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Complex spectrogram enhancement by convolutional neural network with multi-metrics learning.

, , , and . MLSP, page 1-6. IEEE, (2017)

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Unsupervised neural adaptation model based on optimal transport for spoken language identification., , , and . CoRR, (2020)Optimal Classifier Parameter Status Selection Based on Bayes Boundary-ness for Multi-ProtoType and Multi-Layer Perceptron Classifiers., , , , , , and . IUKM, volume 11471 of Lecture Notes in Computer Science, page 295-307. Springer, (2019)Contributions of Jitter and Shimmer in the Voice for Fake Audio Detection., , , and . IEEE Access, (2023)Siamese Neural Network with Joint Bayesian Model Structure for Speaker Verification., , , and . APSIPA ASC, page 769-774. IEEE, (2021)CS-REP: Making Speaker Verification Networks Embracing Re-Parameterization., , , , , , and . ICASSP, page 7082-7086. IEEE, (2022)Speech restoration based on deep learning autoencoder with layer-wised pretraining., , , and . INTERSPEECH, page 1504-1507. ISCA, (2012)Data Augmentation Using McAdams-Coefficient-Based Speaker Anonymization for Fake Audio Detection., , , , , , , , , and . INTERSPEECH, page 664-668. ISCA, (2022)Improving Perceptual Quality by Phone-Fortified Perceptual Loss Using Wasserstein Distance for Speech Enhancement., , , , and . Interspeech, page 196-200. ISCA, (2021)Ensemble speaker modeling using speaker adaptive training deep neural network for speaker adaptation., , , and . INTERSPEECH, page 2892-2896. ISCA, (2015)F0 Contour Analysis Based on Empirical Mode Decomposition for DNN Acoustic Modeling in Mandarin Speech Recognition., , , and . INTERSPEECH, page 973-977. ISCA, (2016)