p.mp4', noextname='Battlefield Medicine Is Brutal_1080p', basename='Battlefield Medicine Is Brutal_1080p.mp4', ext='mp4', dirname='C:/Users/Administrator/Desktop/healthmaneger', shound_del_name=None, translate_type=0, tts_type=10, volume='+0%', pitch='+0Hz', voice_rate='+0%', voice_role='No', voice_autorate=False, video_autorate=False, remove_silent_mid=False, align_sub_audio=False, detect_language='en', recogn_type=0, model_name='large-v3-turbo', shibie_audio=None, remove_noise=False, enable_diariz=False, nums_diariz=0, rephrase=0, fix_punc=False, subtitle_language=None, app_mode='tiqu', subtitles='', targetdir_mp4='C:/Users/Administrator/Desktop/healthmaneger/_video_out/Battlefield Medicine Is Brutal_1080p-mp4/Battlefield Medicine Is Brutal_1080p.mp4', novoice_mp4='D:/pyvideotrans/tmp/13044/e979bed083/novoice.mp4', is_separate=False, instrument=None, vocal=None, back_audio='', clear_cache=False, background_music=None, subtitle_type=0, only_out_mp4=False, recogn2pass=False, output_srt=0, copysrt_rawvideo=False)


=
system:Windows-10-10.0.26100-SP0
version:v3.98
frozen:True
language:zh
root_dir:D:/pyvideotrans

1 Replies

这是由于显存不足导致 faster-whisper 的进程崩溃(large-v3-turbo 模型需约 6-10GB 显存)。请按以下顺序尝试解决:

  1. 切换为更小的模型:在主界面的语音识别模型中改为 basemedium(large 模型对显存要求高)。
  2. 调整高级参数降低显存占用:菜单栏 → 工具/选项 → 高级选项 → 语音识别参数,做以下修改:

    • CUDA数据类型 从默认改为 int8
    • beam_size 改为 1
    • best_of 改为 1
    • 勾选 Whisper预分割音频
    • 最长语音持续秒数 改为 10 或更小
  3. 关闭不必要的功能:若开启了 二次识别,请取消勾选。
  4. 确认硬件支持:检查是否已安装 CUDA 12.8+ 及 cuDNN 9.x;若显存不足 8GB,建议使用 CPU 模式(不勾选 CUDA 加速)。
  5. 单视频处理:若正在批量处理多个视频,请勾选 高级选项 → 批量翻译时强制串行

若问题依旧,请提供 logs/ 文件夹下最新的日志文件底部 30 行内容以便进一步分析。

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