• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.756-765
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• 2000

In this paper, a korean text to sign language translation system is designed and implemented for the hearing impaired people to learn letters and to have a conversation with normal people. We adopt the direct method for machine translation which uses morphological analysis and the dictionary search. And we define the necessary sign language dictionaries. Based on this processes, the system translate korean sentences to sign language moving picture. The proposed dictionaries are composed of the basic sign language dictionary, the compound sing language dictionary, and the resemble sign language dictionary. The basic sign language dictionary includes basic symbols and moving pictures of korean sign language. The compound sing language dictionary is composed of key-words of basic sign language. In addition, we offered the similar letters at the resemble sign language dictionary. The moving pictures of searched sign symbols are displayed on a screen in GIF formats by continuous motion of sign symbols or represented by the finger spelling based on the korean code analysis. The proposed system can provide quick sign language search and complement the lack of sign languages in the translation process by using the various sign language dictionaries which are characterized as korean sign language. In addition, to represent the sign language using GIF makes it possible to save the storage space of the sign language. In addition, to represent the sign language using GIF makes it possible to save storage space of the sign language dictionary.

• Cross-Cultural Studies
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• v.29
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• pp.287-314
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• 2012

This article examines the problems with some words used in "Chinese novel Kam Pin Mui"that are presented in"the Great Chinese-Korean dictionary". The author analyses the problems into three aspects: first, error correction in meaning interpretation; second, supplementary correction in meaning interpretation; and third, additional error correction. The main points of the study are presented in the following. First, in relation to the error correction in meaning interpretation, this study finds out that the explanations of "Liezi", "daxuanmo", "kedui", "shaojian" in the "Great Chinese-Korean dictionary"are incorrect. The cases involve the explanations that have no foundation, do not get to the points, and have narrow meaning interpretations compared with original meanings. Second, as for the supplementary correction, this study points out that the explanations of "yiri", "jiaosa", "buxi", "langhu" are not sufficient. Thus, this study claims that the following meanings for each case should be added, including "long time," "abdominal pains during pregnancy," "a type of folk performing arts without stages in local areas of China, and "to devour in greedy gulps." Third, with respect to the additional error correction, this study analyses "the typos of the examples," "the setup of inaccurate meaning items," "the front-to-back arrangement of the examples," and "inconsistency between meaning interpretations and examples" displayed in the dictionary. The error correction in the dictionary can be possible only if the findings from several other disciplines should be incorporated, involving cultural history, the history of literature, philology, grammatology, linguistics, etc. It seems impossible for a person to solve all the problems with the errors in the dictionary. Thus, it will be greatly helpful to the author and the people who prepare for the new edition of "the Great Chinese-Korean dictionary" if we can get continuous supports and comments from relating scholars of other disciplines. As a result, all these efforts will contribute to the academic progress for the relevant disciplines and these academic activities may develop a new area of the study.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.481-486
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• 2023

Anomaly detection holds paramount significance across diverse fields, encompassing fraud detection, risk mitigation, and sensor evaluation tests. Its pertinence extends notably to the military, particularly within the Warrior Platform, a comprehensive combat equipment system with wearable sensors. Hence, we propose a data-compression-based anomaly detection approach tailored to unlabeled time series and sequence data. This method entailed the construction of two distinctive features, typicality and atypicality, to discern anomalies effectively. The typicality of a test sequence was determined by evaluating the compression efficacy achieved through the pattern dictionary. This dictionary was established based on the frequency of all patterns identified in a training sequence generated for each sensor within Warrior Platform. The resulting typicality served as an anomaly score, facilitating the identification of anomalous data using a predetermined threshold. To improve the performance of the pattern dictionary method, we leveraged atypicality to discern sequences that could undergo compression independently without relying on the pattern dictionary. Consequently, our refined approach integrated both typicality and atypicality, augmenting the effectiveness of the pattern dictionary method. Our proposed method exhibited heightened capability in detecting a spectrum of unpredictable anomalies, fortifying the stability of wearable sensors prevalent in military equipment, including the Army TIGER 4.0 system.

