Emotion recognition from EEG could be used in many applications as it allows us to know the “inner” emotion regardless of the human facial expression, behaviour, or verbal communication. In this paper, we proposed and described a novel fractal dimension (FD) based emotion recognition algorithm using an Arousal-Valence emotion model. FD values calculated from the EEG signal recorded from the cor...

In this paper, a Mandarin speech based emotion classification method is presented. Five primary human emotions including anger, boredom, happiness, neutral and sadness are investigated. In emotion classification of speech signals, conventional features are statistics of fundamental frequency, loudness, duration and voice quality. However, the recognition accuracy of systems employing these feat...

Emotion recognition is important for social interaction and communication, yet previous research has identified a cross-cultural emotion recognition deficit: Recognition is less accurate for emotions expressed by individuals from a cultural group different than one's own. The current study examined whether social categorization based on race, in the absence of cultural differences, influences e...

Emotion recognition is a very active field of research. The Emotion Recognition In The Wild Challenge and Workshop (EmotiW) 2013 Grand Challenge consists of an audio-video based emotion classification challenges, which mimics realworld conditions. Traditionally, emotion recognition has been performed on laboratory controlled data. While undoubtedly worthwhile at the time, such lab controlled da...

Emotion recognition ability has been identified as a central component of emotional competence. We describe the development of an instrument that objectively measures this ability on the basis of actor portrayals of dynamic expressions of 10 emotions (2 variants each for 5 emotion families), operationalized as recognition accuracy in 4 presentation modes combining the visual and auditory sense ...

Emotion recognition is a very active field of research. The Emotion Recognition In The Wild Challenge and Workshop (EmotiW) 2013 Grand Challenge consists of an audiovideo based emotion classification challenges, which mimics real-world conditions. Traditionally, emotion recognition has been performed on laboratory controlled data. While undoubtedly worthwhile at the time, such laboratory contro...

Emotion has an important role in naturalness of man-machine communication and computerized emotion recognition from speech is investigated by many researchers in the recent decades. In this paper, the effect of formant-related features on improving the performance of emotion detection systems is experimented. To do this, various forms and combinations of the first three formants are concatenate...

Emotion expression is one of essential issues in human-machine interface. Besides, EEG had been widely used in many applications. With EEG based emotion recognition is also very important in affective computing. In this study, we developed an EEG based emotion recognition. Independent component analysis is applied to remove the noise generated from EOG and ECK. Then, the Fractal dimension is us...

Textual information is an important communication medium contained rich expression of emotion, and emotion recognition on text has wide applications. Word emotion analysis is fundamental in the problem of textual emotion recognition. Through an analysis of the characteristics of word emotion expression, we use word emotion vector to describe the combined basic emotions in a word, which can be u...