Abstract:In recent years, text-independent speaker verification has remained a hot research topic, especially for the limited enrollment and/or test data. At the same time, due to the lack of sufficient training data, the study of low-resource few-shot speaker verification, makes the models prone to overfitting and low accuracy of recognition. Therefore, a bidirectional sampling aggregation-based meta metric learning method is proposed to solve the low accuracy problem of speaker recognition in a low-resource environme… Show more
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