Play with Closing Markers: Cadential Multivalence in 1960s Prechoruses and Related Schemas

2019 ◽  
Vol 42 (1) ◽  
pp. 1-23
Author(s):  
David Heetderks
Keyword(s):  
Emotional States ◽  
Wide Range ◽  
Structural Closure

Abstract In 1960s pop/rock, the end of a prechorus often uses text, breakaway from harmonic loops, hypermeter, or a change of melody to heighten expectation for tonic harmony and create structural closure. Songs harness this heightened expectation to underscore the importance of the chorus and illustrate the singer’s lyrics. These closing markers provide a wide range of expressive and formal options by creating various cadential effects, including a closed cadence overlapping with the chorus, an open cadence before the chorus, or—in passages often depicting marked emotional states—conflicting formal cues.

scholarly journals Understanding of Emotional States in Persons with Pedophilia / Pedophilic Disorder

2018 ◽  
Vol 7 (3) ◽  
pp. 84-99
Author(s):  
L.Y. Demidova ◽  
N.V. Dvoryanchikov
Keyword(s):  
Emotional Regulation ◽  
Mental States ◽  
Control Group ◽  
Emotional States ◽  
Sexual Crimes ◽  
Sexual Drive ◽  
Emotional Perception ◽  
Wide Range ◽  
Icd 10 ◽  
High Level

This article highlights the problem of emotional perception in pedophilia (ICD-10) / pedophilia disorder (ICD-11). In present paper, emotional perception is considered as abilities of recognizing and identifying a wide range of mental states like emotions, affects, moods, feelings. The assumption about relations of alexithymia and disturbances in the recognition of emotions, perspective taking, empathy with pedophilia and regulatory mechanisms of activity verified empirically. Two groups of persons accused of sexual crimes are compared: 44 people with pedophilia, 32 people without the disorder; also 95 persons who haven't been accused were examined for the control group; as well intra-group comparison of pedophilic persons with egosyntonic and egodystonic attitude toward sexual drive was made. Contradictions of earlier studies are resolved in the result: it is shown that in pedophilia the ability of understanding emotional states remains normal at first sight (in comparison with the deficits found in the accused without pedophilia). However, the group with pedophilia is characterized by extremely high level of alexithymia and based on this the consistently conclusion is made about disturbances of emotional regulation in egosyntonic form of this disorder.

Comparative analysis of empathic abilities of foreign and Kazakhstani students of Karaganda Medical University

2020 ◽  
Vol 44 (3) ◽  
pp. 79-84
Author(s):  
D. Sharma ◽  
◽  
M. Ospanova ◽  
Keyword(s):  
Foreign Students ◽  
The Other ◽  
Personal Relationships ◽  
Emotional States ◽  
Emotional Responsiveness ◽  
Wide Range ◽  
Complete Identification ◽  
Increase Productivity ◽  
Medical University ◽  
Different Cultures

The article deals with the problems of empathic abilities of foreign students and Kazakh students of Karaganda Medical University. Special attention is paid to the characteristics of empathy in different cultures, the definitions of which cover a wide range of emotional States, including caring for others and the desire to help them; to experience emotions that correspond to the emotions of another person; to distinguish what the other person thinks or feels. Empathy is needed to increase productivity, to develop competence in communication, to create deeper and personal relationships. Empathy can also be understood as a person’s emotional responsiveness to the experiences of another person, a response to the feelings of another, as well as empathy – a person’s experience of the same emotional States that the other is experiencing, on the basis of complete identification.

Comparison of Several Acoustic Modeling Techniques for Speech Emotion Recognition

2016 ◽  
Vol 7 (1) ◽  
pp. 58-68 ◽  
Author(s):  
Imen Trabelsi ◽  
Med Salim Bouhlel
Keyword(s):  
Emotion Recognition ◽  
Linear Prediction ◽  
Recognition Rate ◽  
Gaussian Mixture ◽  
Speech Emotion Recognition ◽  
Support Vector ◽  
Emotional States ◽  
Wide Range ◽  
Leibler Divergence ◽  
Perceptual Linear Prediction

Automatic Speech Emotion Recognition (SER) is a current research topic in the field of Human Computer Interaction (HCI) with a wide range of applications. The purpose of speech emotion recognition system is to automatically classify speaker's utterances into different emotional states such as disgust, boredom, sadness, neutral, and happiness. The speech samples in this paper are from the Berlin emotional database. Mel Frequency cepstrum coefficients (MFCC), Linear prediction coefficients (LPC), linear prediction cepstrum coefficients (LPCC), Perceptual Linear Prediction (PLP) and Relative Spectral Perceptual Linear Prediction (Rasta-PLP) features are used to characterize the emotional utterances using a combination between Gaussian mixture models (GMM) and Support Vector Machines (SVM) based on the Kullback-Leibler Divergence Kernel. In this study, the effect of feature type and its dimension are comparatively investigated. The best results are obtained with 12-coefficient MFCC. Utilizing the proposed features a recognition rate of 84% has been achieved which is close to the performance of humans on this database.

