A Pre-trained Model Based Recognition Method for Speech Deepfake Algorithms
To improve the accuracy of the recognition model of speech deepfake algorithms and the generalization of the recognition of unknown deepfake algorithms,a recognition method based on the pre-trained model is proposed.Based on the real and fake speech dataset,the HuBERT pre-trained model is fine-tuned and the manifold space is constructed based on the deep embedded features output from the model,and the determination of deepfake algorithms is carried out by measuring the geodesic distances between the manifold spaces of different deepfake algorithms.Experiments show that the proposed method can realize the recognition of known and unknown deepfake algorithms more effectively.
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