• Journal of Educational Research in Mathematics
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• v.19 no.1
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• pp.63-80
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• 2009

This paper has a purpose to find out the important points about linguistic factors suited to the assessment purpose and mathematics teaching/learning that a word-problem sentence has to possess. We also examine the degree of understanding of sentence and the perceptive/emotional reactions of students toward two different kinds of word-problem sentences that have same mathematical contents, but different linguistic structures. The objects of this thesis are 124 students from the third to sixth grade in an elementary school. We execute assessment of simple-sentence-word-problem and complex-sentence-word-problem that have same mathematical contexts, but different linguistic structures. Then we have compared and examined their own process of solving the two types word-problems and we make up questionnaire and have an interview with them. The conclusions are as followings: First, simple-sentence-word-problem is more successful to suggest an information for solving a problem than complex one. Second, it is hard to find the strategy for solving a problem in complex-sentence-word-problem than simple one. Third, students think that suggested information and mathematical knowledge are different according to the linguistic structure in the process of perceiving the information after reading a word-problem. Fourth, in spite of same sentence type, the negative mental reaction is showed greatly to complex-sentence-word-problem even before solving a problem.

• Journal of Environmental Science International
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• v.6 no.3
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• pp.213-218
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• 1997

The question style In high school enoronmental science textbook was examined in terms of the placement, frequency, and type of question, and then analyzed the kind of scientific Inquiry process elicited by the question In the topic of textbook using the Tektbook guestioning Strategy Assessment Instrument (TQSAI). The average number of question per topic was only 0.6. The number of all Question In the high school enororunental science textbook was very little : the number of non-experiential Question was 8 and that of experiential one was 3. The total number of sentence was 1,236 and the ratio of the number of Question to that of sentence was 0.9% . The frequency of non-experlential question was higher than that of experiential one. In action part of the textbook, there were more kinds of Question styles than In the matin part.

• Phonetics and Speech Sciences
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• v.6 no.3
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• pp.13-21
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• 2014

Late talkers are young children who are delayed in their expressive language skills despite normal nonverbal cognitive ability, adequate hearing and typical personality development. The purpose of this study is to investigate the sentence interpretation strategies used by Korean-speaking late talkers and age-matched normal children. Nine late talkers and nine normal children matched by age at 30-35months were participated in this study. 27 simple noun-noun-verb(NNV) sentences were generated by factorial combination of case-marker [nominal case-marker on the first noun and accusative on the second (C1), accusative on the first noun and nominative on the second (C2), and no case markers on both nouns (C0)], and animacy of the nouns [animate-inanimate(AI), inanimate-animate(IA), animate-animate(AA)]. All the children were asked to "act out" their interpretation of the given sentence. For each type of sentences the percentage of choices of the first noun as the agent was calculated. The results of group (2) ${\times}$ animacy(3) ${\times}$ case-marker(3) mixed ANOVA showed a significant main effect for 'animacy', 'case marker' and 'group(2) ${\times}$ case-marker (3)'. The late talkers relied on semantic (animacy) cues in their interpretation of the sentences, while the normal peers utilized both animacy and grammatical morpheme (case-marker) cues. The results indicated that the late-talkers' comprehension skills were also delayed.

• MALSORI
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• no.41
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• pp.73-81
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• 2001

This paper reports the results of an experimental phonetic study of intonation contrasts perception by speakers of British English, Japanese and Russian. Six series of re-synthesized two-syllable rise-fall contours with manipulated parameters of the rise in the first and the fall in the second syllable were employed in the experiment. Modifications of pitch height were executed in 2 st steps, and of duration in 30ms steps. The subjects, who were native speakers of British English, Japanese and Russian, identified the sentence type of presented re-synthesized stimuli. The results of the experiments demonstrate overall similarity of the perception strategies across the three groups of subjects, especially regarding the thresholds of declarative' sentence type judgement. Non-declarative judgements are more language-specific. The results can be employed for the teaching of English, Japanese and Russian as foreign languages as well as for speech synthesis and recognition.

• Proceedings of the KSPS conference
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• 2000.07a
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• pp.139-148
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• 2000

This paper reports the results of an experimental phonetic study of intonation contrasts perception by speakers of British English, Japanese and Russian. Six series of re-synthesized two-syllable rise-fall contours with manipulated parameters of the rise in the first and the fall in the second syllable were employed in the experiment. Modifications of pitch height were executed in 2 st steps, and of duration - in 30ms steps. The subjects, who were native speakers of British English, Japanese and Russian, identified the sentence type of presented re-synthesized stimuli. The results of the experiments demonstrate overall similarity of the perception strategies across the three groups of subjects, especially regarding the thresholds of 'declarative' sentence type judgement. Non-declarative judgements are more language-specific. The results can be employed for the teaching of English, Japanese and Russian as foreign languages as well as for speech synthesis and recognition.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.297-304
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• 2010

Clustering method which based on sentence type or document genre is a technique used to improve translation quality of SMT(statistical machine translation) by domain-specific translation. But there is no previous research using sentence type and document genre information simultaneously. In this paper, we suggest an integrated clustering method that classifying sentence type by syntactic structure similarity and document genre by word similarity information. We interpolated domain-specific models from clusters with general models to improve translation quality of SMT system. Kernel function and cosine measures are applied to calculate structural similarity and word similarity. With these similarities, we used machine learning algorithms similar to K-means to clustering. In Japanese-English patent translation corpus, we got 2.5% point relative improvements of translation quality at optimal case.

• Phonetics and Speech Sciences
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• v.14 no.2
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• pp.39-54
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• 2022

This study aims to clarify the prosodic differences in speech types by examining the Korean read speech and spontaneous speech in the Korean part of the L2 Korean Speech Corpus (speech corpus for Korean as a foreign language). To this end, the articulation length, articulation speed, pause length and frequency, and the average fundamental frequency values of sentences were set as variables and analyzed via statistical methodologies (t-test, correlation analysis, and regression analysis). The results found that read speech and spontaneous speech were structurally different in the form of prosodic phrases constituting each sentence and that the prosodic elements differentiating each speech type were articulation length, pause length, and pause frequency. The statistical results show that the correlation between articulation speed and articulation length was highest in read speech, explaining that the longer a given sentence is, the faster the speaker speaks. In spontaneous speech, however, the relationship between the articulation length and the pause frequency in a sentence was high. Overall, spontaneous speech produces more pauses because short intonation phrases are continuously built to make a sentence, and as a result, the sentence gets lengthened.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.1-25
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• 2020

Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• The Journal of the Acoustical Society of Korea
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• v.31 no.7
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• pp.461-471
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• 2012

The purpose of this paper is to provide basic data for development of Korean teaching programs for immigrant women from multicultural families through the acoustic analysis of their prosodic phrasing and intonation pattern. The results showed that immigrant women showed some differences in most of the prosodic characteristics from a Korean women's group: Immigrant women realized the first word of a sentence in an intonational phrase while Korean women did in an accentual phrase. They also haven't yet correctly learned the tone type of the first of an accentual phrase which differs depending on the type of its first segment yet. As a result, they showed many diverse intonation patterns compared to Korean women. Furthermore, the immigrant women's groups showed some differences between them in a few prosodic characteristics. Philippine women, whose residence duration in Korea is relatively longer than that of Vietnamese women, were more similar to Korean women: Vietnamese women read a sentence with a larger number of intonational phrases than Philippine women did. And they realized sentence-final boundary tone of a yes-no question not only in 'H%' but also in 'HL%' while, like Korean women, Philippine women did only in 'H%'.