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Multi-View and Multi-Objective Semi-Supervised Learning for HMM-Based Automatic Speech Recognition.

, , and . IEEE Trans. Speech Audio Process., 20 (7): 1923-1935 (2012)

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An empirical study of confusion modeling in keyword search for low resource languages., , , , , , , and . ASRU, page 464-469. IEEE, (2013)An investigation of heuristic, manual and statistical pronunciation derivation for Pashto., , , and . ASRU, page 249-253. IEEE, (2011)Cyclegan Bandwidth Extension Acoustic Modeling for Automatic Speech Recognition., and . ICASSP, page 6780-6784. IEEE, (2019)Multi-View and Multi-Objective Semi-Supervised Learning for HMM-Based Automatic Speech Recognition., , and . IEEE Trans. Speech Audio Process., 20 (7): 1923-1935 (2012)A language model adaptation approach based on text classification., , , and . INTERSPEECH, page 516-519. ISCA, (2000)A noise-robust ASR back-end technique based on weighted viterbi recognition., , and . INTERSPEECH, page 2169-2172. ISCA, (2003)Decentralized Bilevel Optimization for Personalized Client Learning., , , , and . ICASSP, page 5543-5547. IEEE, (2022)Speech Emotion Recognition with Complementary Acoustic Representations., , , and . SLT, page 846-852. IEEE, (2022)Dilated Recurrent Neural Networks., , , , , , , , , and . NIPS, page 77-87. (2017)Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks., , , , , , , , and . NeurIPS, page 4901-4910. (2019)