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Phoebe: Pronunciation-aware Contextualization for End-to-end Speech Recognition.

, , , and . ICASSP, page 6171-6175. IEEE, (2019)

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Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition., , and . CoRR, (2017)Recognizing Long-Form Speech Using Streaming End-to-End Models., , , , , and . ASRU, page 920-927. IEEE, (2019)Minimum Word Error Rate Training for Attention-Based Sequence-to-Sequence Models., , , , , , and . ICASSP, page 4839-4843. IEEE, (2018)How to Estimate Model Transferability of Pre-Trained Speech Models?, , , , , , , , and . CoRR, (2023)Less Is More: Improved RNN-T Decoding Using Limited Label Context and Path Merging., , , , , , and . CoRR, (2020)Dual Learning for Large Vocabulary On-Device ASR., , , , , and . CoRR, (2023)A Neural Acoustic Echo Canceller Optimized Using An Automatic Speech Recognizer and Large Scale Synthetic Data., , , , and . ICASSP, page 7128-7132. IEEE, (2021)Learning Word-Level Confidence for Subword End-To-End ASR., , , , , , , , , and 2 other author(s). ICASSP, page 6393-6397. IEEE, (2021)Investigations into the Crandem Approach to Word Recognition., , , , and . HLT-NAACL, page 725-728. The Association for Computational Linguistics, (2010)Sharing Low Rank Conformer Weights for Tiny Always-On Ambient Speech Recognition Models., , , , , , , and . ICASSP, page 1-5. IEEE, (2023)