#7166 语音识别阶段出错[阿里FunASR(本地)(内置)] Subprocess Error: regex>=2025.10.22 is required for a normal functioning of this module, but

113.253**7 Posted at: 1 hour ago

语音识别阶段出错[阿里FunASR(本地)(内置)] Subprocess Error: regex>=2025.10.22 is required for a normal functioning of this module, but found regex==2023.10.3.
Try: pip install transformers -U or pip install -e '.[dev]' if you're working with git main
Traceback (most recent call last):

File "videotrans\task\job.py", line 35, in run

File "videotrans\task\job.py", line 102, in process_task

File "videotrans\task\speech2text.py", line 100, in recogn

File "videotrans\recognition\__init__.py", line 228, in run

File "videotrans\recognition\_base.py", line 97, in run

File "videotrans\recognition\_funasr.py", line 72, in _exec

File "videotrans\configure\base.py", line 264, in _new_process

videotrans.configure.excepts.VideoTransError: Subprocess Error: regex>=2025.10.22 is required for a normal functioning of this module, but found regex==2023.10.3.
Try: pip install transformers -U or pip install -e '.[dev]' if you're working with git main
[SpeechToText]语音转录: self.out_format='srt',self.copysrt_rawvideo=False,self.spk_insert=False
[TaskCfgSTT]
原始输入文件名: E:/新加坡'仇印'燃燒 三大高官發聲急止血!菲律賓內戰 小馬可仕硬捅杜特蒂家族!高市早苗驚傳缺席亞運【全球大視野】完整版下集 @全球大視野Global_Vision.mp4,
输出结果保存到文件夹: E:/win-pyvideotrans-v4.00-525/output/recogn,
临时文件夹: E:/win-pyvideotrans-v4.00-525/tmp/13244/c51688b9bc
未启用CUDA加速
未选 降噪
语音识别:阿里FunASR(本地)(内置), Fun-ASR-MLT-Nano-2512 断句方式:默认断句
发音语言:zh-tw
未选 降噪


=
system:Windows-10-10.0.26200-SP0
version:v4.12
frozen:True
language:zh
root_dir:E:/win-pyvideotrans-v4.00-525

1 Replies

#1 DeepSeek reply at 1 hour ago

这是 regex 模块版本过低导致的依赖冲突(当前为 2023.10.3,而阿里 FunASR 渠道所需 transformers 要求 >= 2025.10.22)。

你是 Windows 预打包版用户(frozen:True),无法直接运行 pip 命令修复依赖,建议按以下顺序处理:

  1. 确认版本:你的软件目录名为 win-pyvideotrans-v4.00-525,但日志显示版本为 v4.12,说明是旧目录叠加了补丁包。此类混合覆盖极易导致依赖库文件版本错乱。
  2. 下载完整包覆盖:前往官网下载最新 v4.12 的完整版压缩包(约 2.7GB),解压到全新英文路径(如 D:\pyVideoTrans),不要与旧目录混用。
  3. 重新尝试:在全新完整版中再次使用阿里 FunASR(内置) 渠道。
  4. 替代方案:若仍报错,可先改用 faster-whisper(内置) 渠道(默认推荐),中文识别效果同样良好,可绕过此依赖问题。

请查阅相关文档:

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