• Proceedings of the KSPS conference
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• 1996.10a
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• pp.432-434
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• 1996

The aim of this presentation is to show the structures and characteristics of English-Korean Machine Translator 'Trannie 96' 'Trannie 06' consists of five main engines and various types of dictionaries. With respect to the engines, the English sentences filtered by Pre-processor are tagged and parsed. After the conversion form English sentence structure to Korean one, 'Trannie 96' constructs Korean sentence. As for dictionaries, each engine has more than one optimized dictionaries. The algorithms employed by this machine is based on Linguistic theories, which make it possible for us to produce speedy and accurate translation.

• Annual Conference on Human and Language Technology
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• 1993.10a
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• pp.559-570
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• 1993

In this article we present a rapid development of a Korean to English translation system, by the help of general English generator, PENMAN. PENMAN is an English sentence generation system, of which input language is a language specially devised for sentence generation, named Sentence Planning Language(SPL). The language SPL has various features that are necessary for generating sentences, covering both syntactic and semantic features. In this development we integrated a Korean language parser based on dependency grammar and the English sentence generator PENMAN, bridging two systems through a converting module, which converts dependency structures produced by Korean parser into SPL for PENMAN.

• English Language & Literature Teaching
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• v.12 no.1
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• pp.103-129
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• 2006

This paper presents a case study of the effectiveness of debate class in promoting speaking skills of advanced learners. The researcher adopted English debate techniques in an English speaking class during four-week teacher training program and investigated how teachers responded to the new technique. Forty-five middle and high school teachers participated in the study and classroom observation, pre-survey, post-survey, and focus group interviews were used as the major research methods. The teacher pre-survey results presented that teachers prefer a conversation class where they can directly acquire proper sentence patterns and speaking strategies rather than spend time in performing communicative events. The results of the focus group interview and post-survey confirmed that a debate class can meet this specific teachers' needs. Most teachers responded positively to the debate classes since: 1) debate techniques are relatively new ideas to Korean teachers; 2) debate techniques require speed and accuracy in speech; thus teachers could learn to present their ideas logically and efficiently in a limited time through repeated argument exercises. The study result implies that debate technique can be an effective vehicle in an EFL context to promote advanced learners' logical thinking skills and logical English sentence structures.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.35-46
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• 2017

According to domestic and foreign research, one of the common characteristics of good teaching is a variety of class activities. To make 'Business Major English' a good class, the researcher used a variety of class activities such as professor explanation, group activities & presentation, vocabulary quizzes, reading comprehension, homework and test feedback. The participants were 39 junior students who took 'Business Major English' in 2015 and 2016. Data on student perception were gathered from questionnaires. The analysis of the data showed, first, that the class activity the students preferred the most was professor explanation. Second, the class activity which was the most helpful in understanding text content and English sentence structures was professor explanation. Third, there were not many students preferring group activities & presentation and the students found group activities & presentation the least helpful in understanding text content and English sentence structures. Given the results, this study implies that for English class activities, students' preferences and the help they perceive have a relation to the characteristics of a class and students' English proficiency.

• English Language & Literature Teaching
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• v.18 no.2
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• pp.21-44
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• 2012

This paper aims to discuss the effects of learning how to write English interrogative sentences. 122 students who participated in the study learned basic structural components of English questions and practiced writing questions by inversing the subject and the verb in a given declarative sentence. The participants were divided into two groups: Group 1 which was given a brief explanation of interrogative structures and practices, and Group 2 which was given the same explanation and practices in addition to an assignment for which they had to make one or two comprehension questions based on reading a passage. For the pre-tests and the post-tests, they took a TOEIC reading test with 40 questions and a structure test with 25 questions. The results of the tests show that both groups improved significantly in the two post-tests, benefiting from this learning method. However, the additional treatment for Group 2 did not seem to be highly effective. In the questionnaire survey, the participants think that the method of learning English questions has helped them better understand English grammar as well as interrogative structures. The participants were also divided into three different levels: high, intermediate, and low. The intermediate level group students benefited most from learning writing questions as the results of the post-test of the 25-questions test and the final exam of the course show.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.21-28
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• 2016

The performance of an English-Korean machine translation system depends heavily on its English parser. The parser in this paper is a part of the rule-based English-Korean MT system, which includes many syntactic rules and performs the chart-based parsing. The parser generates too many structures due to many syntactic rules, so much time and memory are required. The rule-based parser has difficulty in analyzing and translating the long sentences including the commas because they cause high parsing complexity. In this paper, we propose the 3-phase parsing method with sentence segmentation to efficiently translate the long sentences appearing in usual. Each phase of the syntactic analysis applies its own independent syntactic rules in order to reduce parsing complexity. For the purpose, we classify the syntactic rules into 3 classes and design the 3-phase parsing algorithm. Especially, the syntactic rules in the 3rd class are for the sentence structures composed with commas. We present the automatic rule acquisition method for 3rd class rules from the syntactic analysis of the corpus, with which we aim to continuously improve the coverage of the parsing. The experimental results shows that the proposed 3-phase parsing method is superior to the prior parsing method using only intra-sentence segmentation in terms of the parsing speed/memory efficiency with keeping the translation quality.

