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SNDCNN: Self-Normalizing Deep CNNs with Scaled Exponential Linear Units for Speech Recognition.

, , , , , and . ICASSP, page 6854-6858. IEEE, (2020)

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Acoustic Model Fusion For End-to-End Speech Recognition., , , , , , , , , and 1 other author(s). ASRU, page 1-7. IEEE, (2023)Progress on Mandarin conversational telephone speech recognition., , , , , , , , , and 2 other author(s). ISCSLP, page 1-4. IEEE, (2004)Improved morphological decomposition for Arabic broadcast news transcription., , , and . ICASSP, page 4309-4312. IEEE, (2009)Jointly optimized discriminative features for speech recognition., , and . INTERSPEECH, page 2618-2621. ISCA, (2010)Unsupervised adaptation for deep neural network using linear least square method., , , , and . INTERSPEECH, page 2887-2891. ISCA, (2015)Mandarin Word-Character Hybrid-Input Neural Network Language Model., , and . INTERSPEECH, page 625-628. ISCA, (2011)Region Dependent Transform on MLP Features for Speech Recognition., , , and . INTERSPEECH, page 221-224. ISCA, (2011)Neural Network Bottleneck Features for Language Identification., , , , , , and . Odyssey, page 299-304. ISCA, (2014)SNDCNN: Self-Normalizing Deep CNNs with Scaled Exponential Linear Units for Speech Recognition., , , , , and . ICASSP, page 6854-6858. IEEE, (2020)Web-Data Augmented Language Models for Mandarin Conversational Speech Recognition., , , , , and . ICASSP (1), page 589-592. IEEE, (2005)