• Title/Summary/Keyword: 감정 예측 시스템

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Emotion Prediction from Natural Language Documents ith Emotion Network (감정망을 활용한 자연언어 문서 상의 감정예측)

  • Min, Hye-Jin;Park, Jong-C.
    • Annual Conference on Human and Language Technology
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    • 2004.10d
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    • pp.191-199
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    • 2004
  • 본 논문에서는 텍스트에 나타난 감정상태를 인지하는 모델을 제안하고, 이러한 모델을 활용하여 현재문장에서 나타난 감정 및 이후에 나타나게 될 감정상태들을 예측하는 시스템에 대하여 다룬다. 사용자의 감정을 인지하고 이에 대한 자연스러운 메시지, 행동 등을 통해 인간과 상호작용 할 수 있는 컴퓨터시스템을 구현하기 위해서는 현재의 감정상태뿐만 아니라 사용자 개개인의 정보 및 시스템과 상호작용하고 있는 상황의 정보 등을 통해 이후에 사용자가 느낄 수 있는 감정을 예측할 수 있는 감정모델이 요구된다. 본 논문에서는 파악된 이전의 감정상태 및 실제 감정과 표현된 감정간의 관계, 그리고 감정에 영향을 미친 주변대상의 특징 및 감정경험자의 목표와 행동이 반영된 상태-전이형태의 감정모델인 감정망(Emotion Network)을 제안한다. 감정망은 각 감정을 나타내는 상태(state)와 연결된 상태들 간의 전이(transition), 그리고 전이가 발생하기 위한 조건(condition)으로 구성된다. 본 논문에서는 텍스트 형태의 상담예시에 감정망을 활용하여 문헌의 감정어휘에 의해 직접적으로 표출되지 않는 감정을 예측할 수 있음을 보인다.

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A Speech Emotion Recognition System for Audience Response Collection (관객 반응정보 수집을 위한 음성신호 기반 감정인식 시스템)

  • Kang, Jin Ah;Kim, Hong Kook
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2013.06a
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    • pp.56-57
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    • 2013
  • 본 논문에서는 연극공연을 관람하는 관객의 반응정보를 수집하기 위하여, 청각센서를 통해 관객의 음성을 획득하고 획득된 음성에 대한 감정을 예측하여 관객 반응정보 관리시스템에 전송하는 음성신호 기반 감정인식 시스템을 구현한다. 이를 위해, 관객용 헤드셋 마이크와 다채널 녹음장치를 이용하여 관객음성을 획득하는 인터페이스와 음성신호의 특징벡터를 추출하여 SVM (support vector machine) 분류기에 의해 감정을 예측하는 시스템을 구현하고, 이를 관객 반응정보 수집 시스템에 적용한다. 실험결과, 구현된 시스템은 6가지 감정음성 데이터를 활용한 성능평가에서 62.5%의 인식률을 보였고, 실제 연극공연 환경에서 획득된 관객음성과 감정인식 결과를 관객 반응정보 수집 시스템에 전송함을 확인하였다.

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Visualization using Emotion Information in Movie Script (영화 스크립트 내 감정 정보를 이용한 시각화)

  • Kim, Jinsu
    • Journal of the Korea Convergence Society
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    • v.9 no.11
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    • pp.69-74
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    • 2018
  • Through the convergence of Internet technology and various information technologies, it is possible to collect and process vast amount of information and to exchange various knowledge according to user's personal preference. Especially, there is a tendency to prefer intimate contents connected with the user's preference through the flow of emotional changes contained in the movie media. Based on the information presented in the script, the user seeks to visualize the flow of the entire emotion, the flow of emotions in a specific scene, or a specific scene in order to understand it more quickly. In this paper, after obtaining the raw data from the movie web page, it transforms it into a standardized scenario format after refining process. After converting the refined data into an XML document to easily obtain various information, various sentences are predicted by inputting each paragraph into the emotion prediction system. We propose a system that can easily understand the change of the emotional state between the characters in the whole or a specific part of the various emotions required by the user by mixing the predicted emotions flow and the amount of information included in the script.

