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Phoneme-Based Contextualization for Cross-Lingual Speech Recognition in End-to-End Models.

, , , , and . INTERSPEECH, page 2155-2159. ISCA, (2019)

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On the Choice of Modeling Unit for Sequence-to-Sequence Speech Recognition., , , , , and . INTERSPEECH, page 3800-3804. ISCA, (2019)Sequence-to-sequence Neural Network Model with 2D Attention for Learning Japanese Pitch Accents., , and . INTERSPEECH, page 1284-1287. ISCA, (2018)Phoneme-Based Contextualization for Cross-Lingual Speech Recognition in End-to-End Models., , , , and . INTERSPEECH, page 2155-2159. ISCA, (2019)Algorithmic Exploration of American English Dialects., , , and . ICASSP, page 7374-7378. IEEE, (2020)Neural-FST Class Language Model for End-to-End Speech Recognition., , , , , , , , , and . ICASSP, page 6107-6111. IEEE, (2022)Sharing Low Rank Conformer Weights for Tiny Always-On Ambient Speech Recognition Models., , , , , , , and . ICASSP, page 1-5. IEEE, (2023)Phoebe: Pronunciation-aware Contextualization for End-to-end Speech Recognition., , , and . ICASSP, page 6171-6175. IEEE, (2019)NN-Grams: Unifying Neural Network and n-Gram Language Models for Speech Recognition., , , and . INTERSPEECH, page 3499-3503. ISCA, (2016)Anti-Aliasing Regularization in Stacking Layers., , , and . INTERSPEECH, page 314-318. ISCA, (2020)Efficient Cascaded Streaming ASR System Via Frame Rate Reduction., , , , , , , , and . ASRU, page 1-8. IEEE, (2023)