• 인지과학
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• 제24권4호
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• pp.339-363
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• 2013

습득연령효과는 연령 초기에 습득된 단어가 후기에 습득된 단어에 비해 효율적으로 처리되는 현상이다. 습득연령은 단어빈도와 함께 단어처리과정의 주요한 변인으로 간주되고 있다. 본 연구는 한국어/한글 단어재인에서 습득연령효과를 검토하였다. 실험 1에서는 단어명명과제와 어휘판단과제에서 습득연령효과를 검토하였다. 그 결과, 과제유형과 습득연령 간의 상호작용을 관찰하였다. 습득연령효과는 단어명명과제에서는 나타나지 않았고 어휘판단과제에서만 유의하게 나타났다. 실험 2에서는 어휘판단과제를 사용하여 습득연령과 단어빈도의 관계를 검토하였다. 그 결과, 습득연령과 단어빈도는 각각 유의한 변인으로 드러났다. 후기습득 단어에 비해 초기습득 단어의 어휘 판단 수행이 우수했으며, 저빈도 단어에 비해 고빈도 단어의 어휘 판단 수행이 우수했다. 두 변인의 독립적 효과는 확인했으나, 둘 간의 상호작용은 없었다. 실험 3에서는 음 변화가 일어나는 단어 조건과 음 변화가 일어나지 않는 단어 조건에서 습득연령효과를 검토하였다. 그 결과, 습득연령효과는 두 조건에서 유사하게 나타났으며 두 조건 간 차이는 없었다. 본 연구 결과에 대해 여러 가설들을 비교 논의하였다.

• 한국언어정보학회지:언어와정보
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• 제10권1호
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• pp.21-46
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• 2006

This study proposes a Word Sense Disambiguation (WSD) algorithm, based on concept learning with special emphasis on statistically meaningful lowest frequency words. Previous works on WSD typically make use of frequency of collocation and its probability. Such probability based WSD approaches tend to ignore the lowest frequency words which could be meaningful in the context. In this paper, we show an algorithm to extract and make use of the meaningful lowest frequency words in WSD. Learning method is adopted from the Find-Specific algorithm of Mitchell (1997), according to which the search proceeds from the specific predefined hypothetical spaces to the general ones. In our model, this algorithm is used to find contexts with the most specific classifiers and then moves to the more general ones. We build up small seed data and apply those data to the relatively large test data. Following the algorithm in Yarowsky (1995), the classified test data are exhaustively included in the seed data, thus expanding the seed data. However, this might result in lots of noise in the seed data. Thus we introduce the 'maximum a posterior hypothesis' based on the Bayes' assumption to validate the noise status of the new seed data. We use the Naive Bayes Classifier and prove that the application of Find-Specific algorithm enhances the correctness of WSD.

• 대한음성학회지:말소리
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• 제60호
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• pp.29-45
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• 2006

We investigated whether the first syllable plays an important role in lexical access in Korean visual word recognition. To do so, one lexical decision task (LDT) and two form primed LDT experiments examined the nature of the syllabic neighborhood effect. In Experiment 1, the syllabic neighborhood density and the syllabic neighborhood frequency was manipulated. The results showed that lexical decision latencies were only influenced by the syllabic neighborhood frequency. The purpose of experiment 2 was to confirm the results of experiment 1 with form-primed LDT task. The lexical decision latency was slower in form-related condition compared to form-unrelated condition. The effect of syllabic neighborhood density was significant only in form-related condition. This means that the first syllable plays an important role in the sub-lexical process. In Experiment 3, we conducted another form-primed LDT task manipulating the number of syllabic neighbors in words with higher frequency neighborhood. The interaction of syllabic neighborhood density and form relation was significant. This result confirmed that the words with higher frequency neighborhood are more inhibited by neighbors sharing the first syllable than words with no higher frequency neighborhood in the lexical level. These findings suggest that the first syllable is the unit of neighborhood and the unit of representation in sub-lexical representation is syllable in Korea.

• 한국인지과학회:학술대회논문집
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• 한국인지과학회 2002년도 춘계학술대회
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• pp.111-116
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• 2002

The regularity effect for printed word recognition and naming depends on ambiguities between single letters (small grain-size) and their phonemic values. As a given word is repeated and becomes more familiar, letter-aggregate size (grain-size) is predicted to increase, thereby decreasing the ambiguity between spelling pattern and phonological representation and, therefore, decreasing the regularity effect. Lexical decision and naming tasks studied the effect of repetition on the regularity effect for words. The familiarity of a word from was manipulated by presenting low and high frequency words as well as by presenting half the stimuli in mixed upper- and lowercase letters (an unfamiliar form) and half in uniform case. In lexical decision, the regularity effect was initially strong for low frequency words but became null after two presentations; in naming it was also initially strong but was merely reduced (although still substantial) after three repetitions. Mixed case words were recognized and named more slowly and tended to show stronger regularity effects. The results were consistent with the primary hypothesis that familiar word forms are read faster because they are processed at a larger grain-size, which requires fewer operations to achieve lexical selection. Results are discussed in terms of a neurobiological model of word recognition based on brain imaging studies.

