49 lines
1.7 KiB
Python
49 lines
1.7 KiB
Python
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import unittest
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import numpy as np
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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from modelscope.utils.logger import get_logger
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logger = get_logger()
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class TestXVectorInferencePipelines(unittest.TestCase):
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def test_funasr_path(self):
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import funasr
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import os
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logger.info("run_dir:{0} ; funasr_path: {1}".format(os.getcwd(), funasr.__file__))
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def test_inference_pipeline(self):
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inference_sv_pipline = pipeline(
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task=Tasks.speaker_verification,
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model="damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch",
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)
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# the same speaker
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rec_result = inference_sv_pipline(
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audio_in=(
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_enroll.wav",
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_same.wav",
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)
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)
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assert (
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abs(rec_result["scores"][0] - 0.85) < 0.1 and abs(rec_result["scores"][1] - 0.14) < 0.1
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)
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logger.info(f"Similarity {rec_result['scores']}")
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# different speaker
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rec_result = inference_sv_pipline(
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audio_in=(
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_enroll.wav",
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/sv_example_different.wav",
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)
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)
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assert abs(rec_result["scores"][0] - 0.0) < 0.1 and abs(rec_result["scores"][1] - 1.0) < 0.1
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logger.info(f"Similarity {rec_result['scores']}")
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if __name__ == "__main__":
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unittest.main()
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