• Korean Journal of Cognitive Science
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• v.10 no.2
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• pp.11-16
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• 1999

It is expected that some Josa/Eomi's are frequently used and others are not in the Korean documents. In this paper. we confirm it through the experiment and show that such information is very useful for Korean language processing. In case of Josa. most frequent 9 Josa's occupied 70% of total Josa's and 20. 32. 69 Josa's occupied 90%. 95%. and 99% respectively. Similarly, most frequent 10 numbers of Eomi's occupied 70% of total Eomi's and 33. 54. 117 Eomi's occupied 90%. 95%. and 99% respectively. We propose a dictionary construction method for Josa/Eomi dictionary that is classified by the frequency information. Furthermore. Josa/Eomi frequency results are very useful for the identification of unregistered morphemes and the disambiguation of lexical ambiguities.

• Annual Conference on Human and Language Technology
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• 1995.10a
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• pp.188-194
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• 1995

한글 문서에서는 일부 조사와 일부 어미가 자주 출현하며 그 외의 조사/어미는 출현 빈도가 낮을 것으로 추측되고 있다. 본 연구에서는 실험에 통해서 이러한 사실을 확인하고 자주 출현하는 통합형 조사와 어미의 빈도를 구하기 위하여 한국어 말뭉치에서 통합형 조사와 통합형 어미의 상대적 출현 빈도를 조사하였다. 통합형 조사의 상대적 출현 빈도를 조사한 결과 말뭉치의 분야에 따라 약간의 차이가 있으나 평균 상위 9개의 통합형 조사가 전체 조사의 70%를 차지하고 있으며 상위 20개, 32개, 69개의 통합형 조사가 각각 90%, 95%, 99%를 차지하고 있음을 확인하였다. 통합형 어말어미의 경우에는 상위 10개의 통합형 어말어미가 전체 어말어미의 70%를 차지하고 상위 33개, 54개, 117개의 통합형 어미가 각각 90%, 95%, 99%를 차지하고 있다. 본 논문에서는 조사, 어미의 상대적 출현 빈도에 따라 계층적으로 조사/어미 사진을 구성함으로써 형태소 분석 효율을 높이고 형태소 분석기가 다양한 응용 분야에 쉽게 적응할 수 있도록 하는 방법을 제안한다. 또한 통합형 조사, 어미의 상대적 출현 빈도는 미등록어 추정을 용이하게 하거나 형태론적 모호성을 해결할 때에도 유용하게 활용될 수 있음을 보인다.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1294-1306
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• 1996

To achieve high compression ratio for Hangul texts, in this paper two text compression algorithms which use the structural feature of Hangul, the frequency of postpositional words, are proposed. The performances of these proposed algorithms are also compared with previous text compression algorithms. The proposed compression algorithms named HLZ77 and HLZW come out from the modification of previous algorithms LZ77 and :ZW, respectively. The major distinction of the proposed ones is that the proposed algorithms use the fixed dictionary of selected postpositional words that appear most frequently in Hangul texts. The performances of HLZ77 and HLZW also are compared with those of LZ77 and LZW, respectively, with respect to the compression ratio. According to the result of performance study, the proposed algorithms are better than the previous algorithms for descriptive Hangul text snce the structural feature of Hangul is helpful to achievement of high compression ratio.

• Phonetics and Speech Sciences
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• v.12 no.1
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• pp.33-42
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• 2020

This study identified the substitution of /u/ for /o/ (e.g., pyəllo [pyəllu]) in Korean based on the speech corpus as a function of grammar items. Korean /o/ and /u/ share the vowel feature [+rounded], but are distinguished in terms of tongue height. However, researchers have reported that the merger of Korean /o/ and /u/ is in progress, making them indistinguishable. Thus, in this study, the frequency of the phonetic manifestation /u/ of the underlying form of /o/ for each grammar item was calculated in The Korean Corpus of Spontaneous Speech (Seoul Corpus 2015) which is a large corpus from a total of 40 speakers from Seoul or Gyeonggi-do. It was then confirmed that linking endings, particles, and adverbs ending with /o/ in the word-final position were substituted for /u/ approximately 50% of the stimuli, whereas, in nominal items, they were replaced at a frequency of less than 5%. The high rates of substitution were the special particle "-do[du]" (59.6%) and the linking ending "-go[gu]" (43.5%) among high-frequency items. Observing Korean pronunciation in real life provides deep insight into its theoretical implications in terms of speech recognition.

• Korean Journal of Cognitive Science
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• v.16 no.2
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• pp.123-140
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• 2005

The purpose of this paper is to examine the frequency and usage of sentence patterns appearing in electronic dictionaries used in Korean language education in order to design an automatic sentence patterns checking. First, the concept of sentence patterns is defined and it is classified into sentence structure patterns and sentencial expression patterns. Sentence structure patterns and sentencial expression patterns are analyzed how they are expressed in the Korean Learner's Corpus. learner's Corpus is built into the Standard Corpus, which all Korean Learners must learn, and the Errors Corpus made by learners. From these research, we will find out how frequently the Sentential Patterns are being used in the Standard Corpus which has been made of Korean Texts and how the Sentential Pattern are being used in the Errors Corpus which were constructed from Korean learner's writings. Finally, having described the Sentential Patterns on the Sentential Electric Dictionary, we determine the optimum speed in the search for the Sentential Pattern.