• Title/Summary/Keyword: text recognition

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Operation Technique of Spatial Data Change Recognition Data per File (파일 단위 공간데이터 변경 인식 데이터 운영 기법)

  • LEE, Bong-Jun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.4
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    • pp.184-193
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    • 2021
  • The system for managing spatial data updates the existing information by extracting only the information that is different from the existing information for the newly obtained spatial information file to update the stored information. In order to extract only objects that have changed from existing information, it is necessary to compare whether there is any difference from existing information for all objects included in the newly obtained spatial information file. This study was conducted to improve this total inspection method in a situation where the amount of spatial information that is frequently updated increases and data update is required at the national level. In this study, before inspecting individual objects in a new acquisition space information file, a method of determining whether individual space objects have been changed only by the information in the file was considered. Spatial data files have structured data characteristics different from general image or text document files, so it is possible to determine whether to change the file unit in a simpler way compared to the existing method of creating and managing file hash. By reducing the number of target files that require full inspection, it is expected to improve the use of resources in the system by saving the overall data quality inspection time and saving data extraction time.

A Study on Image Recognition of local Currency Consumers Using Big Data (빅데이터를 활용한 지역화폐 소비자 이미지 인식에 관한 연구)

  • Kim, Myung-hee;Ryu, Ki-hwan
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.4
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    • pp.11-17
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    • 2022
  • Currently, the income and funds of the local economy are flowing out to the metropolitan area, and talented people, the driving force for regional development, also gather in the metropolitan area, and the local economy is facing a serious crisis. Local currency is issued by local governments and is a currency with auxiliary and complementary functions that can be used only within the area concerned. In order to revitalize the local economy, as local governments have focused their attention on the introduction of local currency, studies on the issuance and use of local currency are continuously being conducted. In this study, by using big data from data materials such as portals and SNS, the consumer image of local currency issued in local governments was identified through big data analysis, and based on the research results, the issuance and operation of local currency was conducted. The purpose is to present implications for The results of this study are as follows. First, by inducing local consumption through the policy issuance of local currency, it is showing the effect of increasing the economic income of the region. Second, local governments are exerting efforts to revitalize the economy and establish a virtuous cycle system for the local economy by issuing and distributing local currency. Third, the introduction of blockchain technology shows the stable operation of local currency. With academic significance, it was possible to grasp the changed appearance and effect of local currency through big data analysis and the policy direction of local currency.

Implementation of CoMirror System with Video Call and Messaging Function between Smart Mirrors (스마트 미러간 화상 통화와 메시징 기능을 가진 CoMirror 시스템 구현)

  • Hwang, Kitae;Kim, Kyung-Mi;Kim, Yu-Jin;Park, Chae-Won;Yoo, Song-Yeon;Jung, Inhwan;Lee, Jae-Moon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.6
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    • pp.121-127
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    • 2022
  • Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the useer along with the mirror function. This paper went beyond the form of dealing with smart mirrors only stand alone device the provide information to users, and constructed a network in which smart mirrors are connected, and proposed and implemented a CoMirror system that allows users to talk and share information with other smart mirror users. The CoMirror system has a structure in which several CoMirror clients are connected on one CoMirror server. The CoMirror client consists of Raspberry Pi, a mirror film, a touch pad, a display device, an web camera, etc. The server has functions such as face learning and recognition, user management, a relay role for exchanging messages between clients, and setting up for video call. Users can communicate with other CoMirror users via the server, such as text, image, and audio messages, as well as 1:1 video call.

A Study on the Multi-Layered Intertextuality of (영화 <드라이브 마이 카>의 다층적 상호텍스트성 고찰)

  • Bae, Kihyung;Kim, Chi Ho
    • The Journal of the Korea Contents Association
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    • v.22 no.9
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    • pp.169-178
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    • 2022
  • In this article, the narrative strategy of Ryusuke Hamaguchi's is researched focusing on multi-layered intertextuality. is framed in the form of a 'story in a story that embraces a story', and the recognition of intertextuality has an important meaning in examining the storytelling strategy of . Because this movie was adapted from the short stories from Haruki's , the various stories included in the film overlap to form the overall narrative. Therefore, in order to understand properly, it is important to understand the organic semantic relationship between the texts in the movie. Understanding the narrative of is also the process of interconnecting textual content of multiple texts included in the film. In , the dream story told by Otto, Gafuku's wife, the main character, and in the play are elaborately linked to the narrative of the entire film in layers and three dimensions with text in a frame. Hamaguchi reinforces the need for the audience through the intertextual narrative strategy of . In addition, the metaphor and personalized space of contributes to the effective delivering the narrative of healing to the audience.

