from transformers import Wav2Vec2FeatureExtractor, WavLMForXVector import torch import librosa model_name = "microsoft/wavlm-base-plus-sv" feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(model_name) model = WavLMForXVector.from_pretrained(model_name) def get_audio_similarity(audio_path1, audio_path2) -> float: target_sr = 16000 waveform1, sample_rate1 = librosa.load(audio_path1) wavef


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