… based sub-challenge of the Emotion Recognition in the Wild (EmotiW) … architectures to address
emotion recognition task, our … -scale features explicitly capturing emotion variation can be …

… This paper presents a new approach of robust emotion recognition in speech signals in … is
proposed for robust emotion recognition in noisy speech. The effectiveness and robustness of …

… Emotion Speech Corpus) and Berlin emotional speech database Emo-DB are used in this
study for evaluating the emotion recognition … emotion recognition systems should be robust …

Context-aware emotion recognition (CAER) has recently boosted the practical applications
of affective computing techniques in unconstrained environments. Mainstream CAER …

… for robust emotion recognition. Specifically, shape decomposition is first performed on the
detected facial images by defining a weight vector. Then, a feature point constraint algorithm is …

… We develop a novel framework to achieve robust emotion recognition from low bit rate video.
While video frames are downsampled at the encoder side, the decoder is embedded with a …

… recognition (ASR) systems. We are interested instead in the usefulness of these algorithms
in the field of speech emotion recognition (… algorithm to accurately identify emotion in speech. …

… emotion recognition on two different datasets. Impact Statement—Multi-modal emotion
recognition … a framework for robust emotion recognition, where the dataset for recognition network …

… develop a robust emotion recognition system. Emotions are expressed in different ways by
the speakers. Business outsourcing call centres would find speech recognition on emotional …

… As the aim of this work is to evaluate the robustness of features for emotion recognition, we
… Classifiers based on MLP were widely used in emotion recognition (El Ayadi et al. 2011; …