• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4241-4254
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• 2019

The efficiency and accuracy of handwriting measurement could be improved by adopting digital image processing. This study developed a computer-based Korean Handwriting Assessment tool. Second graders participated in this study by performing writing tasks of consonants, vowels, words, and sentences. We extracted boundary parameters for each letter using digital image processing and calculated the variables of size, size coefficient of variation (CV), misalignment, inter-letter space, inter-word space, and ratio of inter-letter space to inter-word space. Children were also administered traditional handwriting and visuomotor tests. Digital variables from image processing were correlated with these previous tests. Using these correlations, we established a three-point scoring system that computed test scores for each variable. We analyzed inter-rater reliability between the computer rater and human rater and test-retest reliability between the first and second performances. The validity was examined by analyzing the relationship between the Korean Handwriting Assessment and previous handwriting and visuomotor tests. We suggested the Korean Handwriting Assessment to measure size, size consistency, misalignment, inter-letter space, inter-word space, and space ratio using digital image processing. This Korean Handwriting Assessment tool proved to have reliability and validity. It is expected to be useful for assessing children's handwriting.

• Speech Sciences
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• v.2
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• pp.159-172
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• 1997

This paper proposes a prosodic representation system of the Kyungnam dialect of Korean, based on the ToBI system. In this system, diverse intonation patterns are transcribed on the four parallel tiers: a tone tier, a break index tier, an orthographic tier, and a miscellaneous tier. The tone tier employs pitch accents, phrase accents, and boundary tones marked with diacritics in order to represent various pitch events. The break index tier uses five break indices, numbered from 0 to 4, in order to represent degrees of connectiveness in speech by associating each inter-word position with a break index. In this, each break index represents a boundary of some kind of constituent. This system can contribute not only to a more detailed theory connecting prosody, syntax, and intonation, but also to current text-to-speech synthesis approaches, speech recognition, and other quantitative computational modellings.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.199-208
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• 2022

Korean is an agglutinative language, and one or more morphemes are combined to form a single word. Part-of-speech tagging method separates each morpheme from a word and attaches a part-of-speech tag. In this study, we propose a new Korean part-of-speech tagging method based on the Head-Tail tokenization technique that divides a word into a lexical morpheme part and a grammatical morpheme part without decomposing compound words. In this method, the Head-Tail is divided by the syllable boundary without restoring irregular deformation or abbreviated syllables. Korean part-of-speech tagger was implemented using the Head-Tail tokenization and deep learning technique. In order to solve the problem that a large number of complex tags are generated due to the segmented tags and the tagging accuracy is low, we reduced the number of tags to a complex tag composed of large classification tags, and as a result, we improved the tagging accuracy. The performance of the Head-Tail part-of-speech tagger was experimented by using BERT, syllable bigram, and subword bigram embedding, and both syllable bigram and subword bigram embedding showed improvement in performance compared to general BERT. Part-of-speech tagging was performed by integrating the Head-Tail tokenization model and the simplified part-of-speech tagging model, achieving 98.99% word unit accuracy and 99.08% token unit accuracy. As a result of the experiment, it was found that the performance of part-of-speech tagging improved when the maximum token length was limited to twice the number of words.

• Korean Journal of Cognitive Science
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• v.34 no.4
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• pp.315-347
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• 2023

This study aimed to investigate the semantic preview effect in the parafoveal processing of words that are presented in advance in the parafoveal area ahead of the fixation point, benefiting word processing in the fovea. Using the boundary technique in eye-tracking experiments, 25 Chinese-Korean bilinguals, whose native language is Chinese, were presented with 96 sentences that contained a mix of Chinese and Korean, where Korean words were associated with Chinese characters semantically. The study aimed to determine whether a semantic preview effect could be extracted in reading. The experimental sentences were divided into four conditions: the same Korean native word condition (e.g., "나라" meaning "country"), the same Korean word with semantic equivalent in Chinese condition (e.g., "국가" meaning "country"), the same Chinese condition with semantic equivalent in Korean (e.g., "国家" meaning "country"), and the unrelated Chinese condition to the target word (e.g., "围裙" meaning "apron"). The results showed a preview effect in both the Korean word and Chinese word conditions, with a larger preview effect observed in the Chinese word condition compared to the Korean word condition.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.26-32
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• 1996

