• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.7-10
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• 2000

Studies of prosody and sentence processing have demonstrated that prosodic phrasing can exhibit strong effects on processing decisions in English. In this paper, we tested Korean sentence fragments containing syntactically ambiguous Adj-N1-N2 strings in a cross-modal naming task. Four accentual phrasing patterns were tested: (a) the default phrasing pattern, in which each word forms an accentual phrase; (b) a phrasing biased toward N1 modification; (c) a phrasing biased toward complex-NP modification; and (d) a phrasing used with adjective focus. Patterns (b) and (c) are disambiguating phrasings; the other two are commonly found with both interpretations and are thus ambiguous. The results showed that the naming time of items produced in the prosody contradicting the semantic grouping is significantly longer than that produced in either default or supporting prosody, We claim that, as in English, prosodic information in Korean is parsed into a well-formed prosodic representation during the early stages of processing. The partially constructed prosodic representation produces incremental effects on syntactic and semantic processing decisions and is retained in memory to influence reanalysis decisions.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.149-156
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• 2015

In this paper, we propose a Korean sentence symbol preprocessor for a SSML (speech synthesis markup language) supported speech synthesis system in order to improve the quality of the synthesized result. After the analysis of Korean Wikipedia documents, we propose 8 categories for the meaning of sentence symbols and 11 regular expression for the classification of each category. After the development of a Korean sentence symbol preprocess system we archived 56% of precision and 71.45% of recall ratio for 63,000 sentences.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.829-836
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• 2003

In this paper, we propose a stochastic model for sentence speech understanding using dictionary and thesaurus. The proposed model extracts words from an input speech or text into a sentence. A computer is sellected category of dictionary database compared the word extracting from the input sentence calculating a probability value to the compare results from stochastic model. At this time, computer read out upper dictionary information from the upper dictionary searching and extracting word compared input sentence caluclating value to the compare results from stochastic model. We compare adding the first and second probability value from the dictionary searching and the upper dictionary searching with threshold probability that we measure the sentence understanding rate. We evaluated the performance of the sentence speech understanding system by applying twenty questions game. As the experiment results, we got sentence speech understanding accuracy of 79.8%. In this case, probability ($\alpha$) of high level word is 0.9 and threshold probability ($\beta$) is 0.38.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.691-696
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• 2005

In this paper, we present a pilot system that tn compress a Korean sentence automatically using knowledge extracted from news articles and their headlines. A sot of compressed sentences can be presented as an abstraction of a document. As a compressed sentence is of headline-style, it could be easily displayed on small devices, such as mobile phones and other handhold devices. Our compressing system has shown to be promising through a preliminary experiment.

• English Language & Literature Teaching
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• v.18 no.2
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• pp.67-84
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• 2012

The present study investigated the effect of sentence translation as a production task on short-term and long-term retention of foreign vocabulary. 87 EFL university students at a beginning level, enrolled in reading class participated in the study. The study compared the performance of three groups on vocabulary recall: (1) Control group, (2) Translation group, and (3) Copy group. During the treatment sessions, translation group translated L1 sentences into English, while copy group simply copied given English sentences with each target word. Results of the immediate test were collected each week from week 2 to week 5 and analyzed by one-way ANOVA. Results revealed that regarding short-term vocabulary retention, participants in rote-copy condition outperformed those in translation group. Four weeks later a delayed test was administered to measure long-term vocabulary retention. In contrast, the results of two-way repeated measures ANOVA showed that long-term vocabulary retention of translation group was significantly greater than copy group. The findings suggest that although sentence translation is rather challenging to low-level learners, it may facilitate long-term retention of new vocabulary given the more elaborate and deeper processing the task entails.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.107-116
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• 2004

