Emotional Space Research Articles

On the use of AI for Generation of Functional Music to Improve Mental Health.

Increasingly music has been shown to have both physical and mental health benefits including improvements in cardiovascular health, a link to reduction of cases of dementia in elderly populations, and improvements in markers of general mental well-being such as stress reduction. Here, we describe short case studies addressing general mental well-being (anxiety, stress-reduction) through AI-driven music generation. Engaging in active listening and music-making activities (especially for at risk age groups) can be particularly beneficial, and the practice of music therapy has been shown to be helpful in a range of use cases across a wide age range. However, access to music-making can be prohibitive in terms of access to expertize, materials, and cost. Furthermore the use of existing music for functional outcomes (such as targeted improvement in physical and mental health markers suggested above) can be hindered by issues of repetition and subsequent over-familiarity with existing material. In this paper, we describe machine learning approaches which create functional music informed by biophysiological measurement across two case studies, with target emotional states at opposing ends of a Cartesian affective space (a dimensional emotion space with points ranging from descriptors from relaxation, to fear). Galvanic skin response is used as a marker of psychological arousal and as an estimate of emotional state to be used as a control signal in the training of the machine learning algorithm. This algorithm creates a non-linear time series of musical features for sound synthesis “on-the-fly”, using a perceptually informed musical feature similarity model. We find an interaction between familiarity and perceived emotional response. We also report on subsequent psychometric evaluation of the generated material, and consider how these - and similar techniques - might be useful for a range of functional music generation tasks, for example, in nonlinear sound-tracking such as that found in interactive media or video games.

A-Situ: a computational framework for affective labeling from psychological behaviors in real-life situations

This paper presents a computational framework for providing affective labels to real-life situations, called A-Situ. We first define an affective situation, as a specific arrangement of affective entities relevant to emotion elicitation in a situation. Then, the affective situation is represented as a set of labels in the valence-arousal emotion space. Based on psychological behaviors in response to a situation, the proposed framework quantifies the expected emotion evoked by the interaction with a stimulus event. The accumulated result in a spatiotemporal situation is represented as a polynomial curve called the affective curve, which bridges the semantic gap between cognitive and affective perception in real-world situations. We show the efficacy of the curve for reliable emotion labeling in real-world experiments, respectively concerning (1) a comparison between the results from our system and existing explicit assessments for measuring emotion, (2) physiological distinctiveness in emotional states, and (3) physiological characteristics correlated to continuous labels. The efficiency of affective curves to discriminate emotional states is evaluated through subject-dependent classification performance using bicoherence features to represent discrete affective states in the valence-arousal space. Furthermore, electroencephalography-based statistical analysis revealed the physiological correlates of the affective curves.

Affective border violence: Mapping everyday asylum precarities across different spaces and temporalities

This paper stems from my long-term involvement in asylum activist communities in London and Berlin and is an analysis of the emotional work of borders. It describes asylum seekers’ daily journeys through endless spaces of discomfort and depletion, which I conceptualise as affective border violence. Stories about different public and private spaces such as the post office, gay clubbing and Berlin's asylum camp spaces will illustrate how affective technologies are mobilised to manage asylum seekers' bodies, time and space. The aims of this paper are threefold: 1) to illustrate how affective border violence works through occupying emotional and mental space by creating an overwhelming amount of emotional borderwork, 2) to illustrate how states mobilise power and violence in and through specific temporal modalities such as fearful anticipation, continuity and the everyday, and 3) how people seeking asylum negotiate affective border violence through re-claiming bodily and temporal space. The empirical elements of this paper include personal reflections, participatory work within and outside of asylum activist groups in London and Berlin, in-depth conversations and friendships with people registered as asylum seekers.

Four-classes Human Emotion Recognition Via Entropy Characteristic and Random Forest。


 Human Emotion Recognition is of vital importance to realize human-computer interaction (HCI), while multichannel electroencephalogram (EEG) signals gradually replace other physiological signals and become the main basis of emotional recognition research with the development of brain-computer interface (BCI). However, the accuracy of emotional classification based on EEG signals under video stimulation is not stable, which may be related to the characteristics of EEG signals before receiving stimulation. In this study, we extract the change of Differential Entropy (DE) before and after stimulation based on wavelet packet transform (WPT) to identify individual emotional state. Using the EEG emotion database DEAP, we divide the experimental EEG data in the database equally into 15 sets and extract their differential entropy on the basis of WPT. Then we calculate value of DE change of each separated EEG signal set. Finally, we divide the emotion into four categories in the two-dimensional valence-arousal emotional space by combining it with the integrated algorithm, Random Forest (RF). The simulation results show that the WPT-RF model established by this method greatly improves the recognition rate of EEG signal, with an average classification accuracy of 87.3%. In addition, we use WPT-RF model to train individual subjects, and the classification accuracy reached 97.7%.

