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A Comparison of Transformer and LSTM Encoder Decoder Models for ASR.

, , , , и . ASRU, стр. 8-15. IEEE, (2019)

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RWTH ASR Systems for LibriSpeech: Hybrid vs Attention - w/o Data Augmentation., , , , , , , и . CoRR, (2019)Training of reduced-rank linear transformations for multi-layer polynomial acoustic features for speech recognition., , , , и . Speech Commun., (2019)A study of latent monotonic attention variants., , и . CoRR, (2021)End-To-End Training of a Neural HMM with Label and Transition Probabilities., , , , и . ASRU, стр. 1-8. IEEE, (2023)End-to-End Speech Recognition: A Survey., , , , и . IEEE ACM Trans. Audio Speech Lang. Process., (2024)Efficient Utilization of Large Pre-Trained Models for Low Resource ASR., , , , и . ICASSP Workshops, стр. 1-5. IEEE, (2023)Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR., , и . INTERSPEECH, стр. 1601-1605. ISCA, (2019)An Analysis of Local Monotonic Attention Variants., , , и . INTERSPEECH, стр. 1398-1402. ISCA, (2019)The Impact of ASR on the Automatic Analysis of Linguistic Complexity and Sophistication in Spontaneous L2 Speech., , , и . Interspeech, стр. 4453-4457. ISCA, (2021)Frame-Level MMI as A Sequence Discriminative Training Criterion for LVCSR., , и . ICASSP, стр. 6904-6908. IEEE, (2020)