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DO as I Mean, Not as I Say: Sequence Loss Training for Spoken Language Understanding.

, , , , , , and . ICASSP, page 7473-7477. IEEE, (2021)

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Constrained discriminative training of N-gram language models., , and . ASRU, page 311-316. IEEE, (2009)Neural Composition: Learning to Generate from Multiple Models., , and . CoRR, (2020)Audio-attention discriminative language model for ASR rescoring., and . CoRR, (2019)Acoustically discriminative language model training with pseudo-hypothesis., , , , , and . Speech Commun., 54 (2): 219-228 (2012)REDAT: Accent-Invariant Representation for End-To-End ASR by Domain Adversarial Training with Relabeling., , , , , , , , and . ICASSP, page 6408-6412. IEEE, (2021)Unsupervised Model Adaptation using Information-Theoretic Criterion., , , and . HLT-NAACL, page 190-197. The Association for Computational Linguistics, (2010)Accelerator-Aware Training for Transducer-Based Speech Recognition., , , , , , , , and . SLT, page 100-107. IEEE, (2022)Attention-based Contextual Language Model Adaptation for Speech Recognition., , , , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 1994-2003. Association for Computational Linguistics, (2021)Subspace Gaussian Mixture Models for speech recognition., , , , , , , , , and 3 other author(s). ICASSP, page 4330-4333. IEEE, (2010)Neural Machine Translation for Multilingual Grapheme-to-Phoneme Conversion., , and . INTERSPEECH, page 2065-2069. ISCA, (2019)