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Multi-Channel Training for End-to-End Speaker Recognition Under Reverberant and Noisy Environment.

, , and . INTERSPEECH, page 4365-4369. ISCA, (2019)

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Embedding Aggregation for Far-Field Speaker Verification with Distributed Microphone Arrays., and . SLT, page 308-315. IEEE, (2021)The DKU-JNU-EMA Electromagnetic Articulography Database on Mandarin and Chinese Dialects with Tandem Feature based Acoustic-to-Articulatory Inversion., , , , , and . ISCSLP, page 235-239. IEEE, (2018)An Iterative Framework for Self-Supervised Deep Speaker Representation Learning., , and . ICASSP, page 6728-6732. IEEE, (2021)The DKU-Duke-Lenovo System Description for the Fearless Steps Challenge Phase III., , , , , , and . Interspeech, page 1044-1048. ISCA, (2021)Deep Speaker Embeddings with Convolutional Neural Network on Supervector for Text-Independent Speaker Recognition., , and . APSIPA, page 1478-1482. IEEE, (2018)Mandarin electrolaryngeal voice conversion with combination of Gaussian mixture model and non-negative matrix factorization., , , and . APSIPA, page 1360-1363. IEEE, (2017)The DKU Replay Detection System for the ASVspoof 2019 Challenge: On Data Augmentation, Feature Representation, Classification, and Fusion., , , and . INTERSPEECH, page 1023-1027. ISCA, (2019)Leveraging ASR Pretrained Conformers for Speaker Verification Through Transfer Learning and Knowledge Distillation., and . IEEE ACM Trans. Audio Speech Lang. Process., (2024)The DKU-Duke-Lenovo System Description for the Third DIHARD Speech Diarization Challenge., , , , and . CoRR, (2021)Locality sensitive discriminant analysis for speaker verification., , , and . APSIPA, page 1-5. IEEE, (2016)