• Title/Summary/Keyword: Corpus statistics

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The Study Of Lexical Statistics Analysis For Elementary School Textbook : Focusing On Comparing The SEJONG Corpus In Korean (초등학교 교과서의 어휘 통계 분석 연구 : 한국어 세종 코퍼스와의 비교를 중심으로)

  • Yu, Wonhee;Lim, Heuiseok
    • The Journal of Korean Association of Computer Education
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    • v.18 no.1
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    • pp.99-108
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    • 2015
  • In this paper, we build a primary school textbook corpus and a statistical analysis was performed with respect to the vocabulary found in elementary textbooks. also We performed the Spearman's correlation coefficient in order to explore whether similar elementary textbooks in general life used vocabulary. the result of this study shows that corpus building in the form of elementary school textbooks and actual examples. then numerically shown correlation of the elementary textbooks and general corpus.

A Study on the Diachronic Evolution of Ancient Chinese Vocabulary Based on a Large-Scale Rough Annotated Corpus

  • Yuan, Yiguo;Li, Bin
    • Asia Pacific Journal of Corpus Research
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    • v.2 no.2
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    • pp.31-41
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    • 2021
  • This paper makes a quantitative analysis of the diachronic evolution of ancient Chinese vocabulary by constructing and counting a large-scale rough annotated corpus. The texts from Si Ku Quan Shu (a collection of Chinese ancient books) are automatically segmented to obtain ancient Chinese vocabulary with time information, which is used to the statistics on word frequency, standardized type/token ratio and proportion of monosyllabic words and dissyllabic words. Through data analysis, this study has the following four findings. Firstly, the high-frequency words in ancient Chinese are stable to a certain extent. Secondly, there is no obvious dissyllabic trend in ancient Chinese vocabulary. Moreover, the Northern and Southern Dynasties (420-589 AD) and Yuan Dynasty (1271-1368 AD) are probably the two periods with the most abundant vocabulary in ancient Chinese. Finally, the unique words with high frequency in each dynasty are mainly official titles with real power. These findings break away from qualitative methods used in traditional researches on Chinese language history and instead uses quantitative methods to draw macroscopic conclusions from large-scale corpus.

Enhancement of a language model using two separate corpora of distinct characteristics

  • Cho, Sehyeong;Chung, Tae-Sun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.3
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    • pp.357-362
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    • 2004
  • Language models are essential in predicting the next word in a spoken sentence, thereby enhancing the speech recognition accuracy, among other things. However, spoken language domains are too numerous, and therefore developers suffer from the lack of corpora with sufficient sizes. This paper proposes a method of combining two n-gram language models, one constructed from a very small corpus of the right domain of interest, the other constructed from a large but less adequate corpus, resulting in a significantly enhanced language model. This method is based on the observation that a small corpus from the right domain has high quality n-grams but has serious sparseness problem, while a large corpus from a different domain has more n-gram statistics but incorrectly biased. With our approach, two n-gram statistics are combined by extending the idea of Katz's backoff and therefore is called a dual-source backoff. We ran experiments with 3-gram language models constructed from newspaper corpora of several million to tens of million words together with models from smaller broadcast news corpora. The target domain was broadcast news. We obtained significant improvement (30%) by incorporating a small corpus around one thirtieth size of the newspaper corpus.

Judging Translated Web Document & Constructing Bilingual Corpus (웹 번역문서 판별과 병렬 말뭉치 구축)

  • Jee-hyung, Kim;Yill-byung, Lee
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10a
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    • pp.787-789
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    • 2004
  • People frequently feel the need of a general searching tool that frees from language barrier when they find information through the internet. Therefore, it is necessary to have a multilingual parallel corpus to search with a word that includes a search keyword and has a corresponding word in another language, Multilingual parallel corpus can be built and reused effectively through the several processes which are judgment of the web documents, sentence alignment and word alignment. To build a multilingual parallel corpus, multi-lingual dictionary should be constructed in each language and HTML should be simplified. And by understanding the meaning and the statistics of document structure, judgment on translated web documents will be made and the searched web pages will be aligned in sentence unit.

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On the statistics of Korean Phonetic Dictionary - Basic Survey to make corpus of Korean Speech DB - (발음사전 표제어중의 음소의 통계적 성질-음성 DB용 단어선정을 위하여-)

  • Lee, Y.J.;Kim, K.T.;Jo, C.W.;Rhee, T.W.
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1606-1609
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    • 1987
  • Statistical information about spoken Korean was obtained. The data are the results of analyzing the Korean phonetic dictionary. This is one of the basic survey to make phoneme ballanced corpus of Korean Speech Data Base (KSDB).

