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Multimodal Fusion with Deep Neural Networks for Audio-Video Emotion Recognition
This paper presents a novel deep neural network (DNN) for multimodal fusion of audio, video and text modalities for emotion recognition.
Bag-of-Audio-Words based on Autoencoder Codebook for Continuous Emotion Prediction
The conventional BoW model is based on a dictionary (codebook) built from elementary representations which are selected randomly or by using a clustering algorithm on a training dataset.
Speaker Sincerity Detection based on Covariance Feature Vectors and Ensemble Methods
Automatic measuring of speaker sincerity degree is a novel research problem in computational paralinguistics.
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