The Power of Experiential Learning in Emotional Courtroom Spaces

Courtrooms are dynamic and emotionally imbued spaces. In these environments, case processing challenges, shortcomings, successes, and power struggles impact court actors, defendants, and victims. We asked: What happens when you immerse a group of students with limited interest in court systems into this environment to witness, take notes, and reflect on their experiences? Can this experiential learning opportunity spark interest and enhance understanding of criminal court processes? A qualitative analysis of 42 journals reveals that students had strong emotional responses to what they saw; through journaling, students described not only their own reactions but also a myriad of emotions they perceived in court actors and participants. Further, many students personally related to processes observed, especially when they were attentive to the backgrounds of defendants, victims, and their families. Whether positive or negative, our data demonstrate that these experiences lead students to critically analyze system processes on a more macro level.

Artificial Intelligence as a Cultural Problem

We are currently experiencing a revolution associated with the rapid development and widespread introduction of artificial intelligence (AI) systems. This process provides great opportunities and is associated with great risks. It has become an important factor in geoeconomics and geopolitics, an arena for superpower rivalry.Human being exists in rational, emotional and intuitive spaces. The last three centuries have been associated with the development of rational space. We know little about the emotional space and know almost nothing about the intuitive one. These areas of cognition of the world are associated with art, artistic and social creativity, with philosophy. In the 21st century, the role of these areas will grow. There is a transition now happening from the industrial phase of the civilization development to the post-industrial one, from the world of machines to the world of people. Therefore, attempts to reduce human activity to the rational solving of problems, to replace human in many areas with artificial intelligence, will be a step backward, into the past, and not forward, into the future.The response to the challenge associated with the AI development, with the rapid spread of computer technologies, should be given, first of all, in the cultural space, in the area of meanings and values. It is necessary to rethink the essence and limitations of people, the nature of the tools that they can create, and those that should be abandoned. This is about redefining the capabilities of human beings and their place in the world, as well as about fundamental changes in the organization of society. The article shows that the strategy of “irresponsible gods” and entrusting AI with the “last issues” can bring us to a global catastrophe. However, conscious using of the opening opportunities can help humanity reach a new, higher level. And the choice between these alternatives is now being made in the cultural space.

Safe Spaces for Enabling the Creative Process in Classrooms

Based on interviews with five creative professionals this article looks to investigate the creative experience as a source of data on how educators might create space for enabling the creative process in the classroom. Looking toward professional artists who are also committed educators provides core commentary on how to maximise creative experiences in the classroom. Whilst acknowledging the importance of physical space, the following article looks purposefully toward how to enable space as an internal state of being, with the intent toward establishing transdisciplinary discussions that stimulate and provoke creative pedagogical research across an interdependent continuum. The research concludes that enabling space for the creative process lies in the educators’ ability to create safe physical, social and emotional spaces for exploring creative processes. Implications for initial teacher education, professional development and classroom practice are identified.

Investigation of multilingual and mixed-lingual emotion recognition using enhanced cues with data augmentation

In the past decade, research for improving man–machine communication has focused on emotion recognition using audio cues. Several effective monolingual, multilingual, and cross-corpus speech emotion recognition (SER) systems have been developed; however, they are limited to recognizing emotions from databases of monolingual discourse, primarily in either categorical or dimensional emotion space. For multilingual countries and federations such as India, Russia, and the European Union, these limitations can be problematic. Furthermore, in an environment of mixed diversified languages, the performance of existing models is unclear. To address these issues, we propose an innovative mixed-lingual SER system that considers five diverse languages, including dialect variability. Mixed-lingual corpora are developed from available standard speech emotion databases. Furthermore, a compact feature set having a unique set of speech feature functionals with a distinctive set of enhanced perceptual features and modified H-coefficients is proposed. Against existing large feature sets, the proposed compact feature set is robust and effective to perform the dual task of significantly recognizing different emotions from multilingual SER systems also, along with the mixed-lingual SER systems in both emotion spaces of categorical and dimensional. In the proposed SER system, to overcome the skewness of SER system performance for recognizing certain emotions, a data augmentation method is then incorporated. Furthermore, the proposed SER system is designed to efficiently recognize even the extreme emotions of boredom, disgust, sadness, and surprise in both emotion spaces. The proposed SER system is compared to existing SER systems, and the comparison results demonstrate that the proposed system outperformed existing systems.