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Corpus-Based Ambiguity-Driven Learning of Context- Dependent Lexical Rules for Part-of-Speech Tagging (품사태킹을 위한 어휘문맥 의존규칙의 말뭉치기반 중의성주도 학습)

  • 이상주;류원호;김진동;임해창
    • Journal of KIISE:Software and Applications
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    • v.26 no.1
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    • pp.178-178
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    • 1999
  • Most stochastic taggers can not resolve some morphological ambiguities that can be resolved only by referring to lexical contexts because they use only contextual probabilities based ontag n-grams and lexical probabilities. Existing lexical rules are effective for resolving such ambiguitiesbecause they can refer to lexical contexts. However, they have two limitations. One is that humanexperts tend to make erroneous rules because they are deterministic rules. Another is that it is hardand time-consuming to acquire rules because they should be manually acquired. In this paper, wepropose context-dependent lexical rules, which are lexical rules based on the statistics of a taggedcorpus, and an ambiguity-driven teaming method, which is the method of automatically acquiring theproposed rules from a tagged corpus. By using the proposed rules, the proposed tagger can partiallyannotate an unseen corpus with high accuracy because it is a kind of memorizing tagger that canannotate a training corpus with 100% accuracy. So, the proposed tagger is useful to improve theaccuracy of a stochastic tagger. And also, it is effectively used for detecting and correcting taggingerrors in a manually tagged corpus. Moreover, the experimental results show that the proposed methodis also effective for English part-of-speech tagging.

The fundamental frequency (f0) distribution of American speakers in a spontaneous speech corpus

  • Byunggon Yang
    • Phonetics and Speech Sciences
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    • v.16 no.1
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    • pp.11-16
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    • 2024
  • The fundamental frequency (f0), representing an acoustic measure of vocal fold vibration, serves as an indicator of the speaker's emotional state and language-specific pattern in daily conversations. This study aimed to examine the f0 distribution in an English corpus of spontaneous speech, establishing normative data for American speakers. The corpus involved 40 participants engaging in free discussions on daily activities and personal viewpoints. Using Praat, f0 values were collected filtering outliers after removing nonspeech sounds and interviewer voices. Statistical analyses were performed with R. Results indicated a median f0 value of 145 Hz for all the speakers. The f0 values for all speakers exhibited a right-skewed, pointy distribution within a frequency range of 216 Hz from 75 Hz to 339 Hz. The female f0 range was wider than that of males, with a median of 113 Hz for males and 181 Hz for females. This spontaneous speech corpus provides valuable insights for linguists into f0 variation among individuals or groups in a language. Further research is encouraged to develop analytical and statistical measures for establishing reliable f0 standards for the general population.

Data Mining Research on Maehwado Painting Poetry in the Early Joseon Dynasty

  • Haeyoung Park;Younghoon An
    • Journal of Information Processing Systems
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    • v.19 no.4
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    • pp.474-482
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    • 2023
  • Data mining is a technique for extracting valuable information from vast amounts of data by analyzing statistical and mathematical operations, rules, and relationships. In this study, we employed data mining technology to analyze the data concerning the painting poetry of Maehwado (plum blossom paintings) from the early Joseon Dynasty. The data was extracted from the Hanguk Munjip Chonggan (Korean Literary Collections in Classical Chinese) in the Hanguk Gojeon Jonghap database (Korea Classics DB). Using computer information processing techniques, we carried out web scraping and classification of the painting poetry from the Hanguk Munjip Chonggan. Subsequently, we narrowed down our focus to the painting poetry specifically related to Maehwado in the early Joseon Dynasty. Based on this, refined dataset, we conducted an in-depth analysis and interpretation of the text data at the syllable corpus level. As a result, we found a direct correlation between the corpus statistics for each syllable in Maehwado painting poetry and the symbolic meaning of plum blossoms.

Ambiguity Resolution in Chinese Word Segmentation

  • Maosong, Sun;T'sou, Benjamin-K.
    • Proceedings of the Korean Society for Language and Information Conference
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    • 1995.02a
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    • pp.121-126
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    • 1995
  • A new method for Chinese word segmentation named Conditional F'||'&'||'BMM (Forward and Backward Maximal Matching) which incorporates both bigram statistics (ie., mutual infonllation and difference of t-test between Chinese characters) and linguistic rules for ambiguity resolution is proposed in this paper The key characteristics of this model are the use of: (i) statistics which can be automatically derived from any raw corpus, (ii) a rule base for disambiguation with consistency and controlled size to be built up in a systematic way.

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The f0 distribution of Korean speakers in a spontaneous speech corpus

  • Yang, Byunggon
    • Phonetics and Speech Sciences
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    • v.13 no.3
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    • pp.31-37
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    • 2021
  • The fundamental frequency, or f0, is an important acoustic measure in the prosody of human speech. The current study examined the f0 distribution of a corpus of spontaneous speech in order to provide normative data for Korean speakers. The corpus consists of 40 speakers talking freely about their daily activities and their personal views. Praat scripts were created to collect f0 values, and a majority of obvious errors were corrected manually by watching and listening to the f0 contour on a narrow-band spectrogram. Statistical analyses of the f0 distribution were conducted using R. The results showed that the f0 values of all the Korean speakers were right-skewed, with a pointy distribution. The speakers produced spontaneous speech within a frequency range of 274 Hz (from 65 Hz to 339 Hz), excluding statistical outliers. The mode of the total f0 data was 102 Hz. The female f0 range, with a bimodal distribution, appeared wider than that of the male group. Regression analyses based on age and f0 values yielded negligible R-squared values. As the mode of an individual speaker could be predicted from the median, either the median or mode could serve as a good reference for the individual f0 range. Finally, an analysis of the continuous f0 points of intonational phrases revealed that the initial and final segments of the phrases yielded several f0 measurement errors. From these results, we conclude that an examination of a spontaneous speech corpus can provide linguists with useful measures to generalize acoustic properties of f0 variability in a language by an individual or groups. Further studies would be desirable of the use of statistical measures to secure reliable f0 values of individual speakers.