In this paper we make a rule of pitch variation for a natural synthetic female voice. Intonation phrase, which is the basic unit the rule is applied to, mostly consists of a syllable or syllables. The pitch values of the first, second, and final syllables make up the pitch contour of the intonation phrase. Those of the first and second syllable are determined by the initial consonants of the respective syllables, and that of the final syllable by the type of the function word. There are two kinds of boundaries between intonation phrases. One is a boundary with pause, and the other is a boundary without pause. The pitch contour of the intonation phrase with the boundary phenomena determines the pitch pattern of a sentence.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.441-448
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• 2019

Previous researches on automatic spacing of Korean sentences has been researched to correct spacing errors by using n-gram based statistical techniques or morpheme analyzer to insert blanks in the word boundary. In this paper, we propose an end-to-end automatic word spacing by using deep neural network. Automatic word spacing problem could be defined as a tag classification problem in unit of syllable other than word. For contextual representation between syllables, Bi-LSTM encodes the dependency relationship between syllables into a fixed-length vector of continuous vector space using forward and backward LSTM cell. In order to conduct automatic word spacing of Korean sentences, after a fixed-length contextual vector by Bi-LSTM is classified into auto-spacing tag(B or I), the blank is inserted in the front of B tag. For tag classification method, we compose three types of classification neural networks. One is feedforward neural network, another is neural network language model and the other is linear-chain CRF. To compare our models, we measure the performance of automatic word spacing depending on the three of classification networks. linear-chain CRF of them used as classification neural network shows better performance than other models. We used KCC150 corpus as a training and testing data.

• Speech Sciences
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• v.15 no.4
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• pp.43-60
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• 2008

Instrumental studies (e.g., aerodynamic, EPG, and EMMA) have shown that the first of two stops in sequence can be articulatorily reduced in time and space sometimes; either gradient or categorical. The current EMMA study aims to examine possible factors_linguistic (e.g., speech rate, word boundary, and prosodic boundary) and paralinguistic (e.g., natural context and repetition)_to induce gradient reduction of $C_1$ in /pk/ cluster sequences. EMMA data are collected from five Seoul-Korean speakers. The results show that gradient reduction of lip aperture seldom occurs, being quite restricted both in speaker frequency and in token frequency. The results also suggest that the place assimilation is not a lexical process, implying that speakers have not fully developed this process to be phonologized in the abstract level.

• Korean Institute of Interior Design Journal
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• v.27 no.3
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• pp.108-115
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• 2018

The atmosphere is a popular word in everyday life. There is often an atmosphere when we enter a particular place. As if to say, The mood is perceived as an emotional and subjective word. Atmosphere is subjective and there are different feelings, but there are definitely certain feelings that people can relate to. The researcher examines the question in the paper and analyzes how the atmosphere in the space could be explained. So I will research about $B{\ddot{o}}hme^{\prime}s$ aesthetics which is called atmosphere. and analysis how his atmosphere is applied in nowadays art. So this study has two purposes. First is the notion of the atmosphere, not the atmosphere of rational perspective, it's about emotional and perceptual experiences. Therefore a connection about audience and arts is the most important focus in atmosphere. So the other purpose is Olafur Eliasson's Atmosphere. he is an artist about this perception. His work requires spectator intervention and participation to make it a perfect art. There is also a element in Eliasson's philosophy, in which the perceptual experiences of visitor's relationship between the work and the viewer, and eliminates the boundary as a perceptual expression.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2012-2030
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• 2021

Named Entity Recognition (NER) is used to identify entity nouns in the corpus such as Location, Person and Organization, etc. NER is also an important basic of research in various natural language fields. The processing of Chinese NER has some unique difficulties, for example, there is no obvious segmentation boundary between each Chinese character in a Chinese sentence. The Chinese NER task is often combined with Chinese word segmentation, and so on. In response to these problems, we summarize the recognition methods of Chinese NER. In this review, we first introduce the sequence labeling system and evaluation metrics of NER. Then, we divide Chinese NER methods into rule-based methods, statistics-based machine learning methods and deep learning-based methods. Subsequently, we analyze in detail the model framework based on deep learning and the typical Chinese NER methods. Finally, we put forward the current challenges and future research directions of Chinese NER technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.