Enhancing Visual Speech Recognition for Deaf Individuals: A Hybrid LSTM and CNN 3D Model for Improved Accuracy
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
https://link.springer.com/content/pdf/10.1007/s13369-023-08385-5.pdf
Reference33 articles.
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2. YH Goh; KX Lau and YK Lee; (2019 ), Audio-visual speech recognition system using recurrent neural network. In: 4th International Conference on Information Technology (InCIT), 38–43, https://doi.org/10.1109/INCIT.2019.8912049.
3. Tadayon; Manie Pottie; Greg (2020) Comparative analysis of the hidden markov model and LSTM: a simulative approachhttps://arxiv.org/abs/2008.03825. https://doi.org/10.48550/arXiv.2008.03825.
4. Shillingford; Brendan; Yannis Assael; Matthew W. Hoffman; Thomas Paine; Cían Hughes; Utsav Prabhu; Hank Liao et al.(2018) ,Large-scale visual speech recognition. arXiv preprint arXiv:1807.05162.https://doi.org/10.48550/arXiv.1807.05162
5. W Feng; N Guan; Y Li, X Zhang; Z Luo,(2017), Audio visual speech recognition with multimodal recurrent neural networks. In: 2017 International Joint Conference on Neural Networks (IJCNN), 681–688, https://doi.org/10.1109/IJCNN.2017.7965918.
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