• Title/Summary/Keyword: Emotion Classification

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Performance Evaluation of Attention-inattetion Classifiers using Non-linear Recurrence Pattern and Spectrum Analysis (비선형 반복 패턴과 스펙트럼 분석을 이용한 집중-비집중 분류기의 성능 평가)

  • Lee, Jee-Eun;Yoo, Sun-Kook;Lee, Byung-Chae
    • Science of Emotion and Sensibility
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    • v.16 no.3
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    • pp.409-416
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    • 2013
  • Attention is one of important cognitive functions in human affecting on the selectional concentration of relevant events and ignorance of irrelevant events. The discrimination of attentional and inattentional status is the first step to manage human's attentional capability using computer assisted device. In this paper, we newly combine the non-linear recurrence pattern analysis and spectrum analysis to effectively extract features(total number of 13) from the electroencephalographic signal used in the input to classifiers. The performance of diverse types of attention-inattention classifiers, including supporting vector machine, back-propagation algorithm, linear discrimination, gradient decent, and logistic regression classifiers were evaluated. Among them, the support vector machine classifier shows the best performance with the classification accuracy of 81 %. The use of spectral band feature set alone(accuracy of 76 %) shows better performance than that of non-linear recurrence pattern feature set alone(accuracy of 67 %). The support vector machine classifier with hybrid combination of non-linear and spectral analysis can be used in later designing attention-related devices.

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Greeting, Function, and Music: How Users Chat with Voice Assistants

  • Wang, Ji;Zhang, Han;Zhang, Cen;Xiao, Junjun;Lee, Seung Hee
    • Science of Emotion and Sensibility
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    • v.23 no.2
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    • pp.61-74
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    • 2020
  • Voice user interface has become a commercially viable and extensive interaction mechanism with the development of voice assistants. Despite the popularity of voice assistants, the academic community does not utterly understand about what, when, and how users chat with them. Chatting with a voice assistant is crucial as it defines how a user will seek the help of the assistant in the future. This study aims to cover the essence and construct of conversational AI, to develop a classification method to deal with user utterances, and, most importantly, to understand about what, when, and how Chinese users chat with voice assistants. We collected user utterances from the real conventional database of a commercial voice assistant, NetEase Sing in China. We also identified different utterance categories on the basis of previous studies and real usage conditions and annotated the utterances with 17 labels. Furthermore, we found that the three top reasons for the usage of voice assistants in China are the following: (1) greeting, (2) function, and (3) music. Chinese users like to interact with voice assistants at night from 7 PM to 10 PM, and they are polite toward the assistants. The whole percentage of negative feedback utterances is less than 6%, which is considerably low. These findings appear to be useful in voice interaction designs for intelligent hardware.

The 3D Character Modeling for Golf Swing Motion Analysis by Economical Verification of Body Information (인체정보 DB의 경제적인 조합을 통한 골프 스윙 동작 분석용 3D 캐릭터 모델링)

  • 곽현민;채균식;박찬종;이상태
    • Science of Emotion and Sensibility
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    • v.6 no.2
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    • pp.59-64
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    • 2003
  • The national standard anthropometry of Korea is conducted every 5∼6 year term after its first research was started in 1979, The fourth research was conducted in 1997. The result of the national standard anthropometry has been reflected in manufactured goods design of allied industries such as clothing, shoes and furniture. In this paper, we measured anthropometry data for every bodily figurative classification after dividing users according to gender, age and bodily figure using the result of the national standard anthropometry. We constructed 3D character through the process of analyzing interrelation of measured anthropomeoy and measuring representative category. In the process for organization , we measured anthropometry which can effectively express sports action of golf, tennis etc. We made it by presenting measurement which is able to form each type of 3D character after the category was decided. Quantitative and objective valuation for posture and action became possible by developing visible information offer and posture action analysis protocol in theoretical approach for analysis of posture and action in sports.