EVALUATION OF FEATURE EXTRACTION AND CLASSIFICATION TECHNIQUES FOR EEG-BASED SUBJECT IDENTIFICATION

2016 ◽  
Vol 78 (9-3) ◽  
Author(s):  
Dini Handayani ◽  
Abdul Wahab ◽  
Hamwira Yaacob
Keyword(s):  
Feature Extraction ◽  
Affective Computing ◽  
User Profiling ◽  
Support Vector ◽  
Emotional States ◽  
Mel Frequency Cepstral Coefficients ◽  
Classification Techniques ◽  
Power Spectral ◽  
Wide Range ◽  
Subject Identification

The ability to identify a subject is indispensable in affective computing research due to its wide range of applications. User profiling was created based on the strength of emotional patterns of the subject, which can be used for subject identification. Such system is made based on the emotional states of happiness and sadness, indicated by the electroencephalogram (EEG) data. In this paper, we examine several techniques used for subject profiling or identification purposed. Those techniques include feature extraction and classification techniques. In the experimental study, we compare three techniques for feature extraction namely, Power Spectral Density (PSD), Kernel Density Estimation (KDE), and Mel Frequency Cepstral Coefficients (MFCC). As for classification we compare three classification techniques, they are; Multilayer Perceptron (MLP), Naive Bayesian (NB), and Support Vector Machine (SVM). The best result achieved was 59.66%, using the MFCC and MLP-based techniques using 5-fold cross validation. The experiment results indicated that these profiles could be more accurate in identifying subject compared to NB and SVM. The comparisons demonstrated that profile-based methods for subject identification provide a viable and simple alternative to this problem.

scholarly journals Lexicаl-Semantic and Syntactic Valency of Language Representations of the Emotional World in the Poem “Then, fare thee well” by T. Mооre

Discourse ◽  
2021 ◽  
Vol 7 (6) ◽  
pp. 120-131
Author(s):  
A. V. Diehl
Keyword(s):  
Literary Criticism ◽  
Positive Emotions ◽  
Cognitive Linguistics ◽  
Relevant Information ◽  
Individual Characteristics ◽  
Emotional States ◽  
Continuous Sampling ◽  
Wide Range ◽  
The Individual ◽  
Emotional Concepts

Introduction. The article is devoted to the study of the specificity of the lexical-semantic and syntactic valency of lexical units nominating emotions in the poem “Then, fare thee well” by T. Moore. The relevance of this study lies in the fact that it has been carried out in line with the linguo-cognitive paradigm and aims to identify the specifics of the compatibility of emotions nominations with other lexical units verbalizing the fragment of the concept “the emotional world”. The novelty of the research is associated with its anthropocentric orientation and interdisciplinary nature of the interpretation of the material, which implies the study of the artistic concept sphere “the emotional world” on the material of the poem “Then, fare thee well” by T. Moore from the standpoint of cognitive linguistics, psychology and literary criticism.Methodology and sources. The theoretical basis of this research is presented by the works of scientists V.Yu. Apresjan, E.V. Galeeva, N.A. Krasavskii, I.N. Kucher, S.G. Lyubova, K.O. Pogosova, E.A. Rozhnova, who considered the essence of emotional concepts as culturally conditioned mental constructs, i.e. directly related to the worldview of representatives of a particular ethnic group.In the article we use the following research methods: the method of definitional analysis, the functional-semantic method, the method of component analysis, the descriptive method, as well as methods of continuous sampling and quantitative data processing.Results and discussion. In the present study, the classification of lexical units verbalizing the manifestations of emotional states in the poem “Then, fare thee well” by T. Moore has been made. In the semantic structure of the lexemes under consideration, we highlight and categorize the semes marked by the correlation with the emotional sphere of people. The linguo-cognitive analysis of the lexic and syntactic valency of the primary and secondary nominations of emotions, carried out in the work, revealed the specifics of the conceptualization of emotional states and experiences in the individual author's picture of the world.Conclusion. It has been established that the artistic conceptual sphere “emotional world” in the poem “Then, fare thee well” by T. Moore consists of two closely interrelated concepts – “negative emotions” and “positive emotions”, verbalized by lexemes nominating a wide range of emotional experiences of the lyrical character. It is concluded that the associative-figurative characteristics attributed to a specific emotion in the artistic world of the author carry valuable culturally relevant information about the individual characteristics of the interpretation of emotional concepts both by the poet himself and by the “naïve” thinking of an English-speaking person as a representative of his language and culture.

