Class Confusability Reduction in Audio-Visual Speech Recognition Using Random Forests-Reference-Cited by-同舟云学术

Class Confusability Reduction in Audio-Visual Speech Recognition Using Random Forests

Published:2018 Issue: Volume: Page:584-592
ISSN:0302-9743
Container-title:Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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Author:

Sad Gonzalo D.,Terissi Lucas D.,Gómez Juan C.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-319-75193-1_70

Reference10 articles.

1. Advanced Multimedia Processing Laboratory. Carnegie Mellon University, Pittsburgh, PA. http://chenlab.ece.cornell.edu/projects/AudioVisualSpeechProcessing/

2. Borgström, B., Alwan, A.: A low-complexity parabolic lip contour model with speaker normalization for high-level feature extraction in noise-robust audiovisual speech recognition. IEEE Trans. Syst. Man Cybern. 38(6), 1273–1280 (2008)

3. Digital Signal Processing Group, Rice University: NOISEX-92 Database, Houston, Rice

4. Katsaggelos, A.K., Bahaadini, S., Molina, R.: Audiovisual fusion: challenges and new approaches. Proc. IEEE 103(9), 1635–1653 (2015)

5. Krishnamurthy, N., Hansen, J.: Babble noise: modeling, analysis, and applications. IEEE Trans. Audio Speech Lang. Process. 17(7), 1394–1407 (2009)

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