A Fully Convolutional Sequence Learning Approach for Cued Speech Recognition from Videos-Reference-Cited by-同舟云学术

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A Fully Convolutional Sequence Learning Approach for Cued Speech Recognition from Videos

Published:2021-01-24 Issue: Volume: Page:
ISSN:
Container-title:2020 28th European Signal Processing Conference (EUSIPCO)
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Author:

Papadimitriou Katerina,Potamianos Gerasimos

Funder

Hellenic Foundation for Research and Innovation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9287308/9287310/09287365.pdf?arnumber=9287365

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Computation and Parameter Efficient Multi-Modal Fusion Transformer for Cued Speech Recognition;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

2. Cuing Without Sharing: A Federated Cued Speech Recognition Framework via Mutual Knowledge Distillation;Proceedings of the 31st ACM International Conference on Multimedia;2023-10-26

3. Cross-Modal Mutual Learning for Cued Speech Recognition;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

4. Multistream Neural Architectures for Cued Speech Recognition Using a Pre-Trained Visual Feature Extractor and Constrained CTC Decoding;ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2022-05-23

5. Cross-Modal Knowledge Distillation Method for Automatic Cued Speech Recognition;Interspeech 2021;2021-08-30

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