• Journal of Korean language education
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• v.29 no.3
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• pp.25-53
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• 2018

This study examined the influence of lexical factors on verbal Eojeol recognition. To meet the goal, forty-five L2 Korean learners and twenty-two Korean native speakers took Eojeol decision tasks measured with the lexical factors such as 'number of strokes', 'number of consonants and vowels', 'number of syllables', 'number of morphemes', 'whole Eojeol frequency', 'root frequency', 'first-syllable-sharing frequency', and 'number of dictionary meanings.' As a result, 'whole Eojeol frequency' was the most effective factor to predict Eojeol recognition reaction time for native speakers and L2 learners, which supports the full-list model. Other lexical factors influencing Eojeol recognition reaction time in L2 learners were different following their proficiency level.

• Journal of the Korean Society of Tobacco Science
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• v.37 no.1
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• pp.8-17
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• 2015

The purpose of this study is to classify the tobacco names in the world, to investigate the regional distribution of the classified type, and to show origin of names according to the type. The names of tobacco used in this study was 50. The type of tobacco names was classified by the presence or absence of nasal sound(morn) on the first syllable, the Number of syllable, and the structure of consonants and vowels of tobacco names. Type I (Dambago) has the nasal sound on the first syllable. The proportion of Type I(Dambago) was 28%. And the rest(Type I~Type V ; 72%) has no nasal sound. Type II(Tabaco) has three syllables, and its proportion was 20%. Type III(Tabac) has the two syllables and the structure of T+vowels+B+vowels. And its proportion was 30%. Type IV(Tutun) has the two syllables and the structure of T+vowels+T+vowels. And its proportion was 12%. Type V(Duhan) has the two syllables and the structure of D+vowels+H(V)+vowels. And its proportion was 10%. The world's most widely distributed type was Type I(Dambago). regional distribution of the world's tobacco names were clustered by the type. 72% of Type I(Dambago) was distributed in Asia. The etymology of Type I(Dambago) was only 14% Tambaku and the other is not yet known. The etymology of Type I(Dambago) seems to be derived from the Haitian Tambaku(meaning a tobacco pipe). 88% of Type II(Tabaco) and III(Tabac) were distributed in Europe. The etymology of Type II(Tabaco) and Type III(Tabac) were 84% Spanish "Tabaco". 100% of Type IV(Tutun) and V(Duhan) were distributed in Europe. The etymology of Type IV(Tutun) and Type V(Duhan) were 100% Turkish tutun and duhan, respectively. This finding suggests that the etymology of Type I(Dambago) is certainly may be Haitian "Tambaku(meaning a tobacco pipe)".

• Annual Conference on Human and Language Technology
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• 1996.10a
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• pp.262-267
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• 1996

한국어 맞춤법 검사기는 문서내에서 발생되는 비표준어 오류, 띄어쓰기/붙여쓰기 오류, 조사/어미 오류, 외래어 오류, 철자 오류 등에 대해서 이에 적합한 대치어를 제시해 준다. 일반적으로 한국어의 맞춤법 오류 중 가장 빈번하게 발생되는 것이 띄어쓰기 오류이며, 이 중에서도 복합 명사에 대한 띄어쓰기 오류가 가장 많이 발생한다. 본 논문에서는 복합 명사에 대한 띄어쓰기 교정 방안으로 복합명사의 음절수에 따라 1개의 결과만을 출력하도록 하는 복합 명사 분리 방안을 제시하며, 또한 복합 명사 분리 시의 사전 참조 횟수를 줄이는 방법을 제안한다.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.629-632
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• 2000

In this paper, we studied on the phoneme classification for Korean speech recognition. In the case of making large vocabulary speech recognition system, it is better to use phoneme than syllable or word as recognition unit. And, In order to study the difference of speech recognition according to the number of phoneme as recognition unit, we used the speech toolkit of OGI in U.S.A as recognition system. The result showed that the performance of diphthong being unified was better than that of seperated diphthongs, and we required the better result when we used the biphone than when using mono-phone as recognition unit.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.11-22
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• 1994

For the conventional systme based on word, it is very difficult to enlarge the number of vocabulary. To cope with this problem, we must use more fundamental units of speech. For example, syllables and phonemes are such units, Korean speech consists of initial consonants, middle vowels and final consonants and has characteristic that we can obtain syllables from speech easily. In this paper, we show a speech recognition system with the advantage of the syllable characteristics peculiar to the Korean speech. The algorithm of recognition system is the Time Delay Neural Network. To recognize many recognition units, system consists of initial consonants, middle vowels, and final consonants recognition neural network. At first, our system recognizes initial consonants, middle vowels and final consonants. Then using this results, system recognizes isolated words. Through experiments, we got 85.12% recognition rate for 2735 data of initial consonants, 86.95% recognition rate for 3110 data of middle vowels, and 90.58% recognition rate for 1615 data of final consonants. And we got 71.2% recognition rate for 250 data of isolated words.

