… also used for emotional speech [3], [12], [26]. Acoustic feature sets used in emotion recognition
models mainly contain prosodic (pitch, energy, rhythm), timbre and voice quality features. …

… to the video based sub-challenge of the Emotion Recognition in the Wild (EmotiW) 2016 …
shallow neural network architectures to address emotion recognition task, our HoloNet has …

… 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 …

… 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 …

… we focus on the emotional state and the emotional group in order … we propose a new feature
for emotion recognition called the … the proposed feature with other existing features, such as …

… of discovering generic EEG features with a robust capability to distinguish emotions. … -robust
feature selection (LRFS) method for promoting EEG-based emotion recognition systems with …

… 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; …

… feature points for the traditional scale-invariant feature transform (SIFT) method, an improved
SIFT algorithm is proposed for robust emotion recognition. … Then, a feature point constraint …

… techniques to provide robust features for audio-visual emotion recognition. Emotion recognition
accuracy relies heavily on the ability to generate representative features. However, this …

… 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 …