Overview of the Advancements in Automatic Emotion Recognition: Comparative Performance of Commercial Algorithms
Previous works show that mood congruence effect or trait congruence effect can be achieved (Chepenik et al., 2007; Rusting, 1998). The present study explores the effect of emotional state and dispositional joy on effectiveness of emotion recognition from facial expression. The experimental study was conducted in two groups of subjects. The general sample consisted of 39 participants. Participants’ emotional state was measured with the self-report questionnaire PANAS. The participants’ current mood was manipulated with the emotion induction procedure, which involved screening video with “joyful” or “neutral” emotional coloring. To measure the speed of emotional information processing a computer technique was used, in which a participant performed the task on emotion recognition from facial expression. The hypothesis was tested whether there is an effect of congruency in positive information processing. It was supposed that positive emotional state and dispositional joy heighten the speed of positive information processing and don’t influence processing of the stimuli with negative emotional coloring. Testing of the emotion induction procedure proved it to be partially successful. Congruency effect for dispositional joy was achieved: we found an interrelation of higher manifestation of this trait with higher speed in joy recognition from facial expressions. The influence of positive emotional state was manifested in lower speed in recognition of joy. In sum, the results show that the congruency effect is expressed differently for trait and emotional state. Overall, the results of the conducted study provide information on the mechanisms of emotion recognition.
The paper focuses on the way one’s own emotional state influences the recognition of other people’s emotions. Existing research indicates the effect of congruence between the emotions experienced at the moment and the evaluations of emotional stimuli. Our experimental study tested the hypotheses of the influence of emotional states on two aspects of emotion recognition, accuracy and sensitivity. We hypothesized that emotional state of the observer reduces the accuracy and increases the sensitivity. The study involved 69 participants divided into three groups. The baseline emotional state was assessed using a self-report measure. We used video clips with neutral, positive, and negative emotional content to induce different emotional states in each group. The accuracy and sensitivity of emotion recognition were measured using a test based on video samples of people's behavior in different situations. The results showed that the emotional state in the control group was rather «tense» and different from neutral. However, our hypotheses were not supported: the groups with different induced emotional states did not exhibit any significant differences in the accuracy of emotion recognition. The control group demonstrated higher sensitivity. These preliminary results are discussed in the context of the issues of emotion recognition research (such as emotion induction, assessment of emotions, differentiation of emotional states and traits).
In this paper we consider the automatic emotions recognition problem, especially the case of digital audio signal processing. We consider and verify an approach in which the classification of a sound fragment is reduced to the problem of image recognition. The waveform and spectrogram are used as a visual representation of the image. The computational experiment was done based on Radvess open dataset including 8 different emotions: "neutral", "calm", "happy," "sad," "angry," "scared", "disgust", "surprised". The best accuracy result was 64%, which was produced by a combination of “|spectrogram + convolution neural network VGG-11”
In this paper we consider the automatic emotions recognition problem, especially the case of digital audio signal processing. We consider and verify an straight forward approach in which the classification of a sound fragment is reduced to the problem of image recognition. The waveform and spectrogram are used as a visual representation of the image. The computational experiment was done based on Radvess open dataset including 8 different emotions: “neutral”, “calm”, “happy,” “sad,” “angry,” “scared”, “disgust”, “surprised”. Our best accuracy result 71% was produced by combination “melspectrogram + convolution neural network VGG-16”.
The distractive effects on attentional task performance in different paradigms are analyzed in this paper. I demonstrate how distractors may negatively affect (interference effect), positively (redundancy effect) or neutrally (null effect). Distractor effects described in literature are classified in accordance with their hypothetical source. The general rule of the theory is also introduced. It contains the formal prediction of the particular distractor effect, based on entropy and redundancy measures from the mathematical theory of communication (Shannon, 1948). Single- vs dual-process frameworks are considered for hypothetical mechanisms which underpin the distractor effects. Distractor profiles (DPs) are also introduced for the formalization and simple visualization of experimental data concerning the distractor effects. Typical shapes of DPs and their interpretations are discussed with examples from three frequently cited experiments. Finally, the paper introduces hierarchical hypothesis that states the level-fashion modulating interrelations between distractor effects of different classes.
This article describes the expierence of studying factors influencing the social well-being of educational migrants as mesured by means of a psychological well-being scale (A. Perrudet-Badoux, G.A. Mendelsohn, J.Chiche, 1988) previously adapted for Russian by M.V. Sokolova. A statistical analysis of the scale's reliability is performed. Trends in dynamics of subjective well-being are indentified on the basis the correlations analysis between the condbtbions of adaptation and its success rate, and potential mechanisms for developing subjective well-being among student migrants living in student hostels are described. Particular attention is paid to commuting as a factor of adaptation.