Audio-visual speech recognition using deep learning

Author:

Noda Kuniaki,Yamaguchi Yuki,Nakadai Kazuhiro,Okuno Hiroshi G.,Ogata Tetsuya

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Reference52 articles.

1. Abdel-Hamid O, Jiang H. (2013) Rapid and effective speaker adaptation of convolutional neural network based models for speech recognition. In: Proceedings of the 14th Annual Conference of the International Speech Communication Association. Lyon, France

2. Abdel-Hamid O, rahman Mohamed A, Jiang H, Penn G (2012) Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition. In: Proceedings of the IEEE International Conference on Acoustics, Speech,and Signal Processing, Kyoto, pp 4277–4280

3. Aleksic PS, Katsaggelos AK (2004) Comparison of low- and high-level visual features for audio-visual continuous automatic speech recognition. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, vol 5, Montreal, pp 917–920

4. Barker J, Berthommier F (1999) Evidence of correlation between acoustic and visual features of speech. In: Proceedings of the 14th International Congress of Phonetic Sciences, San Francisco , pp 5–9

5. Bengio Y (2009) Learning deep architectures for AI. Found Trends Mach Learn 2(1):1–127

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