scholarly journals Emotion Detection for Social Robots Based on NLP Transformers and an Emotion Ontology

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1322
Author(s):  
Wilfredo Graterol ◽  
Jose Diaz-Amado ◽  
Yudith Cardinale ◽  
Irvin Dongo ◽  
Edmundo Lopes-Silva ◽  
...  
Keyword(s):  
Language Processing ◽  
Application Programming Interface ◽  
Social Robots ◽  
Classification Model ◽  
Machine Learning Techniques ◽  
Emotional States ◽  
Emotion Detection ◽  
Learning Techniques ◽  
Wide Range ◽  
Application Programming

For social robots, knowledge regarding human emotional states is an essential part of adapting their behavior or associating emotions to other entities. Robots gather the information from which emotion detection is processed via different media, such as text, speech, images, or videos. The multimedia content is then properly processed to recognize emotions/sentiments, for example, by analyzing faces and postures in images/videos based on machine learning techniques or by converting speech into text to perform emotion detection with natural language processing (NLP) techniques. Keeping this information in semantic repositories offers a wide range of possibilities for implementing smart applications. We propose a framework to allow social robots to detect emotions and to store this information in a semantic repository, based on EMONTO (an EMotion ONTOlogy), and in the first figure or table caption. Please define if appropriate. an ontology to represent emotions. As a proof-of-concept, we develop a first version of this framework focused on emotion detection in text, which can be obtained directly as text or by converting speech to text. We tested the implementation with a case study of tour-guide robots for museums that rely on a speech-to-text converter based on the Google Application Programming Interface (API) and a Python library, a neural network to label the emotions in texts based on NLP transformers, and EMONTO integrated with an ontology for museums; thus, it is possible to register the emotions that artworks produce in visitors. We evaluate the classification model, obtaining equivalent results compared with a state-of-the-art transformer-based model and with a clear roadmap for improvement.

EVALUATION OF SIGNAL PROCESSING TECHNIQUES IN DISCRIMINATING ECG SIGNALS OF MEN AND WOMEN DURING REST CONDITION AND EMOTIONAL STATES

2018 ◽  
Vol 30 (04) ◽  
pp. 1850028 ◽  
Author(s):  
Ateke Goshvarpour ◽  
Atefeh Goshvarpour ◽  
Ataollah Abbasi
Keyword(s):  
Gender Differences ◽  
Signal Processing ◽  
Emotional States ◽  
Men And Women ◽  
Wide Range ◽  
Significant Difference ◽  
Rest Condition ◽  
Processing Techniques ◽  
The Impact ◽  
Signal Processing Techniques

Great range of electrocardiogram (ECG) signal processing methods can be found in the literature. In addition, the importance of gender differences in physiological activities was also identified in various conditions. This article aims to provide a comprehensive evaluation of linear and nonlinear ECG parameters to indicate suitable signal processing approaches which can show significant differences between men and women. These differences were investigated in two conditions: (i) during rest condition, and (ii) during the affective image inducements. A wide range of parameters from time-, frequency-, wavelet-, and nonlinear-techniques were examined. Applying the Wilcoxon rank sum test, significant differences between two genders were inspected. The analysis was performed on 47 college students at rest condition and while subjects watching four types of affective pictures, including sadness, happiness, fear, and peacefulness. The impact of these emotions on the results was also investigated. The results indicated that 72.95% and 72.61% of all features were significantly different between male and female in rest condition and affective inducements, respectively. In addition, the highest percentage of the significant difference between ECG parameters of men and women was achieved using nonlinear characteristics. Considering all features together, the highest significant difference between two genders was achieved for negative emotions, including sadness and fear. In conclusion, the results of this study emphasized the importance of gender role in cardiac responses during rest condition and different emotional states. Since these gender differences are well manifested by nonlinear signal processing techniques, dynamical gender-specific ECG system may improve the automatic emotion recognition accuracies.

