• 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.

• Korean Journal of Child Studies
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• v.35 no.2
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• pp.157-169
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• 2014

This study sought to explore the types of predictable pattern books are suitable for reading aloud, the differences between English and translated Korean picture books in terms of their characteristics of speakability and the meaning of sentences. This study investigated a total of 112 picture books. The predictable pattern types were analyzed specifically, compared with onomatopoeia, mimetic words, repetition, rhyme, the shift of sentence and style types. The results indicated that predictable pattern books could be classified into eight types and the number of sentences in translated books increased owing to the difference of sentence structure. In terms of speakability, words in repetition, onomatopoeia and mimetic words represented higher frequency except rhyme because of the difference of characteristics of the two languages. Furthermore, translations used strategies of the shift in sentence and style types for speakability. These findings demonstrate that predictable pattern books can serve as good materials to read aloud for young children not only in terms of English picture books but also translated books regardless of concerns regarding their speakability.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.470-475
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• 2004

In this paper, we propose a method to extract a definitional answer sentence for a Definitional Question-Answering System. definitional answer sentence patterns are manually constructed with restriction rules to patterns, and a ranking information of the pattern using its frequency from the corpus. answer sentence pattern consists of the syntactic structure of a definitional answer sentence, and clue words. this system show 83% accuracy for untrained corpus.

• Journal of the Korean Society for information Management
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• v.18 no.4
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• pp.37-55
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• 2001

The purpose of this study is to present a text summarization system using a knowledge base containing information about verbs and their arguments that are statistically obtained from a subject domain. The system consists of two modules: the training module and the summarization module. The training module is to extract cue verbs and their basic sentence patterns by counting the frequency of verbs and case markers respectively, and the summarization module is substantiate basic sentence patterns and to generate summaries. Basic sentence patterns are substantiated by applying substantiation rules to the syntactics structure of sentences. A summary is then produced by connecting simple sentences that the are generated through the substantiation module of basic sentence patterns. ‘robbery’in the daily newspapers are selected for a test collection. The system generates natural summaries without losing any essential information by combining both cue verbs and essential arguments. In addition, the use of statistical techniques makes it possible to apply this system to other subject domains through its learning capability.

• Speech Sciences
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• v.11 no.3
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• pp.111-128
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• 2004

In English, a focused word with new information receives a pitch accent. This paper examines how English native speakers and Korean speakers produce and perceive focus in English yes-no questions. The production experiments show that native speakers realize an appropriate intonation of yes-no questions, in which a focused word has a low pitch accent followed by a high phrasal accent and a high boundary tone. However, Korean speakers usually give a high tone to a focused word. In a like manner, the perception experiments show that English native speakers judge a word with a low tone to be focused, while Korean speakers have difficulty in comprehending a focused word realized as a low tone. And it is found that Korean speakers tend to perceive low tones on sentence initial and final focused words better than those on sentence medial focused words, and they often perceive a word with a relatively high fundamental frequency or a sharp rise of fundamental frequency as a focused word. This paper shows that Korean speakers have trouble to produce and perceive an appropriate tonal pattern of a focused yes-no question, and that can cause confusion in a conversation with native speakers.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.107-110
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• 1994

In this paper, we describe the features of the fundamental frequency contour of Korean read speech, and propose a new stylization method to characterize the Fø pattern of segments. Our algorithm consists of three stylization processes : the segment level, the syllable level, and the sord level. For stylization of Fø contour in the segment level , we applied least square error minimization method to determine Fø values at initial, medial, and final position in a segment. In the syllable level, we determine the stylized Fø pattern of a syllable using the mean Fø value of each word and style information for each word, syllable and segment, we reconstruct Fø contour of sentences. The simulation results show that the error is less than 10% of the actual Fø contour for each sentence. In perception test, there is little difference between the synthesized speech with the original difference between the synthesized speech with the original Fø contour and the synthesized speech with the stylized Fø contour.

• Journal of Music and Human Behavior
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• v.13 no.2
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• pp.67-83
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• 2016

This study investigated the tonal characteristics in Korean emotion words by analyzing the pitch patterns transformed from word utterance. Participants were 30 women, ages 19-23. Each participant was instructed to talk about their emotional experiences using 4-syllable target words. A total of 180 utterances were analyzed in terms of the frequency of each syllable using the Praat. The data were transformed into meantones based on the semi-tone scale. When emotion words were used in the middle of a sentence, the pitch pattern was transformed to A3-A3-G3-G3 for '즐거워서(joyful)', C4-D4-B3-A3 for '행복해서(happy)', G3-A3-G3-G3 for '억울해서(resentful)', A3-A3-G3-A3 for '불안해서(anxious)', and C4-C4-A3-G3 for '침울해서(frustrated)'. When the emotion words were used at the end of a sentence, the pitch pattern was transformed to G4-G4-F4-F4 for '즐거워요(joyful)', D4-D4-A3-G3 for '행복해요(happy)', G3-G3-G3-A3 and F3-G3-E3-D3 for '억울해요(resentful)', A3-G3-F3-F3 for '불안해요(anxious)', and A3-A3-F3-F3 for '침울해요(frustrated)'. These results indicate the differences in pitch patterns depending on the conveyed emotions and the position of words in a sentence. This study presents the baseline data on the tonal characteristics of emotion words, thereby suggesting how pitch patterns could be utilized when creating a melody during songwriting for emotional expression.

• MALSORI
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• no.65
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• pp.51-65
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• 2008

The aim of this study is to compare ASD (Autism Spectrum Disorder) children with normal children in terms of the prosodic features. Materials are collected by the reading of Korean read sentences. They are composed of 10 declarative sentences, each of which was consisted of 5-6 words. Subjects are consisted of 10 ASD and 10 normal male children with a receptive vocabulary age of 5;0-6;5 years. We found out that both groups showed the differences not only in the tonal patterns at the end of the prosodic phrases, but also in both the degree of rising and falling slope related to pitch contour. While HL% and HLH% were highly emerged in sentence final position in normal group, HL% and HLH% were prominent in ASD group in the same position. LH% and LHL% IP types were observed only in ASD group in sentence medial position. The slope showing the variation in the fundamental frequency at the end of the prosodic phrase was twice as steep in the group of ASD children as in the group of normal children.

• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.627-635
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• 2008

An extended form of lexical network is explored by presenting U-WIN, which applies lexical relations that include not only semantic relations but also conceptual relations, morphological relations and syntactic relations, in a way different with existing lexical networks that have been centered around linking structures with semantic relations. So, This study introduces the new methodology for constructing a syntactic relation automatically. First of all, we extract probable nouns which related to verb based on verb's sentence type. However we should decided the extracted noun's meaning because extracted noun has many meanings. So in this study, we propose that noun's meaning is decided by the example matching rule/syntactic pattern/semantic similarity, frequency information. In addition, syntactic pattern is expanded using nouns which have high frequency in corpora.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1150-1159
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• 2000

This paper presents an automatic text categorization model that improves the accuracy by combining statistical and knowledge-based categorization methods. In our model we apply knowledge-based method first, and then apply statistical method on the text which are not categorized by knowledge-based method. By using this combined method, we can improve the accuracy of categorization while categorize all the texts without failure. For statistical categorization, the vector model with Inverted Category Frequency (ICF) weighting is used. For knowledge-based categorization, Phrasal Patterns and Keyword Sets are introduced to represent sentence patterns, and then pattern matching is performed. Experimental results on new articles show that the accuracy of categorization can be improved by combining the tow different categorization methods.