• 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 KIPS Transactions:PartD
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• v.9D no.3
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• pp.457-466
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• 2002

In this paper, we designed and implemented a web-based dictionary of computing which keeps the data up-to-date. This dictionary shows the English information based on the FOLDOC (Free On-Line Dictionary Of Computing) dictionary file at the beginning of searching, and then one or more users can translate the information into Korean. This function is the new one only this dictionary has. Also, we can easily find any words we want to took up, even if we don't know the spelling completely, because the dictionary has various searching interfaces (searching for the words starting with inputted characters, searching for the words including inputted characters in the description, etc.) using a SQL Server DBMS and SQL. The performance test for CPU load factor shows that the server can support at least 1780 users at the same time.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.41-44
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• 2002

This paper is related to the enhancement of speech recognition rate using enhanced pronunciation dictionary. Modern large vocabulary, continuous speech recognition systems have pronunciation dictionaries. A pronunciation dictionary provides pronunciation information for each word in the vocabulary in phonemic units, which are modeled in detail by the acoustic models. But in most speech recognition system based on Hidden Markov Model, actual pronunciation variations are disregarded. Without the pronunciation variations in the speech recognition system, the phonetic transcriptions in the dictionary do not match the actual occurrences in the database. In this paper, we proposed the unvoiced rule of semivowel in allophone rules to pronunciation dictionary. Experimental results on speech recognition system give higher performance than existing pronunciation dictionaries.

• MALSORI
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• no.65
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• pp.93-103
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• 2008

In this paper, we propose a method for optimizing a multiple pronunciation dictionary used for modeling pronunciation variations of non-native speech. The proposed method removes some confusable pronunciation variants in the dictionary, resulting in a reduced dictionary size and less decoding time for automatic speech recognition (ASR). To this end, a confusability measure is first defined based on the Levenshtein distance between two different pronunciation variants. Then, the number of phonemes for each pronunciation variant is incorporated into the confusability measure to compensate for ASR errors due to words of a shorter length. We investigate the effect of the proposed method on ASR performance, where Korean is selected as the target language and Korean utterances spoken by Chinese native speakers are considered as non-native speech. It is shown from the experiments that an ASR system using the multiple pronunciation dictionary optimized by the proposed method can provide a relative average word error rate reduction of 6.25%, with 11.67% less ASR decoding time, as compared with that using a multiple pronunciation dictionary without the optimization.

• KIISE Transactions on Computing Practices
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• v.21 no.7
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• pp.500-505
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• 2015

The Sejong Electronic(machine readable) Dictionary, which was developed by the 21 century Sejong Plan, contains a systematic of immanence information of Korean words. It helps in solving the problem of electronical presentation of a general text dictionary commonly used. Word sense disambiguation problems can also be solved using the specific information available in the Sejong Electronic Dictionary. However, the Sejong Electronic Dictionary has a limitation of suggesting structure of sentences and selection-restricted nouns. In this paper, we discuss limitations of word sense disambiguation by using subcategorization information as suggested by the Sejong Electronic Dictionary and generalize selection-restricted noun of argument using Korean Lexico-semantic network.

• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.103-110
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• 2015

Sentiment lexicon is an essential element for expressing sentiment on a text or recognizing sentiment from a text. We propose a graph-based semi-supervised learning method to construct a sentiment dictionary as sentiment lexicon set. In particular, we focus on the construction of domain-specific sentiment dictionary. The proposed method makes up a graph according to lexicons and proximity among lexicons, and sentiments of some lexicons which already know their sentiment values are propagated throughout all of the lexicons on the graph. There are two typical types of the sentiment lexicon, sentiment words and sentiment phrase, and we construct a sentiment dictionary by creating each graph of them and infer sentiment of all sentiment lexicons. In order to verify our proposed method, we constructed a sentiment dictionary specific to the movie domain, and conducted sentiment classification experiments with it. As a result, it have been shown that the classification performance using the sentiment dictionary is better than the other using typical general-purpose sentiment dictionary.

• Korean Journal of Cognitive Science
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• v.7 no.4
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• pp.75-93
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• 1996