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An investigation on DNN-derived bottleneck features for GMM-HMM based robust speech recognition.

, , , and . ChinaSIP, page 30-34. IEEE, (2015)

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Covariance Based Deep Feature for Text-Dependent Speaker Verification., , , and . IScIDE, volume 11266 of Lecture Notes in Computer Science, page 231-242. Springer, (2018)Cambridge university transcription systems for the multi-genre broadcast challenge., , , , , , , and . ASRU, page 639-646. IEEE, (2015)Cluster adaptive training for deep neural network., , , , and . ICASSP, page 4325-4329. IEEE, (2015)Fast Adaptation on Deepmixture Generative Network Based Acoustic Modeling., , and . ICASSP, page 5944-5948. IEEE, (2018)Integrated adaptation with multi-factor joint-learning for far-field speech recognition., , , and . ICASSP, page 5770-5774. IEEE, (2016)Stochastic data sweeping for fast DNN training., , , , and . ICASSP, page 240-244. IEEE, (2014)Very deep convolutional neural networks for robust speech recognition., and . SLT, page 481-488. IEEE, (2016)End-to-End Overlapped Speech Detection and Speaker Counting with Raw Waveform., , , and . ASRU, page 660-666. IEEE, (2019)Single-channel multi-talker speech recognition with permutation invariant training., , and . Speech Commun., (2018)Erratum to: Past review, current progress, and challenges ahead on the cocktail party problem., , , , and . Frontiers Inf. Technol. Electron. Eng., 19 (4): 582 (2018)