Exploring the Spatial Distribution Characteristics of Emotions of Weibo Users in Wuhan Waterfront Based on Gender Differences Using Social Media Texts

The benefits of the natural environment in urban space have been explored in numerous studies. However, only a few statistics and studies have been conducted on the correlation between emotion and urban waterfront space, especially considering gender differences. Taking Wuhan city as an example, this study puts forward a new approach and perspective. Text emotion analysis is combined with the spatial analysis technique based on big data of social media. Based on the emotions of the public of different genders in urban space, suggestions are provided for urban planning and development from the perspective of POI (Point of Interest). The main steps are: (1) Analyzing the emotional score of Weibo texts published by citizens in the waterfront area of 21 lakes in Wuhan City; (2) exploring the public emotion characteristics of different genders in the urban waterfront; (3) classifying the waterfront according to the emotional response (score) of the public of different genders; (4) exploring the relationship between different POI types and waterfront types and proposing planning suggestions. The results of this study provide evidence for gender differences and spatial distribution of public emotions in the Wuhan waterfront area. It can help decision-makers to judge the prior protection and development direction of waterfront space, thus demonstrating the feasibility of this approach.

Manajemen Gerakan Sekolah Menyenangkan dalam Penguatan Pendidikan Karakter (PPK) di SD Negeri Buayan Kebumen

Gerakan Sekolah Menyenangkan (GSM) i.e Enjoyable School Movement, actively participates in the creation of an adaptive educational culture with changing times. This research aims to analyze GSM management in Penguatan Pendidikan Karakter (PPK) i.e Character Building Affirmation in Buayan 1 Kebumen Elementary School. This is descriptive-qualitative research. The data were collected through interviews, observations, and documentation. The results show that GSM management in Buayan 1 Kebumen Elementary School uses the following functions: 1) Planning with carefully in elaborating GSM principles by school resources; 2) Organizing, with the formation of work divisions explained in detail according to authority and duties; 3) Implementation through the establishment of a 'learning environment' which provides physical and emotional development space for students; 4) Supervision by analyzing strengths, weaknesses, supporting and inhibiting factors for future program improvement references. GSM has become the right program to be developed as a solution to the imbalance in the quality of education so far through grassroots transformation.

A Method of Describing Uncertain Emotions of Facial Expressions

In order to describe uncertain and fuzzy emotions in recognizing facial expressions, a PAD regressive model based on deep convolutional neural network model is built to quantize the emotions, by which the facial expressions can be mapped to the emotional space of PAD. Then the emotional membership function is proposed to describe the uncertainty and fuzziness of the emotions in the space of PAD. Finally the testing results demonstrate that the regressive model performs well in recognizing facial expressions and the results from describing the emotions quantitatively agree with the human cognition to facial expressions.

Emo2Vec

Sentiment analysis or opinion mining for subject information extraction from the text has become more and more dependent on natural language processing, especially for business and healthcare, since the online products and service reviews affect the consuming behaviors. Word embeddings that can map the words to low-dimensional vector representations have been widely used in natural language processing tasks. But the word embeddings based on context such as Word2Vec and GloVe fail to capture the sentiment information. Most of existing sentiment analysis methods incorporate emotional polarity (positive and negative) to improve the sentiment embeddings for the emotion classification. This article takes advantage of an emotional psychology model to learn the emotional embeddings in Chinese first. In order to combine the semantic space and an emotional space, we present two different purifying models from local (LPM) and global (GPM) perspectives based on Plutchik's wheel of emotions to add the emotional information into word vectors. The two models aim to improve the word vectors so that not only the semantically similar words but also the sentimentally similar words can be closer than before. The Plutchik's wheel of emotions model can give eight-dimensional vector for one word in emotional space that can capture more sentiment information than the binary polarity labels. The obvious advantage of the local purifying model is that it can be fit for any pretrained word embeddings. For the global purifying model, we can get the final emotional embeddings at once. These models have been extended to handle English texts. The experimental results on Chinese and English datasets show that our purifying model can improve the conventional word embeddings and some proposed sentiment embeddings for sentiment classification and multi-emotion classification.

The Neural Representation of Visually Evoked Emotion Is High-Dimensional, Categorical, and Distributed across Transmodal Brain Regions.

