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Unidirectional Neural Network Architectures for End-to-End Automatic Speech Recognition.

, , and . INTERSPEECH, page 76-80. ISCA, (2019)

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Fast on-the-fly composition for weighted finite-state transducers in 1.8 million-word vocabulary continuous speech recognition., , and . INTERSPEECH, page 289-292. ISCA, (2004)Efficient Beam Width Control to Suppress Excessive Speech Recognition Computation Time Based on Prior Score Range Normalization., , , , , and . INTERSPEECH, page 1011-1014. ISCA, (2012)Improvements of search error risk minimization in viterbi beam search for speech recognition., , and . INTERSPEECH, page 1962-1965. ISCA, (2010)Variable Attention Masking for Configurable Transformer Transducer Speech Recognition., , , , , , , , , and 2 other author(s). CoRR, (2022)Momentum Pseudo-Labeling: Semi-Supervised ASR With Continuously Improving Pseudo-Labels., , , and . IEEE J. Sel. Top. Signal Process., 16 (6): 1424-1438 (2022)End-to-End Speech Recognition: A Survey., , , , and . IEEE ACM Trans. Audio Speech Lang. Process., (2024)Minimum word error training of long short-term memory recurrent neural network language models for speech recognition., , , and . ICASSP, page 5990-5994. IEEE, (2016)Joint CTC-attention based end-to-end speech recognition using multi-task learning., , and . ICASSP, page 4835-4839. IEEE, (2017)Graph index based query-by-example search on a large speech data set., , , , and . ICASSP, page 8520-8524. IEEE, (2013)Efficient training of discriminative language models by sample selection., , and . Speech Commun., 54 (6): 791-800 (2012)