• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.713-721
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• 2013

This paper describes an efficiency of chroma based tonal features for speech emotion recognition. As the tonality caused by major or minor keys affects to the perception of musical mood, so the speech tonality affects the perception of the emotional states of spoken utterances. In order to justify this assertion with respect to tonality and emotion, subjective hearing tests are carried out by using synthesized signals generated from chroma features, and consequently show that the tonality contributes especially to the perception of the negative emotion such as anger and sad. In automatic emotion recognition tests, the modified chroma-based tonal features are shown to produce noticeable improvement of accuracy when they are supplemented to the conventional log-frequency power coefficient (LFPC)-based spectral features.

• Journal of the Korean Society of Food Culture
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• v.34 no.4
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• pp.432-439
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• 2019

The purpose of this study is to measure the effect of customers' waiting time on their revisit intention through their emotion. Also this study assessed the effect of restaurant selection attributes on consumers' revisit intention in Korea. This study used experimental scenario questionnaires for collecting data. Frequency analysis, Cronbach's alpha, correlation, t-tests and multiple regression analysis were assessed using SPSS. Customers preferred taste, sanitation and service when selecting a restaurant to dine out. The results of this study found that there were no significant differences between positive and negative emotions due to waiting time. Findings of this study suggested that waiting time, convenience, nutritional value, and emotion influenced consumers' revisit intention. Therefore, reducing waiting time and providing proper service will help consumers have positive emotions to return to dine at a restaurant.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4E
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• pp.144-151
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• 2005

We evaluate the performance of emotion recognition via speech signals when a plain speaker talks to an entertainment robot. For each frame of a speech utterance, we extract the frame-based features: pitch, energy, formant, band energies, mel frequency cepstral coefficients (MFCCs), and velocity/acceleration of pitch and MFCCs. For discriminative classifiers, a fixed-length utterance-based feature vector is computed from the statistics of the frame-based features. Using a speaker-independent database, we evaluate the performance of two promising classifiers: support vector machine (SVM) and hidden Markov model (HMM). For angry/bored/happy/neutral/sad emotion classification, the SVM and HMM classifiers yield $42.3\%\;and\;40.8\%$ accuracy, respectively. We show that the accuracy is significant compared to the performance by foreign human listeners.

• Journal of Families and Better Life
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• v.30 no.5
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• pp.135-147
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• 2012

The purposes of this study were to uncover the relationships and correlations between mental health, resilience and happiness. The sample consisted of 184 intermarried Korean men. The data were analyzed by means of frequency, Pearson's correlation, and multiple regression analysis using SPSS. The major findings were as follows; Mental health was negatively correlated with resilience and happiness, except for the component of negative emotion. Additionally, resilience was positively correlated with feelings of happiness and positive emotion. Second, social maladaptation and depression had a negative influence on resilience and a negative influence on happiness. Resilience had a mediating effect on mental health and feelings of happiness. Resilience had a mediating effect on mental health and positive emotion, while resilience had a mediating effect on mental health and negative emotion. In conclusion, in order to improve happiness it is important to mediate on intermarried Korean men's resilience through special education programs and counseling.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.177-184
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• 2022

The purpose of this study is to provide implications by conducting research on brand benefits for skiwear brand customers. For this purpose, a structural equation model was established and empirical research was conducted by selecting brand convenience as a hygiene variable and brand emotion, brand satisfaction, and repurchase intention as endogenous variables. In order to analyze the general characteristics of the subjects, frequency analysis was conducted using SPSS 25 and Cronbach's alpha analysis was conducted using the same statistical program. Confirmatory factor analysis and path analysis were conducted using AMOS 21. In addition, the benefits of skiwear brand, which is an independent variable, were composed of two sub-dimensions, and psychological benefits rather than functional benefits were found to have a stronger impact on brand emotion, suggesting practical implications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3925-3932
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• 2013