• 한국융합학회논문지
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• 제12권8호
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• pp.1-11
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• 2021

본 연구의 목적은 '복압성 요실금'을 키워드로 검색된 연구들의 경향과 특성을 단어 빈도를 통해 분석하고, 워드 임베딩을 사용하여 그 관계를 모델링 하고자 하였다. 의학 서지 데이터베이스인 MEDLINE에 등록되어 있는 복압성 요실금 연구 9,868개 논문들의 초록 문자 데이터를 Python 프로그램을 이용하여 추출하였다. 그런 다음 빈도 분석을 통해 10개의 키워드를 선택하였다. 키워드 관련 단어들의 유사도는 Word2Vec 머신러닝 알고리즘으로 분석하였다. 그리고, t-SNE 기법을 사용하여 단어의 위치와 거리가 시각화하였고, 이에 따라 그룹을 분류하여 이를 분석하였다. 복압성 요실금과 관련된 연구는 1980년대 이후 빠르게 증가했다. 키워드 분석을 통해 논문 초록에서 가장 많이 사용된 키워드는 '여성', '요도', '수술'로 나타났다. Word2Vec 모델링을 통해 복압성 요실금 관련 연구에서 주요 키워드들과 가장 높은 연관성을 나타내는 단어들에는 '여성', '절박', '증상' 등이 있었다. 그리고, t-SNE 기법을 통해 키워드와 관련 단어들은 복압성 요실금의 증상, 신체 기관의 해부학적 특성, 그리고 수술적 중재를 중심으로 하는 3개의 그룹으로 분류될 수 있었다. 본 연구는 초록을 구성하는 단어들의 키워드 빈도 분석 및 워드임베딩 방식을 이용하여 복압성 요실금 관련 연구들의 동향을 살펴본 최초의 연구이다. 본 연구의 결과는 향후 연구자들이 복압성 요실금 관련 연구 분야의 주제와 방향성을 선택하는 데 있어 기초자료로 활용될 수 있을 것이다.

• 한국문헌정보학회지
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• 제34권2호
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• pp.87-115
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• 2000

유사문장의 식별 및 통합을 위하여 문장의 구성성분, 품사, 절유형, 위치 등이 미치는 영향을 조사하고 유사도측정 공식과 통합방안을 모색하였다. 문법적 요인보다는 문장간에 일치하는 단어의 수가 유사성에 영향을 미치며 표제어와 기능절도 관여되었다. 문장간의 유사도 측정 공식은 설튼의 유사도 측정식과 코싸인계수를 혼합하여 사용하였다. 유사문장들의 통합에서 절들의 대체 방법을 사용하였는데 앞으로는 단어들의 대체 방법으로 전환하여야 할 것이다.

• 대한음성학회지:말소리
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• 제55권
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• pp.33-43
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• 2005

This paper investigates the word accent pattern of Cheju dialects in Korean and determines whether it varies according to the age as well as the word itself and where the speakers come from. On the basis on the theory of pitch accent, which was suggested by Koo(1993) and Jung(1965) for the Korean standard accent, the fundamental frequency of each syllable is measured. The syllable that has the highest frequency is labelled for 2, while the rests for 1. The results of the experiment are that the two syllabic words have 21 accent pattern, while the three syllabic words 121 pattern and the four syllabic words 1211. In addition to this characteristic of accent pattern in Cheju dialects, it is interesting that the older the speakers, the less accent pattern the utterance has as suggested above.

• 대한음성학회지:말소리
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• 제57호
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• pp.31-42
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• 2006

The purpose of this study is to observe how Korean learners perceive an English weak syllable in words containing WS syllable pattern. According to the automated discrimination task using E-Prime, the ratio of correct answer(%) and reaction time of the stimuli with same syllable patterns were respectively higher and faster than those with different syllable patterns. Specifically, in the stimuli with different syllable patterns, the frequency(familiarity) of stressed word succeeding weak syllable and whether the weak syllable had coda in it were two important factors in distinguishing between a word with and without weak syllable. Even though the high English proficiency Koreans had faster reaction time than the low English proficiency Koreans, all Korean learners had a difficulty in perceiving the weak syllable at the beginning of a word.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.401-403
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• 2019

In this paper, we propose a generative adversarial networks (GAN) based text-to-image generating method. In many natural language processing tasks, which word expressions are determined by their term frequency -inverse document frequency scores. Word2Vec is a type of neural network model that, in the case of an unlabeled corpus, produces a vector that expresses semantics for words in the corpus and an image is generated by GAN training according to the obtained vector. Thanks to the understanding of the word we can generate higher and more realistic images. Our GAN structure is based on deep convolution neural networks and pixel recurrent neural networks. Comparing the generated image with the real image, we get about 88% similarity on the Oxford-102 flowers dataset.

• 음성과학
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• 제14권1호
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• pp.105-119
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• 2007

The purpose of this study is to examine Korean students' production and perception of word-final stop voicing in light of their overseas experience. Subjects were English native speakers, Korean university students with residence experience in America, Korean university students without residence experience in America, and Korean elementary school students. They participated in both production and perception tests. Results showed that the students' production and perception with residence experience in America appeared quite similar to those of the English native speakers. In the production tests, we noticed somewhat different results in temporal and frequency features. The one-year residence in America had some influence on their frequency features, but not the temporal features in the word final stop production. That difference could be seen in the perception tests, too. We could not find any difference in the identification test of the final release environment between the Korean university students who had studied abroad and those who didn't. Rather the difference could be found in the cue influence test in both the final release and non-release environments.