• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1443-1453
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• 1998

This paper presents the speech synthesis engine that converts the character strings kept in a computer memory into the synthesized speech sounds with enhancing the intelligibility and the naturalness by adapting the waveform processing method. The speech engine using demisyllable speech segments receives command streams for pitch modification, duration and energy control. The command based engine isolates the high level processing of text normalization, letter-to-sound and the lexical analysis and the low level processing of signal filtering and pitch processing. The TTS(Text-to-Speech) system implemented by using the speech synthesis engine has three independent object modules of the Text-Normalizer, the Commander and the said Speech Synthesis Engine those of which are easily replaced by other compatible modules. The architecture separating the high level and the low level processing has the advantage of the expandibility and the portability because of the mix-and-match nature.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.37-48
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• 2014

Social emotion is being highlighted as an important factor of human life in terms of quality of communication as a variety of social networks are commonly used. To understand such social emotion, this study verifies and analyzes the significance of lexical meaning and expression of emotion basically for understanding of complex meaning of social emotion. The emotional expressions represented in SNS text messages, one of the major channel of communication, are examined in this study to create scales of meaning and expression and to understand the differences deeply. As a result of the analysis, it turned out that negative assessment factors were more than positive ones among social emotional factors while positive ones were outstandingly many in the case of social emotional expression. Social emotional factors were classified by basic emotional elements and valences while emotional expression included complex meaning and especially positive elements were dominant in general.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.247-271
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• 2019

Uncertainty in scientific knowledge means an uncertain state where propositions are neither true or false at present. The existing studies have analyzed the propositions written in the academic literature, and have conducted the performance evaluation based on the rule based and machine learning based approaches by using the corpus. Although they recognized that the importance of word construction, there are insufficient attempts to expand the word by analyzing the meaning of uncertainty words. On the other hand, studies for analyzing the structure of networks by using bibliometrics and text mining techniques are widely used as methods for understanding intellectual structure and relationship in various disciplines. Therefore, in this study, semantic relations were analyzed by applying Word2Vec to existing uncertainty words. In addition, WordNet, which is an English vocabulary database and thesaurus, was applied to perform a network analysis based on hypernyms, hyponyms, and synonyms relations linked to uncertainty words. The semantic and lexical relationships of uncertainty words were structurally identified. As a result, we identified the possibility of automatically expanding uncertainty words.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1786-1793
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• 2022

Cyber-attacks such as smishing and hacking mail exploiting COVID-19, political and social issues, have recently been continuous. Machine learning and deep learning technology research are conducted to prevent any damage due to cyber-attacks inducing malicious links to breach personal data. It has been concluded as a lack of basis to judge the attacks to be malicious in previous studies since the features of data set were excessively simple. In this paper, nine main features of three types, "URL Days", "URL Word", and "URL Abnormal", were proposed in addition to lexical features of URL which have been reflected in previous research. F1-Score and accuracy index were measured through four different types of machine learning algorithms. An improvement of 0.9% in a result and the highest value, 98.5%, were examined in F1-Score and accuracy through comparatively analyzing an existing research. These outcomes proved the main features contribute to elevating the values in both accuracy and performance.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.151-160
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• 2015

As a lexical meaning, casino is defined as "a certified gambling house, equipped with recreational facilities such as dance and music, etc., where people play roulette or cards." Casinos started from 17th to 18th century for European nobility and their social meetings and established a casino industry framework in the United States in the 1930s. The success of the casino business leads to the increase of sales; it became very helpful for the local and national government revenues and also for the related incidental tasks. Casino operations include a variety of fields, such as general customer management, dealer game management, security, account management, currency exchange, re-exchange management, marketing management, comp management and placement management, etc. These operations should be organically connected to each other by information systems such as a groupware, ERP and Customer Relationship Management (CRM), etc. In addition, in order to effectively manage comprehensive entertainment service, including accommodation and tourism, it is necessary to develop an information system which supports casino business and collateral entertainment service, collects the data generated throughout the business and provides information about the situations of management. Thus, this study will propose a casino information system designed and implemented, considering these details.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.35-42
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• 2013

