forked from killua/TakwayPlatform
86 lines
3.6 KiB
Python
86 lines
3.6 KiB
Python
from modelscope.pipelines import pipeline
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import numpy as np
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import os
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ERES2NETV2 = {
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"task": 'speaker-verification',
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"model_name": 'damo/speech_eres2netv2_sv_zh-cn_16k-common',
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"model_revision": 'v1.0.1',
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"save_embeddings": False
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}
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# 保存 embedding 的路径
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DEFALUT_SAVE_PATH = os.path.join(os.path.dirname(os.path.dirname(__name__)), "speaker_embedding")
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class speaker_verfication:
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def __init__(self,
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task='speaker-verification',
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model_name='damo/speech_eres2netv2_sv_zh-cn_16k-common',
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model_revision='v1.0.1',
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device="cuda",
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save_embeddings=False):
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self.pipeline = pipeline(
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task=task,
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model=model_name,
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model_revision=model_revision,
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device=device)
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self.save_embeddings = save_embeddings
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def wav2embeddings(self, speaker_1_wav, save_path=None):
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result = self.pipeline([speaker_1_wav], output_emb=True)
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speaker_1_emb = result['embs'][0]
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if save_path is not None:
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np.save(save_path, speaker_1_emb)
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return speaker_1_emb
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def _verifaction(self, speaker_1_wav, speaker_2_wav, threshold, save_path):
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if not self.save_embeddings:
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result = self.pipeline([speaker_1_wav, speaker_2_wav], thr=threshold)
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return result["text"]
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else:
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result = self.pipeline([speaker_1_wav, speaker_2_wav], thr=threshold, output_emb=True)
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speaker1_emb = result["embs"][0]
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speaker2_emb = result["embs"][1]
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np.save(os.path.join(save_path, "speaker_1.npy"), speaker1_emb)
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return result['outputs']["text"]
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def _verifaction_from_embedding(self, base_emb, speaker_2_wav, threshold):
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base_emb = np.load(base_emb)
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result = self.pipeline([speaker_2_wav], output_emb=True)
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speaker2_emb = result["embs"][0]
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similarity = np.dot(base_emb, speaker2_emb) / (np.linalg.norm(base_emb) * np.linalg.norm(speaker2_emb))
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if similarity > threshold:
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return "yes"
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else:
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return "no"
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def verfication(self,
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base_emb=None,
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speaker_1_wav=None,
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speaker_2_wav=None,
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threshold=0.333,
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save_path=None):
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if base_emb is not None and speaker_1_wav is not None:
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raise ValueError("Only need one of them, base_emb or speaker_1_wav")
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if base_emb is not None and speaker_2_wav is not None:
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return self._verifaction_from_embedding(base_emb, speaker_2_wav, threshold)
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elif speaker_1_wav is not None and speaker_2_wav is not None:
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return self._verifaction(speaker_1_wav, speaker_2_wav, threshold, save_path)
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else:
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raise NotImplementedError
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if __name__ == '__main__':
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verifier = speaker_verfication(**ERES2NETV2)
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verifier = speaker_verfication(save_embeddings=False)
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result = verifier.verfication(base_emb=None, speaker_1_wav=r"C:\Users\bing\Downloads\speaker1_a_cn_16k.wav",
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speaker_2_wav=r"C:\Users\bing\Downloads\speaker2_a_cn_16k.wav",
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threshold=0.333,
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save_path=r"D:\python\irving\takway_base-main\savePath"
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)
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print("---")
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print(result)
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print(verifier.verfication(r"D:\python\irving\takway_base-main\savePath\speaker_1.npy",
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speaker_2_wav=r"C:\Users\bing\Downloads\speaker1_b_cn_16k.wav",
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threshold=0.333,
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)) |