SummaryCentral to our subjective lives is the experience of different emotions. Recent behavioral work mapping emotional responses to 2,185 videos found that people experience upward of 27 distinct emotions occupying a high-dimensional space, and that emotion categories, more so than affective dimensions (e.g., valence), organize self-reports of subjective experience. Here, we sought to identify the neural substrates of this high-dimensional space of emotional experience using fMRI responses to all 2,185 videos. Our analyses demonstrated that (1) dozens of video-evoked emotions were accurately predicted from fMRI patterns in multiple brain regions with different regional configurations for individual emotions; (2) emotion categories better predicted cortical and subcortical responses than affective dimensions, outperforming visual and semantic covariates in transmodal regions; and (3) emotion-related fMRI responses had a cluster-like organization efficiently characterized by distinct categories. These results support an emerging theory of the high-dimensional emotion space, illuminating its neural foundations distributed across transmodal regions.

A Provisional Taxonomy of Subjectively Experienced Positive Emotions.

Over the past two decades, scholars have conducted studies on the subjective experience of over 30 positive emotional states (see Weidman, Steckler, & Tracy, 2017). Yet, evidence from research on the non-verbal expression and biological correlates of positive emotions suggests that people likely experience far fewer than 30 distinct positive emotions. The present research provided an initial, lexically driven examination of how many, and which, positive emotions cohere as distinct subjective experiences, at both the state and trait levels. Four studies (including two pre-registered replications) using factor and network analyses of 5939 participants' emotional experiences, elicited through the relived emotions task, found consistent evidence for nine distinct positive emotion states and five distinct traits. At both levels, many frequently studied positive emotions were found to overlap considerably or entirely with other ostensibly distinct states in terms of the subjective components used to describe them, suggesting that researchers currently study more positive emotions than individuals experience distinctively. These findings provide the first-ever comprehensive portrait of the taxonomic structure of subjectively experienced positive emotions, with the ultimate aim of inspiring further examination of the positive emotion space at the subjective experiential as well as more biological and behavioral levels of analysis.

Emotional response evoked when looking at and trying a new food product, measured through images and words. A case-study with novel fruit and vegetable smoothies

Little research has been published on emotional responses evoked by completely new, innovative food products. The objectives of the present study were 1) to assess the emotional response to new products (fruit and vegetable smoothies in a drink pouch) in two different scenarios: looking at the smoothie pouch, or tasting the smoothie with the smoothie pouch alongside; 2) to compare the information obtained when the participants use photographs or use words to express emotions. In the Pack-alone scenario, similar emotional spaces and sample configurations were obtained with both images and words. In the Pack-and-tasting scenario, the richness of the emotional response increased when using images. In both scenarios, the participants used a greater number of negative emotions when these were presented as images rather than as words. This could be considered an advantage, as it enables some negative emotional loads to be portrayed. The present results also demonstrate that evaluating the emotional response allows effective discrimination between samples with similar overall liking scores.

BILINGUALISM AND INTERFERENCE AS TENDENCIES OF LINGUISTIC DEVELOPMENT OF MODERN EDUCATIONAL SPACE IN CONDITIONS OF EDUCATIONAL INTERNATIONALIZATION

The article is devoted to the study of bilingualism and interference problems in the development of modern society. The paper elaborates a theoretical background for the analysis of those two phenomena. As a result, the research has found that in the process of intercultural/interlingual communication there is an inevitable clash of two languages, the result of which is a new cognitive emotional language cultural space, which is a manifestation of interference. The paper has also proposed solutions to the problem of interfered speech. It has been given the available programs for foreign languages improvement as well as recommendations for future studying of these very problems.

AUTOBIOGRAPHY AND SPACE: SLAVE NARRATIVES OF HARRIET JACOBS AND MARY PRINCE

The women writers in the 19th century represented themselves in the form of writings and presented their ideas through the medium of autobiography, a genre in the literary world. Genre, as per Collins dictionary, is ‘a particular type of literature, painting, music, film or other art form which people consider as a class because it has special characteristics’. Autobiography is a tool to represent the ‘Self’ and during the 19th century, the women used it as one of her weapons to challenge the patriarchal and dominant upper class, wherein they were categorised in the marginalized section in terms of their origin and in creative writing field. Their writings became an agency or rather a space- emotional space within the cultural and societal space, where they put forth their emotions, desire to become emancipated, create a bench mark alongside other male writers in the literary world and inspire other women. This research paper attempts to explore autobiography in a new light through spatial theory as proposed by Henri Lefebvre and Edward Soja, vis-à-vis place and will posit the narratives which portrays the injustice done upon the marginalized people during the 19th century. Space will act as a conceptual tool to narrate the slave narratives Incidents in the Life of a Slave Girl written by herself (1861) and The History of Mary Prince, a West Indian Slave. Related by Herself (1831) of Harriet Jacobs, an Afro-American slave in America and Mary Prince, a West Indian Slave in England respectively.

