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The NAIST ASR system for the 2015 Multi-Genre Broadcast challenge: On combination of deep learning systems using a rank-score function.

, , , , , and . ASRU, page 654-659. IEEE, (2015)

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Recovering Capitalization for Automatic Speech Recognition of Vietnamese using Transformer and Chunk Merging., , , , , and . KSE, page 1-5. IEEE, (2019)The NAIST English speech recognition system for IWSLT 2015., , , , and . IWSLT (Evaluation Campaign), (2015)Toward Expressive Speech Translation: A Unified Sequence-to-Sequence LSTMs Approach for Translating Words and Emphasis., , and . INTERSPEECH, page 2640-2644. ISCA, (2017)End-to-end named entity recognition for Vietnamese speech., , , and . O-COCOSDA 2022, page 1-5. IEEE, (2022)Improving translation of emphasis with pause prediction in speech-to-speech translation systems., , , , and . IWSLT, (2015)Learning a Lexicon and Translation Model from Phoneme Lattices., , , , , and . EMNLP, page 2377-2382. The Association for Computational Linguistics, (2016)The NAIST ASR system for the 2015 Multi-Genre Broadcast challenge: On combination of deep learning systems using a rank-score function., , , , , and . ASRU, page 654-659. IEEE, (2015)AdapITN: A Fast, Reliable, and Dynamic Adaptive Inverse Text Normalization., , , , , and . ICASSP, page 1-5. IEEE, (2023)Sequence-to-Sequence Models for Emphasis Speech Translation., , and . IEEE ACM Trans. Audio Speech Lang. Process., 26 (10): 1873-1883 (2018)A Hybrid System for Continuous Word-Level Emphasis Modeling Based on HMM State Clustering and Adaptive Training., , , , and . INTERSPEECH, page 3196-3200. ISCA, (2016)