… to the 2015 Emotion Recognition in the Wild contest, for the sub-challenge of Static Facial
… Recognition in the Wild. The objective of this sub-challenge is to classify the emotions ex…

… deep learning algorithms. In this paper, we propose a novel … emotion recognition method
using multimodal deep learning techniques. In Sect. 2, we will introduce the bimodal deep …

… In the context of emotion recognition on audio features extracted from movie clips, … deep
learning approach for performing emotion recognition just by pretraining a deep MLP as a deep …

… Automatic emotion recognition based on facial expression is … With the remarkable success
of deep learning, the different … automatic facial emotion recognition FER via deep learning. We …

… This paper presents a review of emotional recognition of multimodal signals using deep
learning and … Accuracy varies according to the number of emotions observed, features extracted, …

… In this paper, we investigate the application of end-to-end deep learning to Speech Emotion
Recognition (SER) and critically explore how each of these architectures can be employed …

… deep learning. In this paper, we focus on applying deep architectures for multimodal emotion
recognition … We apply extensions of known DBN models for multimodal emotion recognition …

… proposes an emotion recognition system using a deep learning approach from emotional Big
… The outputs of the two CNNs are fused using two consecutive extreme learning machines (…

… Nowadays, we are at the dawn of Deep Learning (DL) because … segments, only one file’s
emotion class out of 33 testing files … % accuracy on speech emotion recognition task on testing …

… emotion recognition. This work explores the widely used basic deep learning
architectures used in literature. Index Terms—Deep Learning, speech emotion, recognition/identification …