Emotion is closely related to the life of human, so has effect on many parts such as concentration, learning ability, etc. and makes to have different behavior patterns. The purpose of this paper is to extract important features based on physiological signals to recognize negative emotion. In this paper, after acquisition of electrocardiography(ECG), electroencephalography(EEG), skin temperature(SKT) and galvanic skin response(GSR) measurements based on physiological signals, we designed an accurate and fast algorithm using combination of linear discriminant analysis(LDA) and genetic algorithm(GA), then we selected important features. As a result, the accuracy of the algorithm is up to 96.4% and selected features are Mean, root mean square successive difference(RMSSD), NN intervals differing more than 50ms(NN50) of heart rate variability(HRV), ${\sigma}$ and ${\alpha}$ frequency power of EEG from frontal region, ${\alpha}$, ${\beta}$, and ${\gamma}$ frequency power of EEG from central region, and mean and standard deviation of SKT. Therefore, the features play an important role to recognize negative emotion.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.11-18
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• 2023

Recently, in the field of Speech Emotion Recognition (SER), many studies have been conducted to improve accuracy using voice features and modeling. In addition to modeling studies to improve the accuracy of existing voice emotion recognition, various studies using voice features are being conducted. This paper, voice files are separated by time interval in a time series method, focusing on the fact that voice emotions are related to time flow. After voice file separation, we propose a model for classifying emotions of speech data by extracting speech features Mel, Chroma, zero-crossing rate (ZCR), root mean square (RMS), and mel-frequency cepstrum coefficients (MFCC) and applying them to a recurrent neural network model used for sequential data processing. As proposed method, voice features were extracted from all files using 'librosa' library and applied to neural network models. The experimental method compared and analyzed the performance of models of recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU) using the Interactive emotional dyadic motion capture Interactive Emotional Dyadic Motion Capture (IEMOCAP) english dataset.

• The Journal of the Korea Contents Association
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• v.12 no.7
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• pp.147-155
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• 2012

This study is to analyze the difference of the post-viewing emotion and behavior of the audience at a dance performance by general characteristics of the audience. To attain the goal of the study described above paragraphs, the audience of dance performance located in Seoul and Kyoungki-Do was set as a collected group. Then, using the convenience sampling method, finally drew out and analyzed 280 people in total. statistic analysis techniques were used SPSS 18.0 program. Based on the statistical methods above, we had the result of data analysis as follows; First, among the general characteristics(job, viewing frequency, dance experience, and genre), had significantly effect on the post-viewing emotion(positive emotion, satisfaction) Second, among the general characteristics(job, viewing frequency, dance experience, and genre), all the factors had significantly effect on post-viewing behaviors(researching, respectating intention).

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.73-82
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• 2018

Attempts have been made to recognize social emotion, including competition-cooperation, while designing interaction in work places. This study aimed to determine the cardiac response associated with classifying competition-cooperation of social emotion. Sixty students from Sangmyung University participated in the study and were asked to play a pattern game to experience the social emotion associated with competition and cooperation. Electrocardiograms were measured during the task and were analyzed to obtain time domain indicators, such as RRI, SDNN, and pNN50, and frequency domain indicators, such as VLF, LF, HF, VLF/HF, LF/HF, lnVLF, lnLF, lnHF, and lnVLF/lnHF. The significance of classifying social emotions was assessed using an independent t-test. The rule-base for the classification was determined using significant parameters of 30 participants and verified from data obtained from another 30 participants. As a result, 91.67% participants were correctly classified. This study proposes a new method of classifying social emotions of competition and cooperation and provides objective data for designing social interaction.

• Science of Emotion and Sensibility
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• v.18 no.3
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• pp.63-70
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• 2015

This study identified heart response of participants while listening to sounds which have 1/f fluctuations with exponent ${\alpha}$ gradient. The participants were engaged in emotional stress work. Prior studies related to 1/f fluctuation sound have reported that sound source can alleviate psychological and physiological state of users. Subjects of this study were exposed to sound with three levels of ${\alpha}$ gradient. Heart response of subjects were measured with Photoplethysmography(PPG) sensor simultaneously. The dependent variables of this study were beat per minute(BPM), very low frequency percent of pulse rate variability (VLF percent), the standard deviation of all normal RR intervals (SDNN), and high frequency power(HF power). Subject showed arousal response when exposed to sound with exponent ${\alpha}$ gradient of 3 whereas the sound with exponent ${\alpha}$ gradient of 1 and 2 resulted in relax effect. The characteristic of 1/f fluctuation sounds can be applied to alleviate stress for employers under emotional labor.