This paper introduces ISAAC (An Interface for Sentence Analysis & Abstraction with Cogitation) which provides an integrated user interface for sentence analysis. Into ISAAC, the various linguistic tools and resources are integrated. They are necessary for sentence analysis. Most of the tools and resources for sentence analysis are developed and accumulated independently. In the sentence analyzing with these tools and resources, it is difficult for sentence analyst to manage and control information which is taken on each step. In this respect, we have integrated the usable tools and resources, and made ISAAC to provide the consistent user oriented interface to each function. We have been able to divide sentence analysis process Into 14 steps. In ISAAC, these steps are processed by four individual modules $\cicled1$syntactic analysis of sentence,$\cicled2$retrieval of a root word,$\cicled3$searching category information in Roget s Thesaurus, and $\cicled4$searching category information in OfN(Ontology for Narratives). Therefore, in case of sentence analysis with ISAAC, the process of total 14 steps falls into 4 steps. This means that it is able to improve the performance of sentence analyst to the extent 3.5 times or more. Furthermore, ISAAC undertaking tedious transcription needed to process each step, we expect that ISAAC can help the analyst to maintain the accuracy of sentence analysis.

• Phonetics and Speech Sciences
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• v.2 no.1
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• pp.33-39
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• 2010

This study investigates the effect of pitch range reset in Korean listeners' processing of syntactically ambiguous participle structures. Unlike Japanese and English,in Korean, the downtrend or the reset of pitch range does not consistently differentiate Accentual Phrases (AP), a lower level of phrasing, from Intonational Phrases (IP), a higher level of phrasing. Therefore, we explore Korean listeners' comprehension patterns for syntactically ambiguous speech strings varying in 1) the relative height of F0 peaks across prosodic units, and 2) the types of prosodic phrasing, to see whether pitch range reset informs the recovery of syntactic structure even though it is not reflected in the intonational hierarchy in Korean. The results show that the hierarchical level of prosodic phrasing affects the parsing pattern of syntactic ambiguity. The pitch range reset also cued the location of syntactic boundaries, but this effect was confined to phrases across AP.

• Proceedings of the Korean Society for Language and Information Conference
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• 1998.02a
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• pp.316-327
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• 1998

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.805-817
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• 2017

Cross-lingual query expansion is usually based on the relationship among monolingual words. Bilingual comparable corpus contains relationships among bilingual words. Therefore, this paper proposes a method based on these relationships to conduct query expansion. First, the word vectors which characterize the bilingual words are trained using Chinese and Thai bilingual comparable corpus. Then, the correlation between Chinese query words and Thai words are computed based on these word vectors, followed with selecting the Thai candidate expansion terms via the correlative value. Then, multi-group Thai query expansion sentences are built by the Thai candidate expansion words based on Chinese query sentence. Finally, we can get the optimal sentence using the Chinese and Thai query expansion method, and perform the Thai query expansion. Experiment results show that the cross-lingual query expansion method we proposed can effectively improve the accuracy of Chinese and Thai cross-language information retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2718-2731
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• 2023

This paper presents a method of using syntax and shallow semantic analysis for Vietnamese question generation (QG). Specifically, our proposed technique concentrates on investigating both the syntactic and shallow semantic structure of each sentence. The main goal of our method is to generate questions from a single sentence. These generated questions are known as factoid questions which require short, fact-based answers. In general, syntax-based analysis is one of the most popular approaches within the QG field, but it requires linguistic expert knowledge as well as a deep understanding of syntax rules in the Vietnamese language. It is thus considered a high-cost and inefficient solution due to the requirement of significant human effort to achieve qualified syntax rules. To deal with this problem, we collected the syntax rules in Vietnamese from a Vietnamese language textbook. Moreover, we also used different natural language processing (NLP) techniques to analyze Vietnamese shallow syntax and semantics for the QG task. These techniques include: sentence segmentation, word segmentation, part of speech, chunking, dependency parsing, and named entity recognition. We used human evaluation to assess the credibility of our model, which means we manually generated questions from the corpus, and then compared them with the generated questions. The empirical evidence demonstrates that our proposed technique has significant performance, in which the generated questions are very similar to those which are created by humans.