A Multi-speaker Speech Synthesis System Using X-vector (x-vector를 이용한 다화자 음성합성 시스템)

  • Jo, Min Su;Kwon, Chul Hong
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.4
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    • pp.675-681
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    • 2021
  • With the recent growth of the AI speaker market, the demand for speech synthesis technology that enables natural conversation with users is increasing. Therefore, there is a need for a multi-speaker speech synthesis system that can generate voices of various tones. In order to synthesize natural speech, it is required to train with a large-capacity. high-quality speech DB. However, it is very difficult in terms of recording time and cost to collect a high-quality, large-capacity speech database uttered by many speakers. Therefore, it is necessary to train the speech synthesis system using the speech DB of a very large number of speakers with a small amount of training data for each speaker, and a technique for naturally expressing the tone and rhyme of multiple speakers is required. In this paper, we propose a technology for constructing a speaker encoder by applying the deep learning-based x-vector technique used in speaker recognition technology, and synthesizing a new speaker's tone with a small amount of data through the speaker encoder. In the multi-speaker speech synthesis system, the module for synthesizing mel-spectrogram from input text is composed of Tacotron2, and the vocoder generating synthesized speech consists of WaveNet with mixture of logistic distributions applied. The x-vector extracted from the trained speaker embedding neural networks is added to Tacotron2 as an input to express the desired speaker's tone.

Automated Inspection System for Micro-pattern Defection Using Artificial Intelligence (인공지능(AI)을 활용한 미세패턴 불량도 자동화 검사 시스템)

  • Lee, Kwan-Soo;Kim, Jae-U;Cho, Su-Chan;Shin, Bo-Sung
    • Journal of the Korean Society of Industry Convergence
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    • v.24 no.6_2
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    • pp.729-735
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    • 2021
  • Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.

Exploring Narratives on Post-traumatic Growth of Middle-aged Women Who Are Attached to Instabilith (중년여성의 불안정 애착과 외상 후 성장에 관한 내러티브 탐구)

  • Bang, Eun-Jeong;Shin, Dong-Yeol
    • Industry Promotion Research
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    • v.7 no.3
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    • pp.77-83
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    • 2022
  • This study was conducted with the purpose of helping middle-aged women who experienced insecure attachment during personal growth experience positive changes by re-illuminating their own growth process. During this study period, 14 in-depth interviews were conducted from August 2020 to September 2021, and the interview contents were based on the narrative research methodology to examine the meaning of participants' experiences regarding unstable attachment and post-traumatic growth in existential contexts. The text was described in terms of, relational context, life context, etc. As a result of the study, three participants who experienced unstable attachment and post-traumatic growth were selected and the following conclusions were drawn. First, the meaning in the existential context is the desire for recognition, perfectionism, unstable family environment, how to cope with stress, the courage to face the wounds, self-acceptance and affirmation, gratitude to the people around you, and the hope of life is the meaning in the participant experience. was interpreted as Second, the meaning in the relational context was interpreted as experiences with parents, husbands, children, interpersonal relationships, and religion. Third, the meaning in the life context is the lack of care, the reproduction of control, the responsibility as the eldest daughter, the precious family, and the meaning and value of life is the present experience in which the various experiences with the parents in the past affect the lives of the current participants. interpreted in Through the above research results, this study aims to describe the experiences of insecure attachment during childhood and the post-traumatic growth process of participants using a narrative technique, and to suggest positive alternatives to their lives.

