• Speech Sciences
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• v.10 no.4
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• pp.167-177
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• 2003

This paper presents a method of building an exceptional pronunciation dictionary for Korean automatic pronunciation generator. An automatic pronunciation generator is an essential element of speech recognition system and a TTS (Text-To-Speech) system. It is composed of a part of regular rules and an exceptional pronunciation dictionary. The exceptional pronunciation dictionary is created by extracting the words which have exceptional pronunciations from text corpus based on the characteristics of the words of exceptional pronunciation through phonological research and text analysis. Thus, the method contributes to improve performance of Korean automatic pronunciation generator as well as the performance of speech recognition system and TTS system.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.248-252
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• 2004

Cultural, social, economic and other various environmental factors affect our language and different words and terminology are used and coined for different contexts, resulting in quantitative change of vocabulary. This paper presents an automatic pronunciation generator using selection procedure for exceptional pronunciation words from added text corpus, which reflects this dynamic nature of language. For our experiment, we used the text corpus released by ETRI for speech recognition. consisting or 53,750 sentences (740.497 Eojols), and obtained a 100% performance level of the proposed automatic pronunciation generator.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1203-1212
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• 2012

In this paper, we consider the development of round key generator of DES (data encryption standard) based on Microsoft Excel Macro, which was adopted as the FIPS (federal information processing standard) of USA in 1977. Simple introduction to DES is given. Algorithms for round key generator are adapted to excel macro. By repeating the 16 round which is consisted of diffusion (which hide the relation between plain text and cipher text) and the confusion (which hide the relation between cipher key and cipher text) with Microsoft Excel Macro, we can easily get the desired DES round keys.

• MALSORI
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• no.48
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• pp.57-67
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• 2003

This paper presents a systematic description of exceptional pronunciations for automatic Korean pronunciation generation. An automatic pronunciation generator in Korean is an essential part of a Korean speech recognition system and a TTS (Text-To-Speech) system. It is composed of a set of regular rules and an exceptional pronunciation dictionary. The exceptional pronunciation dictionary is created by extracting the words that have exceptional pronunciations, based on the characteristics of the words of exceptional pronunciation through phonological research and the systematic analysis of the entries of Korean dictionaries. Thus, the method contributes to improve performance of automatic pronunciation generator in Korean as well as the performance of speech recognition system and TTS system in Korean.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1891-1908
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• 2021

Cyber deception defense mitigates Advanced Persistent Threats (APTs) with deploying deceptive entities, such as the Honeyfile. The Honeyfile distracts attackers from valuable digital documents and attracts unauthorized access by deliberately exposing fake content. The effectiveness of distraction and trap lies in the enticement of fake content. However, existing studies on the Honeyfile focus less on this perspective. In this work, we seek to improve the enticement of fake text content through enhancing its readability, indistinguishability, and believability. Hence, an enticing deceptive-content generator, EDGE, is presented. The EDGE is constructed with three steps: extracting key concepts with a semantics-aware K-means clustering algorithm, searching for candidate deceptive concepts within the Word2Vec model, and generating deceptive text content under the Integrated Readability Index (IR). Furthermore, the readability and believability performance analyses are undertaken. The experimental results show that EDGE generates indistinguishable deceptive text content without decreasing readability. In all, EDGE proves effective to generate enticing deceptive text content as deception defense against APTs.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.975-978
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• 2002

A new conception of public-key cryptography MEPKC, Petri net based Multi-stage-Encryption Public-Key Cryptography, has been proposed in onder to guarantee stronger network communication security. Different from an ordinary public-key cryptography that opens only a single public key to the public, MEPKC opens a key-generator that can generate multiple encryption keys and uses these keys to encrypt a plain text to a cipher text stage by stage. In this paper, we propose the methods how to carry out the encryption operations. First, we describe how to design a hash function H that is used to conceal the encryption keys from attack. Then, given with a key-generator (a Petri net supposed to possess a large number of elementary T-invariants), we discuss how to randomly generate a series of encryption keys, the elementary T-invariants. Finally, we show how to use these encryption keys to encrypt a plain text to a cipher text by applying a private key cryptography, say DES.

• Journal of Korean Library and Information Science Society
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• v.35 no.3
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• pp.271-291
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• 2004

Such information services source like digital library has been asked information services of atypical multimedia database like image, voice, VOD/AOD. Examined in this study are suggestions such as word-phrase generator, syllable recoverer, morphological analyzer, corrector for voice processing. Suggested voice processing technique transform voice database into tort database, then extract index database from text database. On top of this, the study suggest a information retrieval model to use in extracted index database, voice full-text information retrieval.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.807-812
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• 2024

AI interprets user prompts, surveys data, and generates output. Users input natural language into the prompt in the form of a two-way conversation, and the methodology for conveying accurate intentions to AI is called prompt engineering. Generative AI was used during jewelry production ideation during a major course at H University, and the need for prompt-related research was observed during the training evaluation process. Using the prompt methodology derived from this study, we aim to reduce deviations in output and strengthen prompt capabilities for jewelry production ideas through upward standardization. As a result of applying prompting engineering through previous research, it was confirmed that there is a positive correlation between the advancement of prompts and the completeness of AI output. In the future, through this study, we hope to learn the fundamental principles of prompting and to be helpful in utilizing AI.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.347-353
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• 2022

In this paper, we propose a method that performs a text-video retrieval model by replacing video properties using captions. In general, the exisiting embedding-based models consist of both joint embedding space construction and the CNN-based video encoding process, which requires a lot of computation in the training as well as the inference process. To overcome this problem, we introduce a video-captioning module to replace the visual property of video with captions generated by the video-captioning module. To be specific, we adopt the caption generator that converts candidate videos into captions in the inference process, thereby enabling direct comparison between the text given as a query and candidate videos without joint embedding space. Through the experiment, the proposed model successfully reduces the amount of computation and inference time by skipping the visual processing process and joint embedding space construction on two benchmark dataset, MSR-VTT and VATEX.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.276-282
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• 2021

The system for recognizing text in natural scenes has been applied in various industries. However, due to the change in brightness that occurs in nature such as light reflection and shadow, the text recognition performance significantly decreases. To solve this problem, we propose an adversarial shadow generation and training algorithm that is robust to shadow changes. The adversarial shadow generation and training algorithm divides the entire image into a total of 9 grids, and adjusts the brightness with 4 trainable parameters for each grid. Finally, training is conducted in a adversarial relationship between the text recognition model and the shaded image generator. As the training progresses, more and more difficult shaded grid combinations occur. When training with this curriculum-learning attitude, we not only showed a performance improvement of more than 3% in the ICDAR2015 public benchmark dataset, but also confirmed that the performance improved when applied to our's android application text recognition dataset.