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Fusion for Audio-Visual Laughter Detection — University of ...

    https://research.utwente.nl/en/publications/fusion-for-audio-visual-laughter-detection#:~:text=Audio-visual%20laughter%20detection%20is%20performed%20by%20combining%20%28fusing%29,use%20the%20commonly%20used%20PLP%20and%20RASTA-PLP%20features.
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Decision-Level Fusion for Audio-Visual Laughter Detection ...

    https://link.springer.com/chapter/10.1007/978-3-540-85853-9_13
    Audio-visual laughter detection is performed by fusing the results of separate audio and video classifiers on the decision level. This results in laughter detection with a significantly higher AUC-ROC than single-modality classification. Keywords Speech Recognition Gaussian Mixture Model Emotion Recognition Equal Error Rate Multimodal Interface

Decision-Level Fusion for Audio-Visual Laughter Detection

    https://ibug.doc.ic.ac.uk/media/uploads/documents/reuderink-etal-mlmi08.pdf
    Decision-Level Fusion for Audio-Visual Laughter Detection 139 Table 1. Audio-visualfusion. Thelast column containstheperformance usingdifferent modalities and fusion techniques; A indicates audio, V indicates video, FF indicates feature-level fusion, and DF indicates decision-level fusion. The performance is mea-

Decision-level fusion for audio-visual laughter detection ...

    https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.9746
    Audio-visual laughter detection is performed by combining (fusing) the results of a separate audio and video classifier on the decision level. The video-classifier uses features based on the principal components of 20 tracked facial points, for audio we use the …

(PDF) Decision-level fusion for audio-visual laughter ...

    https://www.academia.edu/2782810/Decision_level_fusion_for_audio_visual_laughter_detection
    Laugh- ter sound detection was performed on MFCC and delta-MFCC features, using two GMMs, one for laughter, and one for other sounds. A recall of 96% and a precision of 60% was obtained using 16 Gaussian mixtures. Decision-level fusion was performed with manually designed rules, resulting in a recall of 71% and a precision of 74%.

Decision-Level Fusion for Audio-Visual Laughter Detection

    https://www.researchgate.net/publication/221040350_Decision-Level_Fusion_for_Audio-Visual_Laughter_Detection
    Audio-visual laughter detection is performed by fusing the results of separate audio and video classifiers on the decision level. This results in laughter detection with a …

Decision-level fusion for audio-visual laughter detection ...

    https://repository.tno.nl/islandora/object/uuid:2b013ae3-5d25-476d-91a7-f27d40e0db7a
    Audio-visual laughter detection is performed by fusing the results of separate audio and video classifiers on the decision level. This results in laughter detection with a significantly higher AUC-ROC than single-modality classification. © 2008 Springer-Verlag Berlin Heidelberg. Subject. Flow interactions Learning systems Robot learning Technical presentations Audio visuals Automatic …

CiteSeerX — Fusion for audio-visual laughter detection

    https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.371.2113
    Audiovisual laughter detection is performed by fusing the results of separate audio and video classifiers on the decision level. This results in laughter detection with a significantly higher AUC-ROC 1 than single-modality classification. 1

Fusion for Audio-Visual Laughter Detection — University of ...

    https://research.utwente.nl/en/publications/fusion-for-audio-visual-laughter-detection
    Audio-visual laughter detection is performed by combining (fusing) the results of a separate audio and video classifier on the decision level. The video-classifier uses features based on the principal components of 20 tracked facial points, for audio we use the commonly used PLP and RASTA-PLP features.

Fusion for Audio-Visual Laughter Detection - ResearchGate

    https://www.researchgate.net/publication/250064716_Fusion_for_Audio-Visual_Laughter_Detection
    Audio-visual laughter detection is performed by fusing the results of separate audio and video classifiers on the decision level. This results in laughter detection with a …

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