Developing English-Korean machine translation system requires the construction of information about the languages, and the amount of information in English-Korean transfer dictionary is especially critical to the translation quality. Newly created words are out-of-vocabulary words and they appear as they are in the translated sentence, which decreases the translation quality. Also, compound nouns make lexical and syntactic analysis complex and it is difficult to accurately translate compound nouns due to the lack of information in the transfer dictionary. In order to improve the translation quality of English-Korean machine translation, we must continuously expand the information of the English-Korean transfer dictionary by collecting the out-of-vocabulary words and the compound nouns frequently used. This paper proposes a method for expanding of the transfer dictionary, which consists of constructing corpus from internet newspapers, extracting the words which are not in the existing dictionary and the frequently used compound nouns, attaching meaning to the extracted words, and integrating with the transfer dictionary. We also develop the tool supporting the expansion of the transfer dictionary. The expansion of the dictionary information is critical to improving the machine translation system but requires much human efforts. The developed tool can be useful for continuously expanding the transfer dictionary, and so it is expected to contribute to enhancing the translation quality.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.177-184
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• 2010

As a voice browser is introduced, voice dialog application becomes available on the Web environment. The voice dialog application consists of voice Web pages that need to translate the dialog scripts into SALT(Speech Application Language Tags). The current Web pages have been designed for visual. They, however, are potentially capable of using voice dialog. This paper, therefore, proposes an automated voice Web generation method that finds the elements for voice dialog from Web pages based HTML and converts them into SALT. The automatic generation system of a voice Web page consists of a lexical analyzer and a syntactic analyzer that converts a Web page which is described in HTML to voice Web page which is described in HTML+SALT. The converted voice Web page is designed to be able to handle not only the current mouse and keyboard input but also voice dialog.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.466-475
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• 2003

To build an efficient Question-Answering (QA) system, a question type classifier is needed. It can classify user's queries into predefined categories regardless of the surface form of a question. In this paper, we propose a question type classifier using a Support Vector Machine (SVM). The question type classifier first extracts features like lexical forms, part of speech and semantic markers from a user's question. The system uses $X^2$ statistic to select important features. Selected features are represented as a vector. Finally, a SVM categorizes questions into predefined categories according to the extracted features. In the experiment, the proposed system accomplished 86.4% accuracy The system precisely classifies question type without using any rules like lexico-syntactic patterns. Therefore, the system is robust and easily portable to other domains.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.333-340
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• 2009

Most of the previous automatic word spacing systems are not suitable to use for mobile devices with relatively low computing powers because they require many system resources. We propose an automatic word spacing system that requires reasonable memory usage and simple numerical computations for mobile devices with low computing powers. The proposed system is a two step model that consists of a statistical system and a rule-based system. To reduce the memory usage, the statistical system first corrects word spacing errors by using a modified hidden Markov model based on character unigrams. Then, to increase the accuracy, the rule-based system re-corrects miscorrected word spaces by using lexical rules based on character bigrams or more. In the experiments, the proposed system showed relatively high accuracy of 94.14% in spite of small memory usage of about 1MB.

• Journal of KIISE:Software and Applications
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• v.34 no.2
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• pp.140-149
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• 2007

This paper presents a statistical model for Korean dependency-based parsing. Although Korean is one of free word order languages, it has the feature of which some word order is preferred to local contexts. Earlier works proposed parsing models using modification lengths due to this property. Our model uses headible path contexts for modification length probabilities. Using a headible path of a dependent it is effective for long distance relation because the large surface context for a dependent are abbreviated as its headible path. By combined with lexical bigram dependency, our probabilistic model achieves 86.9% accuracy in eojoel analysis for KAIST corpus, more improvement especially for long distance dependencies.