Lip Reading for Low-resource Languages by Learning and Combining General Speech Knowledge and Language-specific Knowledge
Author:
Affiliation:
1. KAIST,School of Electrical Engineering,South Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377080.pdf?arnumber=10377080
Reference86 articles.
1. Spatio-Temporal Fusion Based Convolutional Sequence Learning for Lip Reading
2. Learning audio-visual speech representation by masked multimodal cluster prediction;Shi,2022
3. Lrs3-ted: a large-scale dataset for visual speech recognition;Afouras,2018
4. Lip Reading in the Wild
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1. TensorLip: Unveiling Conversations with Deep Learning by Harnessing TensorFlow for Lip Reading Intelligence;International Journal of Advanced Research in Science, Communication and Technology;2024-06-29
2. Towards Practical and Efficient Image-to-Speech Captioning with Vision-Language Pre-Training and Multi-Modal Tokens;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
3. Visual Speech Recognition for Languages with Limited Labeled Data Using Automatic Labels from Whisper;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
4. Generalizing sentence-level lipreading to unseen speakers: a two-stream end-to-end approach;Multimedia Systems;2024-01-25
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