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3D Character Modeling For Sports Motion Analysis (스포츠 동작 분석용 3D캐릭터 모델링)

  • 곽현민;조해성;박찬종;이상태
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2003.05a
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    • pp.134-140
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    • 2003
  • The national standard physique research of Korea is being conducted every 5∼6 year term after its first research was started 1979, the fourth research was conducted in 1997. The result of the national physique research was reflected in manufactured goods design of allied industries such as clothing , shoes, furniture. In this thesis, we measured anthropometry value for every bodily figurative classification after dividing users according to gender, age, bodily figure using the result of the national standard physique research. We constructed 3D character through the process of analyzing interrelation of measured anthropometry and measuring representative category. For the process for organization, we measured anthropometry which can express sports action of golf, tennis and etc effectively. We made it by presenting measurement which is able to form each type of 3D character after the category was decided. Quantitative and objective valuation for posture and action became possible by developing visible information offer and posture action analysis protocol in theoretical approach for analysis for analysis of posture and action in sports.

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Analysis of the Correlation between Narrative and Emotions Displayed by Movie Characters through a Quantitative Analysis of Dialogues in a Movie (영화 대사의 정량적 분석을 통한 등장인물의 감정과 서사간의 상관성 연구)

  • You, Eun-Soon
    • The Journal of the Korea Contents Association
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    • v.13 no.6
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    • pp.95-107
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    • 2013
  • A linguistic element found in a movie, dialogue, plays a critical role in building up narrative structure. Still, analyses conducted on movies mostly focus on images due to the nature of a movie that conveys a story through its visual images while dialogue has either been underestimated or received less spotlight despite their importance. This study highlights the significance of lines in a movie. This study calls attention to dialogue, which has stayed out of the main focus and been on the periphery thus far when analyzing movies, so as to see how they contribute to constructing a narrative. It then spotlights the significance of dialogue in the movie. To this end, the study sorts out emotional expressions articulated by actors through their dialogues then to make polarity classification into affirmation and negation, followed by a quantitative analysis of how the polarity proportion of emotional expressions changes depending on the narrative structure. The study also suggests a narrative's relevance with emotions by pointing to dynamic emotional changes that shift between affirmation and negation depending on incidents, conflicts and resolution thereof throughout a movie.

Speakers' Intention Analysis Based on Partial Learning of a Shared Layer in a Convolutional Neural Network (Convolutional Neural Network에서 공유 계층의 부분 학습에 기반 한 화자 의도 분석)

  • Kim, Minkyoung;Kim, Harksoo
    • Journal of KIISE
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    • v.44 no.12
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    • pp.1252-1257
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    • 2017
  • In dialogues, speakers' intentions can be represented by sets of an emotion, a speech act, and a predicator. Therefore, dialogue systems should capture and process these implied characteristics of utterances. Many previous studies have considered such determination as independent classification problems, but others have showed them to be associated with each other. In this paper, we propose an integrated model that simultaneously determines emotions, speech acts, and predicators using a convolution neural network. The proposed model consists of a particular abstraction layer, mutually independent informations of these characteristics are abstracted. In the shared abstraction layer, combinations of the independent information is abstracted. During training, errors of emotions, errors of speech acts, and errors of predicators are partially back-propagated through the layers. In the experiments, the proposed integrated model showed better performances (2%p in emotion determination, 11%p in speech act determination, and 3%p in predicator determination) than independent determination models.

Development of Artificial Intelligence Education Content to Classify Emotion of Sentences for Elementary School (초등학생을 위한 문장의 정서 분류 인공지능 교육 콘텐츠 개발 및 적용)

  • Shim, Jaekwoun;Kwon, Daiyoung
    • Journal of The Korean Association of Information Education
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    • v.24 no.3
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    • pp.243-254
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    • 2020
  • In order to cultivate AI(artificial intelligence) manpower, major countries are making efforts to apply AI education from elementary school. In order to introduce AI education in elementary school, it is necessary to have a curriculum and educational content for elementary school level. This study developed educational contents to experience the principle of AI learning at the unplugged level for the purpose of AI education for elementary school students. The educational content developed was selected as an AI that evaluates the emotion of sentences. In addition, to solve the problem, data attributes were derived and collected, and the process of AI learning was simulated to solve the problem. As a result of the study, the attitude of elementary school students to AI increased post than before. In addition, the task performance rate was averaged at 85%, showing that the proposed AI education content has educational significance.