• The Journal of the Convergence on Culture Technology
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• v.2 no.4
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• pp.31-40
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• 2016

The hardware of the human body is given the life force by the sentence which is the physiological software that the program for cell activation by the electrical signal enters. The aim of this study is to create a better therapeutic environment for the human body that groaned with errors in the physiological and cognitive systems that are transmitted to neurons and neurons. The sentence program of the rated sijo, which is the software of the human body which has the function as a conductor to connect the emotions of joy, anger, sadness, and enthusiasm to the human mental system, can be connected to the neuron system of the human body, we tried to identify the principle of operating the motherboard of mind in humanities. Once these principles are identified, we can figure out how to minimize side effects and lead the body to a therapeutic program. The research found that there is a strong energy source that can operate the motherboard of the heart very quickly in the rated Sijo. This is because it is confirmed that new coding and re-coding of a number of rated sijo, or a new syllable of one syllable followed by the original syllable of the original syllable, are formed quickly and therapeutically.This has led to the possibility of literary therapy for mankind to upgrade the human psychic system in abundance through the function of the interaction between the sentence as a conductor that is synaptically connected to the human body and the mainboard of the mind attached to the human body without side effects in the future.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.213-232
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• 2005

The purpose of this study is to determine factors affecting text difficulty and to model objective formulas which measure readability scores. Some readability-related factors such as total number of letters, total number of syllables, total number of unique syllables, total number of sentences and total number of paragraphs were found through correlation analysis. Some regression equations with these factors as their variables were produced through regression analysis. A model estimating readability score from total number of unique syllables was a good formula, while a model with two factors, total number of unique syllables and new syllable occurrence ratio, was a better enhanced one. The readability score represents detailed level so we can recommend students read texts corresponding to their reading levels.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.62-67
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• 1999

In this paper, we investigates a reliable model of the Predictive Recurrent Neural Network for the speech recognition. Predictive Neural Networks are modeled by syllable units. For the given input syllable, then a model which gives the minimum prediction error is taken as the recognition result. The Predictive Neural Network which has the structure of recurrent network was composed to give the dynamic feature of the speech pattern into the network. We have compared with the recognition ability of the Recurrent Network proposed by Elman and Jordan. ETRI's SAMDORI has been used for the speech DB. In order to find a reliable model of neural networks, the changes of two recognition rates were compared one another in conditions of: (1) changing prediction order and the number of hidden units: and (2) accumulating previous values with self-loop coefficient in its context. The result shows that the optimum prediction order, the number of hidden units, and self-loop coefficient have differently responded according to the structure of neural network used. However, in general, the Jordan's recurrent network shows relatively higher recognition rate than Elman's. The effects of recognition rate on the self-loop coefficient were variable according to the structures of neural network and their values.

• The Journal of the Acoustical Society of Korea
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• v.17 no.2E
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• pp.26-30
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• 1998

In this paper, we compose neural network predictive HMM(NNPHMM) to provide the dynamic feature of the speech pattern for the HMM. The NNPHMM is the hybrid network of neura network and the HMM. The NNPHMM trained to predict the future vector, varies each time. It is used instead of the mean vector in the HMM. In the experiment, we compared the recognition abilities of the one hundred Korean syllables according to the variation of hidden layer, state number and prediction orders of the NNPHMM. The hidden layer of NNPHMM increased from 10 dimensions to 30 dimensions, the state number increased from 4 to 6 and the prediction orders increased from 10 dimensions to 30 dimension, the state number increased from 4 to 6 and the prediction orders increased from the second oder to the fourth order. The NNPHMM in the experiment is composed of multi-layer perceptron with one hidden layer and CMHMM. As a result of the experiment, the case of prediction order is the second, the average recognition rate increased 3.5% when the state number is changed from 4 to 5. The case of prediction order is the third, the recognition rate increased 4.0%, and the case of prediction order is fourth, the recognition rate increased 3.2%. But the recognition rate decreased when the state number is changed from 5 to 6.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.491-499
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• 2014

This paper studied the statistics such as the total number of syllables: the kinds of syllables: the frequency of syllables, the total number of eojeols, the kinds of eojeols(word phrases unique in Korean language), average length of eojeols and the frequency of eojeols in four different Korean textbooks for 7th-grade students. The results of the statistical survey are as follows: the number of syllables was 286,801; the kinds of Korean syllables were 1,350; the average frequency of syllables was 212.4; the number of eoieol was 109,393; the kinds of eoieol were 29,356; the average frequency of eojeol was 3.7; the average length of eojeols was 2.7 syllables, the longest one consist of 8 syllables.