#7966 语音识别阶段出错[Nemotron-3.5-asr-0.6b(内置)] Sequence Length: 12463 has to be less or equal than config.max_position_embeddings 5

45.88**0 Posted at: 1 hour ago

语音识别阶段出错[Nemotron-3.5-asr-0.6b(内置)] Sequence Length: 12463 has to be less or equal than config.max_position_embeddings 5000.:Traceback (most recent call last):
File "videotrans\process\stt_nemotron.py", line 41, in nemotron_asr
File "D:\program\videotrans\_internal\transformers\models\nemotron3_5_asr\generation_nemotron3_5_asr.py", line 35, in generate

return super().generate(inputs=inputs, generation_config=generation_config, **kwargs)

File "D:\program\videotrans\_internal\transformers\models\nemotron_asr_streaming\generation_nemotron_asr_streaming.py", line 228, in generate

outputs = super().generate(inputs=inputs, generation_config=generation_config, **kwargs)

File "D:\program\videotrans\_internal\transformers\models\parakeet\generation_parakeet.py", line 256, in generate

outputs = super().generate(inputs=inputs, generation_config=generation_config, **kwargs)

File "D:\program\videotrans\_internal\torch\utils\_contextlib.py", line 116, in decorate_contex
......
tput_capturing.py", line 252, in wrapper

outputs = func(self, *args, **kwargs)

File "D:\program\videotrans\_internal\transformers\utils\generic.py", line 911, in wrapper

output = func(self, *args, **kwargs)

File "D:\program\videotrans\_internal\transformers\models\nemotron_asr_streaming\modeling_nemotron_asr_streaming.py", line 1007, in forward

position_embeddings = self.encode_positions(inputs_embeds, cached_frames=cached_frames)

File "D:\program\videotrans\_internal\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl

return self._call_impl(*args, **kwargs)

File "D:\program\videotrans\_internal\torch\nn\modules\module.py", line 1762, in _call_impl

return forward_call(*args, **kwargs)

File "D:\program\videotrans\_internal\torch\utils\_contextlib.py", line 116, in decorate_context

return func(*args, **kwargs)

File "D:\program\videotrans\_internal\transformers\models\nemotron_asr_streaming\modeling_nemotron_asr_streaming.py", line 376, in forward

raise ValueError(

ValueError: Sequence Length: 12463 has to be less or equal than config.max_position_embeddings 5000.

self.cfg=[TaskCfgVTT]当前工作模式: 转录并翻译字幕
原始输入文件名: D:/Downloads/Videos/!Submaker/HUNTA-038-U_01.mp4,
输出结果保存到文件夹: D:/Downloads/Videos/!Submaker/HUNTA-038-U_01-mp4,
临时文件夹: D:/program/videotrans/tmp/14884/ad3d7e9ef9
已选 清理已存在
未启用CUDA加速
未选 降噪
语音识别:Nemotron-3.5-asr-0.6b(内置), , 发音语言: 日语, 断句方式:LLM重新断句
翻译渠道:DeepSeek,原始语言:日语,目标语言:简体中文, 未选 发送完整字幕
输出字幕格式: 单字幕
代理地址:http://127.0.0.1:7897


=
system:Windows-10-10.0.26300-SP0
version:v4.14
frozen:True
language:zh_CN
root_dir:D:/program/videotrans

1 Replies

#1 DeepSeek reply at 1 hour ago

该报错的直接含义是:送入 Nemotron-3.5-asr-0.6b(内置) 模型的单段音频过长——该模型位置编码上限为 5000,而实际输入序列长度达 12463,即 VAD 未能把音频切成足够短的片段(超长片段一般由 VAD 切分参数过大、或某段音频中间几乎没有停顿导致)。

注意:知识库中未收录此模型该报错的官方处理说明,以下为可按参数逻辑执行的排查步骤。

建议操作:

  1. 打开 菜单(Menu) → 工具/选项(Tools/Options) → 高级选项(Advanced Options) → 语音识别参数(ASR Settings),把切分参数调小,强制产生更短的音频片段:

    • 最长语音持续(秒)/(VAD:max speech duration(s)):改为 3 或 4
    • 静音分割持续毫秒/(VAD:Min silence duration for split(ms)):改为 300~400
    • 确保 最短语音持续(毫秒) < 最长语音持续(秒) × 1000(例如最长 3 秒时,最短不要设成 3000 及以上)
  2. 回到主界面勾选清理已生成,重新执行(否则会复用上一次的切片与缓存)。
  3. 若调整后仍报同一错误,说明该音频(本次为 33 分钟长视频)不适合用该渠道处理,建议改用 faster-whisper(内置) 的 large-v3 或 openai-whisper(内置) 的 large-v3 识别日语(两者对长音频兼容性更好,也支持 启用CUDA加速)。
  4. 若以上均无效,请提供软件安装目录下 logs/ 文件夹中最新的日志文件(复制底部约 30 行报错信息)以便分析。

请查阅相关文档:

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