A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.
场景socket通信 ,API:pipelines,Task:'speaker-verification'的,方法:pipeline[wav1,wav2] ,报错:choose a window size 400 that is [2, 0]
Debug不报错,RUN会报错。
方法拿出来单独测试就没问题。
To Reproduce
Steps to reproduce the behavior (always include the command you ran):
Run cmd '....'
See error
Code sample
self.pipline = pipeline(
task='speaker-verification',
model=self.model_path,
)
wav_dict = {file_path: None for file_path in wav_files}
for key, value in wav_dict.items():
time.sleep(0.1)
print("说话人确认计算中...")
print("key:", key)
print("string_path:", string_path)
result = self.pipline([string_path, key])
wav_dict[key] = result
print("key:", key)
print("res:", wav_dict[key])
print("\n",)
🐛 Bug
场景socket通信 ,API:pipelines,Task:'speaker-verification'的,方法:pipeline[wav1,wav2] ,报错:choose a window size 400 that is [2, 0] Debug不报错,RUN会报错。 方法拿出来单独测试就没问题。
To Reproduce
Steps to reproduce the behavior (always include the command you ran):
Code sample
Environment
pip
, source):