• Proceedings of the KSPS conference
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• 1997.07a
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• pp.81-91
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• 1997

This paper deals with the problems of English listening comprehension: the rate of understanding difference in positions and sentence structures, parts of speech easily missed to understand, English sounds only in English(not in Korean), confusion of sounds, unaccented prefixes and suffixes, polysemy, homonym, juncture, understanding as one word by two different words, and sound blending in a normal speed of connected speech. Bearing those in mind I taught Suwon University freshmen video English with the mixed idea of Peterson's bottom-up and top-down methods putting in a meaningful context with thought group rather than word to word understanding. As a consequence, their errors come: prepositions, conjunctions, unstressed prefixes and suffixes, -ing from the present progressives and so forth. Assignments to have students transcribe the TV commercials and the names of reporters or Korean related news from English broadcastings are of use and help.

• Speech Sciences
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• v.14 no.1
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• pp.21-35
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• 2007

This paper attempts to investigate phonetic substances of the stress patterns of English compounds and noun phrases, showing that the theoretically derived stress structures are not consistent with the accentual patterns in real utterances. Even though it has been long claimed that compounds have the stress pattern [1 3] and that noun phrases, [2 1] as in Chomsky & Halle (1968), their difference has not been yet explored empirically or phonetically. I present a phonetic experiment conducted to see if there is any difference along the tonal contours, mostly focusing on their pitch accent distribution. 36 different compounds and 36 different noun phrases included in carrier sentences were examined, and they were varied in position within a sentence. Results showed that various accentual patterns were produced, and among them, [H* X] predominantly occurs in all three positions in both compounds and noun phrases, whereas the patterns [X H*] and [X X] appear relatively more frequently in final position than in initial and medial position. Furthermore, the pattern [Ac + No], in which the preceding element is pitch-accented with no accent on the following one, is the major stress pattern in both compounds and noun phrases and in all three sentence positions. This suggests that there seems to be no difference in accentual patterns between compounds and noun phrases, which is not consistent with the hypothesis. The results are interpreted as saying that the preceding element alone tends to be prominent with no accent following it both in compounds and noun phrases, and that therefore, theoretically speculated phonological claims are not always phonetically supported.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.27-40
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• 2020

In this paper, we investigate the correlation between the amount of English sentences that Korean English learners (L2ers) are exposed to and their sentence processing patterns by examining what Long Short-Term Memory (LSTM) language models (LMs) can learn about implicit syntactic relationship: that is, the filler-gap dependency. The filler-gap dependency refers to a relationship between a (wh-)filler, which is a wh-phrase like 'what' or 'who' overtly in clause-peripheral position, and its gap in clause-internal position, which is an invisible, empty syntactic position to be filled by the (wh-)filler for proper interpretation. Here to implement L2ers' English learning, we build LSTM LMs that in turn learn a subset of the known restrictions on the filler-gap dependency from English sentences in the L2 corpus that L2ers can potentially encounter in their English learning. Examining LSTM LMs' behaviors on controlled sentences designed with the filler-gap dependency, we show the characteristics of L2ers' sentence processing using the information-theoretic metric of surprisal that quantifies violations of the filler-gap dependency or wh-licensing interaction effects. Furthermore, comparing L2ers' LMs with native speakers' LM in light of processing the filler-gap dependency, we not only note that in their sentence processing both L2ers' LM and native speakers' LM can track abstract syntactic structures involved in the filler-gap dependency, but also show using linear mixed-effects regression models that there exist significant differences between them in processing such a dependency.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.345-352
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• 2006

The practical English-Korean machine translation system should be able to translate long sentences quickly and accurately. The intra-sentence segmentation method has been proposed and contributed to speeding up the syntactic analysis. This paper proposes the syntactic category prediction method using decision trees for getting accurate parsing results. In parsing with segmentation, the segment is separately parsed and combined to generate the sentence structure. The syntactic category prediction would facilitate to select more accurate analysis structures after the partial parsing. Thus, we could improve the parsing accuracy by the prediction. We construct features for predicting syntactic categories from the parsed corpus of Wall Street Journal and generate decision trees. In the experiments, we show the performance comparisons with the predictions by human-built rules, trigram probability and neural networks. Also, we present how much the category prediction would contribute to improving the translation quality.