Analyzing Perceptions of Unused Facilities in Rural Areas Using Big Data Techniques - Focusing on the Utilization of Closed Schools as a Youth Start-up Space - (빅데이터 분석 기법을 활용한 농촌지역 유휴공간 인식 분석 - 청년창업 공간으로써 폐교 활용성을 중심으로 -)

  • Jee Yoon Do;Suyeon Kim
    • Journal of Environmental Impact Assessment
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    • v.32 no.6
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    • pp.556-576
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    • 2023
  • This study attempted to find a way to utilize idle spaces in rural areas as a way to respond to rural extinction. Based on the keywords "startup," "youth start-up," and "youth start-up+rural," start-up+rural," the study sought to identify the perception of idle facilities in rural areas through the keywords "Idle facilities" and "closed schools." The study presented basic data for policy direction and plan search by reviewing frequency analysis, major keyword analysis, network analysis, emotional analysis, and domestic and foreign cases. As a result of the analysis, first, it was found that idle facilities and school closures are acting importantly as factors for regional regeneration. Second, in the case of youth startups in rural areas, it was found that not only education on agriculture but also problems for residence should be solved together. Third, in the case of young people, it was confirmed that it was necessary to establish digital utilization for agriculture by actively starting a business using digital. Finally, in order to attract young people and revitalize the region through best practices at home and abroad, policy measures that can serve as various platforms such as culture and education as well as startups should be presented in connection with local residents. These results are significant in that they presented implications for youth start-ups in rural areas by reviewing start-up recognition for the influx of young people as one of the alternatives for the use of idle facilities and regional regeneration, and if additional solutions are presented through field surveys, they can be used to set policy goals that fit the reality.

Machine-learning-based out-of-hospital cardiac arrest (OHCA) detection in emergency calls using speech recognition (119 응급신고에서 수보요원과 신고자의 통화분석을 활용한 머신 러닝 기반의 심정지 탐지 모델)

  • Jong In Kim;Joo Young Lee;Jio Chung;Dae Jin Shin;Dong Hyun Choi;Ki Hong Kim;Ki Jeong Hong;Sunhee Kim;Minhwa Chung
    • Phonetics and Speech Sciences
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    • v.15 no.4
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    • pp.109-118
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    • 2023
  • Cardiac arrest is a critical medical emergency where immediate response is essential for patient survival. This is especially true for Out-of-Hospital Cardiac Arrest (OHCA), for which the actions of emergency medical services in the early stages significantly impact outcomes. However, in Korea, a challenge arises due to a shortage of dispatcher who handle a large volume of emergency calls. In such situations, the implementation of a machine learning-based OHCA detection program can assist responders and improve patient survival rates. In this study, we address this challenge by developing a machine learning-based OHCA detection program. This program analyzes transcripts of conversations between responders and callers to identify instances of cardiac arrest. The proposed model includes an automatic transcription module for these conversations, a text-based cardiac arrest detection model, and the necessary server and client components for program deployment. Importantly, The experimental results demonstrate the model's effectiveness, achieving a performance score of 79.49% based on the F1 metric and reducing the time needed for cardiac arrest detection by 15 seconds compared to dispatcher. Despite working with a limited dataset, this research highlights the potential of a cardiac arrest detection program as a valuable tool for responders, ultimately enhancing cardiac arrest survival rates.

The Error Pattern Analysis of the HMM-Based Automatic Phoneme Segmentation (HMM기반 자동음소분할기의 음소분할 오류 유형 분석)

  • Kim Min-Je;Lee Jung-Chul;Kim Jong-Jin
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.5
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    • pp.213-221
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    • 2006
  • Phone segmentation of speech waveform is especially important for concatenative text to speech synthesis which uses segmented corpora for the construction of synthetic units. because the quality of synthesized speech depends critically on the accuracy of the segmentation. In the beginning. the phone segmentation was manually performed. but it brings the huge effort and the large time delay. HMM-based approaches adopted from automatic speech recognition are most widely used for automatic segmentation in speech synthesis, providing a consistent and accurate phone labeling scheme. Even the HMM-based approach has been successful, it may locate a phone boundary at a different position than expected. In this paper. we categorized adjacent phoneme pairs and analyzed the mismatches between hand-labeled transcriptions and HMM-based labels. Then we described the dominant error patterns that must be improved for the speech synthesis. For the experiment. hand labeled standard Korean speech DB from ETRI was used as a reference DB. Time difference larger than 20ms between hand-labeled phoneme boundary and auto-aligned boundary is treated as an automatic segmentation error. Our experimental results from female speaker revealed that plosive-vowel, affricate-vowel and vowel-liquid pairs showed high accuracies, 99%, 99.5% and 99% respectively. But stop-nasal, stop-liquid and nasal-liquid pairs showed very low accuracies, 45%, 50% and 55%. And these from male speaker revealed similar tendency.