• Asia Pacific Journal of Corpus Research
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• v.2 no.2
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• pp.43-48
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• 2021

The aim of this study is to analyze the trends of corpus driven research in Korean education. For this purpose, a total of 14 papers was searched online with the keywords including Korean corpus and Korean education. The data was categorized into three: vocabulary education, grammar education and corpus data construction methods. The analysis results suggest that the number of corpus studies in the field of Korean education is not large enough but continues to increase, especially in the research on data construction tools. This suggests there is a significant demand in corpus driven studies in Korean education field.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.127-136
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• 2020

This paper presents an environment for rule-based English-Korean machine translation system, which supports the translation domain adaptation and the continuous translation quality improvement. For the purposes, corpus is essential, from which necessary information for translation will be acquired. The environment consists of a corpus construction part and a translation knowledge extraction part. The corpus construction part crawls news articles from some newspaper sites. The extraction part builds the translation knowledge such as newly-created words, compound words, collocation information, distributional word representations, and so on. For the translation domain adaption, the corpus for the domain should be built and the translation knowledge should be constructed from the corpus. For the continuous improvement, corpus needs to be continuously expanded and the translation knowledge should be enhanced from the expanded corpus. The proposed web-based environment is expected to facilitate the tasks of domain adaptation and translation system improvement.

• MALSORI
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• no.46
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• pp.159-174
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• 2003

K-SEC (Korean-Spoken English Corpus) is a kind of speech database that is being under construction by the authors of this paper This article discusses the needs of the K-SEC from various academic disciplines and industrial circles, and it introduces the characteristics of the K-SEC design, its catalogues and contents of the recorded database, exemplifying what are being considered from both Korean and English languages' phonetics and phonologies. The K-SEC can be marked as a beginning of a parallel speech corpus, and it is suggested that a similar corpus should be enlarged for the future advancements of the experimental phonetics and the speech information technology.

• Language and Information
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• v.15 no.1
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• pp.13-29
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• 2011

Conditional sentences also can be formed by inversion of subject and auxiliary, but it happens only in a limited environment. This paper addresses grammatical constraints in conditional inversion and how they behave differently from the regular conditional clauses based on corpus investigations. Our corpus search reveals many different types of conditional inversion constructions, indicating the difficulties of deriving inverted conditionals from movement operations. In this paper, we provide a construction-based approach to the inverted conditional construction. The paper shows that the most optimal way of describing the general as well as idiosyncratic properties of the inverted conditional constructions is an account in the spirit of construction grammar in which a grammar is a repertory of constructions forming a network connected by links of inheritance.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.12-20
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• 2003

K-SEC(Korean-Spoken English Corpus) is a kind of speech database that is being under construction by the authors of this paper. This article discusses the needs of the K-SEC from various academic disciplines and industrial circles, and it introduces the characteristics of the K-SEC design, its catalogues and contents of the recorded database, exemplifying what are being considered from both Korean and English languages' phonetics and phonologies. The K-SEC can be marked as a beginning of a parallel speech corpus, and it is suggested that a similar corpus should be enlarged for the future advancements of the experimental phonetics and the speech information technology.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.29-38
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• 2012

In this paper, we propose a named entity and event annotation tool for cultural heritage information corpus construction. Focusing on time, location, person, and event suitable for cultural heritage information management, the annotator writes the named entities and events with the proposed tool. In order to easily annotate the named entities and the events, the proposed tool automatically annotates the location information such as the line number or the word number, and shows the corresponding string, formatted as both bold and italic, in the raw text. For the purpose of reducing the costs of the manual annotation, the proposed tool utilizes the patterns to automatically recognize the named entities. Considering the very little training corpus, the proposed tool extracts simple rule patterns. To avoid error propagation, the proposed patterns are extracted from the raw text without any additional process. Experimental results show that the proposed tool reduces more than half of the manual annotation costs.

• Asia Pacific Journal of Corpus Research
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• v.1 no.2
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• pp.41-56
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• 2020

This paper aims to investigate how word order interacts with cliticization in Sakizaya, a Formosan language. This paper looks into nominative and genitive case markers from a corpus-based approach. The data are collected from an online dictionary of Sakizaya, and they are classified into two word orders: nominative case marker preceding genitive case marker and vice versa. The data are also divided into three categories, according to the demarcation of the case markers, which include right, left, or no demarcation. The corpus includes 700 sentences in the construction of predicate + noun phrase + noun phrase. The results suggest that the two case markers tend to be parsed into the preceding word and show right demarcation. The results also reveal that there are type difference and distance effect of the case markers on the cliticization. Nominative case markers show more right demarcation than genitive case markers do in the corpus. Also, the closer the case markers are to the predicate, the more possible the case markers undergo cliticization.

• Journal of the Korean Society for information Management
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• v.15 no.3
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• pp.7-26
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• 1998

The large scale documents of the data repository are utilized to the diverse applications. In the cross-language information retrieval, if the words of a query contain polymorphic meanings, the system needs multilingual corpus to exactly translate to the target words. We constructed the financial comparable corpus, called KFCM(Korean Financial Corpus corresponding to MLCC Corpus), comparing to the MLCC Polylingual Documents which consisted with the 6 European languages. It is independently constructed under the DTD of MLCC comparable corpus, and can be utilized to the cross-language information retrieval. In this paper, we discussed about the application and construction procedures of KFCM which is public domain data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1505-1511
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• 2021

Pretrained models with high performance in various tasks within natural language processing have the advantage of learning the linguistic patterns of sentences using large corpus during the training, allowing each token in the input sentence to be represented with appropriate feature vectors. One of the methods of constructing a corpus required for a pre-trained model training is a collection method using web crawler. However, sentences that exist on web may contain unnecessary words in some or all of the sentences because they have various patterns. In this paper, we propose a dataset construction method for filtering sentences containing unnecessary words using neural network models for corpus collected from the web. As a result, we construct a dataset containing a total of 2,330 sentences. We also evaluated the performance of neural network models on the constructed dataset, and the BERT model showed the highest performance with an accuracy of 93.75%.

• Asia Pacific Journal of Corpus Research
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• v.4 no.1
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• pp.25-42
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• 2023

The number of studies on data-driven learning (DDL) has increased in recent years, and DDL's overall effectiveness as an L2 (second language) teaching methodology has been reported to be high. However, the degree of its effectiveness in grammar instruction, particularly for the goal of correcting errors in L2 writing, is still unclear. To provide guidelines for focused grammar instruction with DDL in the Japanese classroom setting, we aimed to identify the typical grammatical errors made by Japanese learners in the Cambridge Learner Corpus First Certificate in English (CLC FCE) dataset. The results revealed that three error types (nouns, articles, and prepositions) should be addressed in DDL grammar instruction for Japanese English as a foreign language (EFL) learners. In light of the findings, pedagogical implications and suggestions for future DDL research and practice are discussed.