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- import time
- from http import HTTPStatus
- from dashscope.audio.asr import Recognition
- # 若没有将API Key配置到环境变量中，需将下面这行代码注释放开，并将apiKey替换为自己的API Key
- import dashscope
- dashscope.api_key = "sk-92f2fec23dc94de49a31c9945d04e5f7"
- # 使用本地已有的wav文件
- audio_file = 'asr_example.wav'
- print(f'开始识别文件: {audio_file}')
- start_time = time.time()
- recognition = Recognition(model='paraformer-realtime-v2',
- format='wav',
- sample_rate=16000,
- # "language_hints"只支持paraformer-v2和paraformer-realtime-v2模型
- language_hints=['zh', 'en'],
- callback=None)
- result = recognition.call(audio_file)
- end_time = time.time()
- elapsed_time = end_time - start_time
- if result.status_code == HTTPStatus.OK:
- print('识别结果：')
- print(result.get_sentence())
- print(f'\n识别耗时: {elapsed_time:.3f} 秒')
- print(f'开始时间: {time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(start_time))}')
- print(f'结束时间: {time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(end_time))}')
- else:
- print('Error: ', result.message)
- print(f'识别失败，耗时: {elapsed_time:.3f} 秒')
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