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PyHTK: Python Library and ASR Pipelines for HTK., , , and . ICASSP, page 6470-6474. IEEE, (2019)Confidence Estimation for Attention-Based Sequence-to-Sequence Models for Speech Recognition., , , , , , , and . ICASSP, page 6388-6392. IEEE, (2021)Generative Modeling of Audible Shapes for Object Perception., , , , , , , and . ICCV, page 1260-1269. IEEE Computer Society, (2017)Residual Energy-Based Models for End-to-End Speech Recognition., , , , and . Interspeech, page 4069-4073. ISCA, (2021)Improving Confidence Estimation on Out-of-Domain Data for End-to-End Speech Recognition., , , , , and . ICASSP, page 6537-6541. IEEE, (2022)Knowledge Distillation for Neural Transducers from Large Self-Supervised Pre-Trained Models., , and . ICASSP, page 8527-8531. IEEE, (2022)Multi-Task Learning for End-to-End ASR Word and Utterance Confidence with Deletion Prediction., , , , , and . Interspeech, page 4074-4078. ISCA, (2021)Integrating Source-Channel and Attention-Based Sequence-to-Sequence Models for Speech Recognition., , and . ASRU, page 39-46. IEEE, (2019)Modular Domain Adaptation for Conformer-Based Streaming ASR., , , , and . INTERSPEECH, page 3357-3361. ISCA, (2023)Bi-directional Lattice Recurrent Neural Networks for Confidence Estimation., , , and . ICASSP, page 6755-6759. IEEE, (2019)