Emotion Prediction of Paragraph using Big Data Analysis (빅데이터 분석을 이용한 문단 내의 감정 예측)

  • Kim, Jin-su
    • Journal of Digital Convergence
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    • v.14 no.11
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    • pp.267-273
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    • 2016
  • Creation and Sharing of information which is structured data as well as various unstructured data. makes progress actively through the spread of mobile. Recently, Big Data extracts the semantic information from SNS and data mining is one of the big data technique. Especially, the general emotion analysis that expresses the collective intelligence of the masses is utilized using large and a variety of materials. In this paper, we propose the emotion prediction system architecture which extracts the significant keywords from social network paragraphs using n-gram and Korean morphological analyzer, and predicts the emotion using SVM and these extracted emotion features. The proposed system showed 82.25% more improved recall rate in average than previous systems and it will help extract the semantic keyword using morphological analysis.

Implementing an Adaptive Neuro-Fuzzy Model for Emotion Prediction Based on Heart Rate Variability(HRV) (심박변이도를 이용한 적응적 뉴로 퍼지 감정예측 모형에 관한 연구)

  • Park, Sung Soo;Lee, Kun Chang
    • Journal of Digital Convergence
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    • v.17 no.1
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    • pp.239-247
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    • 2019
  • An accurate prediction of emotion is a very important issue for the sake of patient-centered medical device development and emotion-related psychology fields. Although there have been many studies on emotion prediction, no studies have applied the heart rate variability and neuro-fuzzy approach to emotion prediction. We propose ANFEP(Adaptive Neuro Fuzzy System for Emotion Prediction) HRV. The ANFEP bases its core functions on an ANFIS(Adaptive Neuro-Fuzzy Inference System) which integrates neural networks with fuzzy systems as a vehicle for training predictive models. To prove the proposed model, 50 participants were invited to join the experiment and Heart rate variability was obtained and used to input the ANFEP model. The ANFEP model with STDRR and RMSSD as inputs and two membership functions per input variable showed the best results. The result out of applying the ANFEP to the HRV metrics proved to be significantly robust when compared with benchmarking methods like linear regression, support vector regression, neural network, and random forest. The results show that reliable prediction of emotion is possible with less input and it is necessary to develop a more accurate and reliable emotion recognition system.

Sentiment Prediction using Emotion and Context Information in Unstructured Documents (비정형 문서에서 감정과 상황 정보를 이용한 감성 예측)

  • Kim, Jin-Su
    • Journal of Convergence for Information Technology
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    • v.10 no.10
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    • pp.40-46
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    • 2020
  • With the development of the Internet, users share their experiences and opinions. Since related keywords are used witho0ut considering information such as the general emotion or genre of an unstructured document such as a movie review, the sensitivity accuracy according to the appropriate emotional situation is impaired. Therefore, we propose a system that predicts emotions based on information such as the genre to which the unstructured document created by users belongs or overall emotions. First, representative keyword related to emotion sets such as Joy, Anger, Fear, and Sadness are extracted from the unstructured document, and the normalized weights of the emotional feature words and information of the unstructured document are trained in a system that combines CNN and LSTM as a training set. Finally, by testing the refined words extracted through movie information, morpheme analyzer and n-gram, emoticons, and emojis, it was shown that the accuracy of emotion prediction using emotions and F-measure were improved. The proposed prediction system can predict sentiment appropriately according to the situation by avoiding the error of judging negative due to the use of sad words in sad movies and scary words in horror movies.

Emotion Prediction System using Movie Script and Cinematography (영화 시나리오와 영화촬영기법을 이용한 감정 예측 시스템)

  • Kim, Jinsu
    • Journal of the Korea Convergence Society
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    • v.9 no.12
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    • pp.33-38
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    • 2018
  • Recently, we are trying to predict the emotion from various information and to convey the emotion information that the supervisor wants to inform the audience. In addition, audiences intend to understand the flow of emotions through various information of non-dialogue parts, such as cinematography, scene background, background sound and so on. In this paper, we propose to extract emotions by mixing not only the context of scripts but also the cinematography information such as color, background sound, composition, arrangement and so on. In other words, we propose an emotional prediction system that learns and distinguishes various emotional expression techniques into dialogue and non-dialogue regions, contributes to the completeness of the movie, and quickly applies them to new changes. The precision of the proposed system is improved by about 5.1% and 0.4%, and the recall is improved by about 4.3% and 1.6%, respectively, when compared with the modified n-gram and morphological analysis.

