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Dynamic visual features for audio-visual speaker ...
https://eprints.qut.edu.au/38143/#:~:text=The%20cascading%20appearance-based%20%28CAB%29%20feature%20extraction%20technique%20has,this%20technique%20for%20the%20related%20speaker%20verification%20application.
Dynamic visual features for audio–visual speaker ...
https://www.researchgate.net/publication/222577960_Dynamic_visual_features_for_audio-visual_speaker_verification
Request PDF | Dynamic visual features for audio–visual speaker verification | The cascading appearance-based (CAB) feature extraction technique has established itself as the state-of-the-art in ...
Dynamic visual features for audio-visual speaker ...
https://eprints.qut.edu.au/38143/
Audio-Visual Speaker Identification Based on the Use of ...
https://link.springer.com/chapter/10.1007/3-540-44887-X_86
From our experimental results, it has been shown that the addition of the dynamical visual information improves the speaker identification accuracies for both clean and noisy audio conditions compared to the audio only case. The best audio, visual and audio-visual identification accuracies achieved were 86.91%, 57.14% and 94.05% respectively.
Audio-visual speaker verification using continuous fused HMMs
http://users.cecs.anu.edu.au/~vishci/VisHCI2006/Papers/VisHCI2006_Dean_Sridharan_Wark_Presentation.pdf
Audio-visual speaker verification ... dynamic video features (mean-removed DCT, contour-based or optical flow) and output fusion with a face GMM – This would take advantage of the temporal audio-visual relationship, in addition to static face-recognition. CRICOS No. 000213J 25
Dynamic visual features for audio-visual speaker ...
https://core.ac.uk/reader/10901054
Dynamic visual features for audio-visual speaker ...
Dynamic Bayesian Networks for Audio-Visual Speaker ...
https://link.springer.com/chapter/10.1007/11608288_72
Audio-Visual speaker recognition promises higher performance than any single modal biometric systems. This paper further improves the novel approach based on Dynamic Bayesian Networks (DBNs) to bimodal speaker recognition. In the present paper, we investigate five different topologies of feature-level fusion framework using DBNs.
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