• Title/Summary/Keyword: Script-based Test

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The Design of Keyword Spotting System based on Auditory Phonetical Knowledge-Based Phonetic Value Classification (청음 음성학적 지식에 기반한 음가분류에 의한 핵심어 검출 시스템 구현)

  • Kim, Hack-Jin;Kim, Soon-Hyub
    • The KIPS Transactions:PartB
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    • v.10B no.2
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    • pp.169-178
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    • 2003
  • This study outlines two viewpoints the classification of phone likely unit (PLU) which is the foundation of korean large vocabulary speech recognition, and the effectiveness of Chiljongseong (7 Final Consonants) and Paljogseong (8 Final Consonants) of the korean language. The phone likely classifies the phoneme phonetically according to the location of and method of articulation, and about 50 phone-likely units are utilized in korean speech recognition. In this study auditory phonetical knowledge was applied to the classification of phone likely unit to present 45 phone likely unit. The vowels 'ㅔ, ㅐ'were classified as phone-likely of (ee) ; 'ㅒ, ㅖ' as [ye] ; and 'ㅚ, ㅙ, ㅞ' as [we]. Secondly, the Chiljongseong System of the draft for unified spelling system which is currently in use and the Paljongseonggajokyong of Korean script haerye were illustrated. The question on whether the phonetic value on 'ㄷ' and 'ㅅ' among the phonemes used in the final consonant of the korean fan guage is the same has been argued in the academic world for a long time. In this study, the transition stages of Korean consonants were investigated, and Ciljonseeng and Paljongseonggajokyong were utilized in speech recognition, and its effectiveness was verified. The experiment was divided into isolated word recognition and speech recognition, and in order to conduct the experiment PBW452 was used to test the isolated word recognition. The experiment was conducted on about 50 men and women - divided into 5 groups - and they vocalized 50 words each. As for the continuous speech recognition experiment to be utilized in the materialized stock exchange system, the sentence corpus of 71 stock exchange sentences and speech corpus vocalizing the sentences were collected and used 5 men and women each vocalized a sentence twice. As the result of the experiment, when the Paljongseonggajokyong was used as the consonant, the recognition performance elevated by an average of about 1.45% : and when phone likely unit with Paljongseonggajokyong and auditory phonetic applied simultaneously, was applied, the rate of recognition increased by an average of 1.5% to 2.02%. In the continuous speech recognition experiment, the recognition performance elevated by an average of about 1% to 2% than when the existing 49 or 56 phone likely units were utilized.

Design and Effects of Science Simulation Applications Using Flash and ActionScript 3.0: In the Composition of Material Chapter in Middle School Science Textbooks (Flash와 Actionscript 3.0을 이용한 과학 시뮬레이션 앱의 디자인 및 효과 -중학교 과학 '물질의 구성' 단원을 중심으로-)

  • Lee, Chang Youn;Park, Chulkyu;Hong, Hun-Gi
    • Journal of The Korean Association For Science Education
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    • v.38 no.4
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    • pp.527-539
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    • 2018
  • Although a simulation is proposed as a candidate for alternative contents of inquiry activities, design cases focused on the characteristic of science education are rare. This study suggested the definition and requirements of science simulation to clarify science subject-specific design and set up the design guidelines to consider usability. Then the science simulation was developed in the form of an app for mobile devices, where 'Flash and Actionscript 3.0' was selected as a development tool for compatibility, functionality, ease of use and optimization for mobile devices with educational applicability in mind. In effect, six science simulation apps were prepared for seven classes of inquiry activity in 10 science classes on the chapter of 'composition of material' in middle school science 2 textbooks. In this regard, the main advantages of the simulation apps expected from each design characteristic are also suggested in this article. In the implementation of the science simulation apps, educational effects were investigated based on the statistical comparison, while 134 students in the second grade in a coeducational middle school, Gyeonggi-do participated as an intervention group and a control group. Our results showed that the scores of academic achievement and affective test in the intervention group were significantly higher than those of the control group (p <.05). In the questionnaire survey on usability, most students responded positively to the design of the science simulation apps. This study will contribute to expanding the horizon of design about science simulation as a design case in science education.

Electric Vehicle Wireless Charging Control Module EMI Radiated Noise Reduction Design Study (전기차 무선충전컨트롤 모듈 EMI 방사성 잡음 저감에 관한 설계 연구)

  • Seungmo Hong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.2
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    • pp.104-108
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    • 2023
  • Because of recent expansion of the electric car market. it is highly growing that should be supplemented its performance and safely issue. The EMI problem due to the interlocking of electrical components that causes various safety problems such as fire in electric vehicles is emerging every time. We strive to achieve optimal charging efficiency by combining various technologies and reduce radioactive noise among the EMI noise of a weirless charging control module, one of the important parts of an electric vehicle was designed and tested. In order to analyze the EMI problems occurring in the wireless charging control module, the optimized wireless charging control module by applying the optimization design technology by learning the accumulated test data for critical factors by utilizing the Python-based script function in the Ansys simulation tool. It showed an EMI noise improvement effect of 25 dBu V/m compared to the charge control module. These results not only contribute to the development of a more stable and reliable weirless charging function in electric vehicles, but also increase the usability and efficiency of electric vehicles. This allows electric vehicles to be more usable and efficient, making them an environmentally friendly alternative.

The Ontology Based, the Movie Contents Recommendation Scheme, Using Relations of Movie Metadata (온톨로지 기반 영화 메타데이터간 연관성을 활용한 영화 추천 기법)

  • Kim, Jaeyoung;Lee, Seok-Won
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.25-44
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    • 2013
  • Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.