Perceived emotional expressions of composite faces.

The eye and mouth regions serve as the primary sources of facial information regarding an individual’s emotional state. The aim of this study was to provide a comprehensive assessment of the relative importance of those two information sources in the identification of different emotions. The stimuli were composite facial images, in which different expressions (Neutral, Anger, Disgust, Fear, Happiness, Contempt, and Surprise) were presented in the eyes and the mouth. Participants (21 women, 11 men, mean age 25 years) rated the expressions of 7 congruent and 42 incongruent composite faces by clicking on a point within the valence-arousal emotion space. Eye movements were also monitored. With most incongruent composite images, the perceived emotion corresponded to the expression of either the eye region or the mouth region or an average of those. The happy expression was different. Happy eyes often shifted the perceived emotion towards a slightly negative point in the valence-arousal space, not towards the location associated with a congruent happy expression. The eye-tracking data revealed significant effects of congruency, expressions and interaction on total dwell time. Our data indicate that whether a face that combines features from two emotional expressions leads to a percept based on only one of the expressions (categorical perception) or integration of the two expressions (dimensional perception), or something altogether different, strongly depends upon the expressions involved.

Constructing and measuring domain-specific emotions for affective design: a descriptive approach to deal with individual differences

Assessing design solutions via domain-specific emotions has been widely concerned and explored in the field of affective design. However, the examination and accommodation of individual differences have not been settled sufficiently in the literature. To address this research gap, this paper proposes a descriptive approach to draw calibrated collective emotion patterns in survey-based affective design assessment. A ‘Repertory Grid Interview linked with Rate-All-That-Apply’ (RGI/RATA) procedure is firstly conducted to elicit and code the individual’s personal emotional descriptions into mid-level Emotion Words (EWs) and to gather emotion data grids with each grid quantified by an individual’s own EWs. The obtained individualised emotion data grids are then subjected to Multiple Factor Analysis (MFA) to extract collective emotional space, thus to enable conceptualising collective emotional dimensions and measuring calibrated collective responses. A case study demonstrating the implementation process for a simple project of appearance design assessment is also presented. Practitioner Summary: The proposed methodology may help a design team to investigate the shared patterns of domain-specific emotions through a single assessment survey. With the provided post hoc analysis tools, designers may also evaluate multi-level individual differences (e.g. regarding user groups or even intra-individual) quantitatively and at a low cost. Abbreviations: EWs: emotion words; HF/E: human factors and ergonomics; IEA: International Ergonomics Association; MFA: multiple factor analysis; PCT: personal construct theory; PCA: principal component analysis; RGI/RATA: repertory grid interview linked with rate-all-that-apply; RGI: repertory grid interview; RATA: rate-all-that-apply; SD: standard deviation; USB: universal serial bus

A city as an emotional space: theoretical-sociological analysis

The focus of this article is focused on the study of peculiarities of the contemporary aestheticization of urban space as a product of emotional capitalism. Noted that the concepts "society experiences" and "experience economy" fixed vector of cultural changes of modern society, and suggest new theoretical trajectory of sociological research. Control for the "experience" in this case can be considered a new form of public influence in which not last role is played by the mass media, which is a kind of mediator for the active promotion of a variety of emotions, first and foremost sensual pleasure. Pointed out that the aestheticization of the contemporary urban space is connected with the logic of the functioning of emotional capitalism. The modern city is forced to form their own "alphabet of feelings", which prescribes rules for their feelings in different situations. Entertainment in the city acquires the features of a universal model, it is a particular code value in U. Eco, that is, a symbolic system that can reveal the contents of the message depending on the purpose and conditions of the functioning of the spectacle. Life in a modern city full of wealth of their own unrest, and the aestheticization of urban space is associated with replication "markets experiences" that focus on the commercialization of human feelings. The emotional richness of urban design has become a part of an overall program of total consumption. The theatricality, iconization and glamor can be considered as the main strategy "emotionalization" of urban space that aims at the reproduction of the effects of the "experience economy". Stressed that the idea glamorizes urban space can be traced in the concepts of the theoreticians of the "creative city", appealing to psychologically and design analysis of the urban environment, and the militarization of urban space through the creation of militaristic icons that form the therapeutically-emotional space. Respectively iconic images serve as points of reference, the individual ascribes to them a special importance as images that represent something significant for social life.