From an animal's point of view: Motivation, fitness, and animal welfare

1990 ◽  
Vol 13 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Marian Stamp Dawkins
Keyword(s):  
Animal Welfare ◽  
Point Of View ◽  
Emotional States ◽  
Inelastic Demand ◽  
Wide Range ◽  
Objective Basis

AbstractTo study animal welfare empirically we need an objective basis for deciding when an animal is suffering. Suffering includes a wide range ofunpleasant emotional states such as fear, boredom, pain, and hunger. Suffering has evolved as a mechanism for avoiding sources ofdanger and threats to fitness. Captive animals often suffer in situations in which they are prevented from doing something that they are highly motivated to do. The “price” an animal is prepared to pay to attain or to escape a situation is an index ofhow the animal “feels” about that situation. Withholding conditions or commodities for which an animal shows “inelastic demand” (i.e., for which it continues to work despite increasing costs) is very likely to cause suffering. In designing environments for animals in zoos, farms, and laboratories, priority should be given to features for which animals show inelastic demand. The care ofanimals can thereby be based on an objective, animal-centered assessment of their needs.

scholarly journals An integrative and functional framework for the study of animal emotion and mood

2010 ◽  
Vol 277 (1696) ◽  
pp. 2895-2904 ◽  
Author(s):  
Michael Mendl ◽  
Oliver H. P. Burman ◽  
Elizabeth S. Paul
Keyword(s):  
Conscious Experience ◽  
Emotional States ◽  
Discrete Emotions ◽  
Physiological Indicators ◽  
Affective Characteristics ◽  
Discrete Emotion ◽  
Functional Perspective ◽  
Wide Range ◽  
Animal Welfare Science

A better understanding of animal emotion is an important goal in disciplines ranging from neuroscience to animal welfare science. The conscious experience of emotion cannot be assessed directly, but neural, behavioural and physiological indicators of emotion can be measured. Researchers have used these measures to characterize how animals respond to situations assumed to induce discrete emotional states (e.g. fear). While advancing our understanding of specific emotions, this discrete emotion approach lacks an overarching framework that can incorporate and integrate the wide range of possible emotional states. Dimensional approaches that conceptualize emotions in terms of universal core affective characteristics (e.g. valence (positivity versus negativity) and arousal) can provide such a framework. Here, we bring together discrete and dimensional approaches to: (i) offer a structure for integrating different discrete emotions that provides a functional perspective on the adaptive value of emotional states, (ii) suggest how long-term mood states arise from short-term discrete emotions, how they also influence these discrete emotions through a bi-directional relationship and how they may function to guide decision-making, and (iii) generate novel hypothesis-driven measures of animal emotion and mood.

scholarly journals Automatic Assessment of Loneliness in Older Adults Using Speech Analysis on Responses to Daily Life Questions

2021 ◽  
Vol 12 ◽  
Author(s):  
Yasunori Yamada ◽  
Kaoru Shinkawa ◽  
Miyuki Nemoto ◽  
Tetsuaki Arai
Keyword(s):  
Older Adults ◽  
Early Detection ◽  
Daily Life ◽  
Binary Classification ◽  
Emotional States ◽  
Automatic Assessment ◽  
Adverse Health Effects ◽  
Wide Range ◽  
Speech Data ◽  
Speech Features

Loneliness is a perceived state of social and emotional isolation that has been associated with a wide range of adverse health effects in older adults. Automatically assessing loneliness by passively monitoring daily behaviors could potentially contribute to early detection and intervention for mitigating loneliness. Speech data has been successfully used for inferring changes in emotional states and mental health conditions, but its association with loneliness in older adults remains unexplored. In this study, we developed a tablet-based application and collected speech responses of 57 older adults to daily life questions regarding, for example, one's feelings and future travel plans. From audio data of these speech responses, we automatically extracted speech features characterizing acoustic, prosodic, and linguistic aspects, and investigated their associations with self-rated scores of the UCLA Loneliness Scale. Consequently, we found that with increasing loneliness scores, speech responses tended to have less inflections, longer pauses, reduced second formant frequencies, reduced variances of the speech spectrum, more filler words, and fewer positive words. The cross-validation results showed that regression and binary-classification models using speech features could estimate loneliness scores with an R2 of 0.57 and detect individuals with high loneliness scores with 95.6% accuracy, respectively. Our study provides the first empirical results suggesting the possibility of using speech data that can be collected in everyday life for the automatic assessments of loneliness in older adults, which could help develop monitoring technologies for early detection and intervention for mitigating loneliness.

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