• Title/Summary/Keyword: AI Storytelling

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Influence of Consumers' Knowledge on Their Behavioral intentions By the Storytelling about the Local Food (소비자의 지식이 향토음식 스토리텔링에 의한 행동의도에 미치는 영향)

  • Song, Young-Ai;Jeon, Ki-Heung
    • Proceedings of the Korea Contents Association Conference
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    • 2013.05a
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    • pp.55-56
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    • 2013
  • 본 연구에서는 소비자의 지식 수준에 따른 향토음식 스토리텔링에 의한 행동의도를 알아보고자 하였다. 지금까지 우리나라 각 지역의 전통적인 식문화를 담고 있는 향토음식과 관련된 스토리텔링 연구를 살펴보면 대부분의 연구가 음식 스토리텔링의 필요성 제기, 음식 스토리의 소재 발굴, 미식 관광을 위한 스토리텔링의 중요성에 대한 연구에 머무르고 있다. 그러나 본 연구에서는 향토음식 스토리텔링이 소비자의 행동의도에 미치는 영향을 살펴보고자 향토음식과 관련된 지식에 기초하여 스토리텔링의 속성과 향토음식의 구매지역을 조절변수로 두었다. 최종적으로 지식의 정도가 낮으며, 구매지역이 일치하지 않는 경우 소비자들이 가장 선호하는 스토리텔링의 속성을 제시하고자 한다. 따라서 각 지역을 대표하는 향토음식의 스토리텔링을 발굴 또는 창작할 경우 향토음식의 문화적 가치를 향상시킬 수 있는 스토리텔링 개발 방법을 제시하고자 한다.

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Generating Extreme Close-up Shot Dataset Based On ROI Detection For Classifying Shots Using Artificial Neural Network (인공신경망을 이용한 샷 사이즈 분류를 위한 ROI 탐지 기반의 익스트림 클로즈업 샷 데이터 셋 생성)

  • Kang, Dongwann;Lim, Yang-mi
    • Journal of Broadcast Engineering
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    • v.24 no.6
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    • pp.983-991
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    • 2019
  • This study aims to analyze movies which contain various stories according to the size of their shots. To achieve this, it is needed to classify dataset according to the shot size, such as extreme close-up shots, close-up shots, medium shots, full shots, and long shots. However, a typical video storytelling is mainly composed of close-up shots, medium shots, full shots, and long shots, it is not an easy task to construct an appropriate dataset for extreme close-up shots. To solve this, we propose an image cropping method based on the region of interest (ROI) detection. In this paper, we use the face detection and saliency detection to estimate the ROI. By cropping the ROI of close-up images, we generate extreme close-up images. The dataset which is enriched by proposed method is utilized to construct a model for classifying shots based on its size. The study can help to analyze the emotional changes of characters in video stories and to predict how the composition of the story changes over time. If AI is used more actively in the future in entertainment fields, it is expected to affect the automatic adjustment and creation of characters, dialogue, and image editing.

The Study of Framework of Structural Scenarios for Chatbot Docent in Science Centers and Museums (과학관 챗봇 도슨트 개발을 위한 구조화된 시나리오의 틀 연구)

  • Kim, Hong-Jeong;Rhee, Sang-Won;Jeong, Seok-Hoon;Tahk, Hyun-Soo
    • Journal of the Korea Convergence Society
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    • v.11 no.11
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    • pp.115-121
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    • 2020
  • This study aims to develop a framework of structural scenarios for chatbot docent that supports visitors' activities in science centers and museums, and to suggest the application examples. For this study, the author adapted Focus Group Interview. As a result, the frameworks of scenarios could be categorized into the Collection of Science and Technology(CST) and Inquiry-Based Exhibition(IBE). These frameworks had dimensions of the primary and storytelling in common. Especially, framework of IBE scenario was added the usage dimension considering the characteristics of interaction between exhibits and visitors. This study could be basic materials for AI chatbot to support exhibition descriptions using the built data, and is expected to be help develop a more visitor-oriented scenarios of activities.

Analysis of the Effects of Reading Education Using S-PUMA Teaching Method on Elementary Students' Literary Imagination and Computational Thinking (S-PUMA 교수법을 활용한 글 읽기 교육이 초등학생의 문학적 상상력과 컴퓨팅사고력에 미치는 영향 분석)

  • Eol Sohn;Youngsik Jeong
    • Journal of The Korean Association of Information Education
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    • v.26 no.6
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    • pp.567-577
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    • 2022
  • Interest in AI and SW education is growing as digital literacy is emphasized in the revised elementary school curriculum for 2022. There are numerous restrictions on how pupils can enhance their digital literacy because there are only 34 class hours available for information education in elementary schools. Therefore, other subjects and information education must be blended in order to ensure class hours for AI and SW instruction. In this study, we investigated the impact of S-PUMA reading instruction on the literary imagination and computational thinking of elementary school pupils. To conduct this study, two classes of sixth graders in an elementary school were chosen and split into an experimental group and a control group. Over the course of five sessions, only the experimental group received reading instruction using the S-PUMA teaching approach. It was discovered that reading instruction with the S-PUMA teaching methodology enhanced literary imagination and computational thinking. Further study is required to identify whether the improvement in creative imagination, a component of literary imagination, is a result of the S-PUMA teaching approach or a natural result of the subject matter of the lesson.