Evaluation of the Odor with Aging (연령증가에 따른 향의 평가)

  • 강인형;민병찬;전광진;김철중
    • Science of Emotion and Sensibility
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    • v.5 no.2
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    • pp.1-9
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    • 2002
  • It is already known that olfactory susceptibility differ with races and sex. Moreover, with aging both detection and identification about olfactory information were impaired. For researches about evaluation of the odor with aging, although the subject used, from infants to elderly, was various, the kinds of odor used were restricted to simple alcohol and acetic acid. Also, the evaluation methods were mainly used olfactory test. From over respects , this research was done as follows. Subjects were 19 to 72 years (n=50) whose sense-of-smell functions are normal. They were taken as stability and closed eye state. The odor stimuli were used 100% natural odor of six kinds of Basil, Lavender, Lemon, Jasmine, Ylangylang oil and Skatole , during 60 seconds using olfactometer. ECG, GSR and subjective evaluation were measured, and examined their relevance. Twenty and 40 ages group evaluated Lemon and 60 ages group did Lavender affirmatively. Correlation was seen among RRI, HR, GSR and subjective evaluation for 40 ages group, and it turns out that it is the group which a mature olfactory function most. These results are fully applied not only to development of the classified cosmetics for the age group but to development of the artificial smell and taste.

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Engagement classification algorithm based on ECG(electrocardiogram) response in competition and cooperation games (심전도 반응 기반 경쟁, 협동 게임 참여자의 몰입 판단 알고리즘 개발)

  • Lee, Jung-Nyun;Whang, Min-Cheol;Park, Sang-In;Hwang, Sung-Teac
    • Journal of Korea Game Society
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    • v.17 no.2
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    • pp.17-26
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    • 2017
  • Excessive use of the internet and smart phones have become a social issue. The level of engagement has both positive and negative effects such as good performance or indulgence phenomenon, respectively. This study was to develop an algorithm to determine the engagement state based on cardiovascular response. The participants were asked to play a pattern matching game and the experimental design was divided into cooperation and competition task to provide the level of engagement. The correlation between heart rate and amplitude was analyzed according to each task. The regression equation and accuracy were verified by polynomial regression analysis. The results showed that heart rate and amplitude were positively correlated when the task was a game, and negatively correlated when there was a reference task. The accuracy of classifying between game and reference task was 89%. The accuracy between tasks was confirmed to be 76.5%. This study is expected to be used to quantitatively evaluate the level of engagement in real time.

Emotion Analysis Using a Bidirectional LSTM for Word Sense Disambiguation (양방향 LSTM을 적용한 단어의미 중의성 해소 감정분석)

  • Ki, Ho-Yeon;Shin, Kyung-shik
    • The Journal of Bigdata
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    • v.5 no.1
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    • pp.197-208
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    • 2020
  • Lexical ambiguity means that a word can be interpreted as two or more meanings, such as homonym and polysemy, and there are many cases of word sense ambiguation in words expressing emotions. In terms of projecting human psychology, these words convey specific and rich contexts, resulting in lexical ambiguity. In this study, we propose an emotional classification model that disambiguate word sense using bidirectional LSTM. It is based on the assumption that if the information of the surrounding context is fully reflected, the problem of lexical ambiguity can be solved and the emotions that the sentence wants to express can be expressed as one. Bidirectional LSTM is an algorithm that is frequently used in the field of natural language processing research requiring contextual information and is also intended to be used in this study to learn context. GloVe embedding is used as the embedding layer of this research model, and the performance of this model was verified compared to the model applied with LSTM and RNN algorithms. Such a framework could contribute to various fields, including marketing, which could connect the emotions of SNS users to their desire for consumption.