The purpose of this paper is twofold:(i) to investigate the emotion representation models and
find out the possibility of a model with minimum number of continuous dimensions and (ii) to …

This survey aims at providing a state-of-the-art overview of feature selection and fusion
strategies, which select and combine multi-view features effectively to accomplish …

Lipreading is the task of decoding text from the movement of a speaker's mouth. Traditional
approaches separated the problem into two stages: designing or learning visual features …

Deep networks have been successfully applied to unsupervised feature learning for single
modalities (eg, text, images or audio). In this work, we propose a novel application of deep …

Multimodal data fusion (MMDF) is the process of combining disparate data streams (of
different dimensionality, resolution, type, etc.) to generate information in a form that is more …

This survey aims at providing multimedia researchers with a state-of-the-art overview of
fusion strategies, which are used for combining multiple modalities in order to accomplish …

This work presents a scalable solution to open-vocabulary visual speech recognition. To
achieve this, we constructed the largest existing visual speech recognition dataset …

In this paper, we present methods in deep multimodal learning for fusing speech and visual
modalities for Audio-Visual Automatic Speech Recognition (AV-ASR). First, we study an …

Lipreading is the task of decoding text from the movement of a speaker's mouth. Traditional
approaches separated the problem into two stages: designing or learning visual features …

Nowadays, human emotion recognition is a mandatory task for many human machine
interaction fields. This paper proposes a novel multi-modal human emotion recognition …