Posture features and emotion predictive models for affective postures recognition (감정 자세 인식을 위한 자세특징과 감정예측 모델)

  • Kim, Jin-Ok
    • Journal of Internet Computing and Services
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    • v.12 no.6
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    • pp.83-94
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    • 2011
  • Main researching issue in affective computing is to give a machine the ability to recognize the emotion of a person and to react it properly. Efforts in that direction have mainly focused on facial and oral cues to get emotions. Postures have been recently considered as well. This paper aims to discriminate emotions posture by identifying and measuring the saliency of posture features that play a role in affective expression. To do so, affective postures from human subjects are first collected using a motion capture system, then emotional features in posture are described with spatial ones. Through standard statistical techniques, we verified that there is a statistically significant correlation between the emotion intended by the acting subjects, and the emotion perceived by the observers. Discriminant Analysis are used to build affective posture predictive models and to measure the saliency of the proposed set of posture features in discriminating between 6 basic emotional states. The evaluation of proposed features and models are performed using a correlation between actor-observer's postures set. Quantitative experimental results show that proposed set of features discriminates well between emotions, and also that built predictive models perform well.

System Implementation of Winner Forecasting for Election Cadidates Utilizing SNS Emotion Analysis (SNS 감정 분석을 이용한 선거 후보자 순위 예측 시스템)

  • Moon, Yoo-Jin;Lee, Hansoo;Park, Hyuk;Lee, Jaeyoung;Kim, Sunguk
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2017.01a
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    • pp.273-274
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    • 2017
  • 대한민국 20대 총선, 영국의 유럽연합 탈퇴인 브렉시트, 트럼프와 힐러리의 대결인 미국 대선, 이 셋의 공통점은 언론의 예측과 다른 투표 결과가 나왔다는 점이다. 이러한 일련의 사건들로 인해, 각종 언론사에서 실시하고 있는 표본조사의 신뢰도에 대한 근본적 재검토의 필요성이 제기되고 있는 실정이다. 본 논문에서는 선거 후보자 지지율을 효율적이며 효과적으로 분석하기 위하여 SNS 감정분석을 제안한다. SNS 감정분석은 기존의 표본을 구하고 분석하는 방식보다 더 빠르게 표본 수집 및 분석이 가능하다. 또한 R프로그램과 구글을 이용하여 처리하기 때문에 기존 방식에 비하여 매우 저렴하다. 현재 언론사의 예측이 빗나가고 있는 시점에서 SNS 감정분석이 훌륭한 대안이 될 수 있을 것이다. 본 연구에서의 트래픽*감정분석 점수를 보았을 때, SNS 감정분석이 여론을 더 정확히 반영한다는 것을 증명한다.

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A Rating System on Movie Reviews using the Emotion Feature and Kernel Model (감정자질과 커널모델을 이용한 영화평 평점 예측 시스템)

  • Xu, Xiang-Lan;Jeong, Hyoung-Il;Seo, Jung-Yun
    • Annual Conference on Human and Language Technology
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    • 2011.10a
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    • pp.37-41
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    • 2011
  • 본 논문에서는 최근 많은 관심을 받고 있는 Opinion Mining으로서 사용자들의 자연어 형태의 영화평 문장을 분석하여 자동으로 평점을 예측하는 시스템을 제안한다. 제안 시스템은 영화평 분석에 적합한 어휘 자질, 감정 자질, 가치 자질 및 기타 자질들을 추출하고, 10점 척도의 영화평의 평점을 10개의 범주로 가정하여, 커널모델인 다중 범주 Support Vector Machine (SVM) 모델을 이용하여 높은 성능으로 영화평의 평점을 범주 분류한다.

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