• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06a
• /
• pp.937-942
• /
• 1994

Text-to-Speech(TTS) conversion system can convert any words or sentences into speech. To synthesize the speech like human beings do, careful prosody control including intonation, duration, accent, and pause is required. It helps listeners to understand the speech clearly and makes the speech sound more natural. In this paper, a prosody control scheme which makes use of the information of the function word is proposed. Among many factors of prosody, intonation, duration, and pause are closely related to syntactic structure, and their relations have been formalized and embodied in TTS. To evaluate the synthesized speech with the proposed prosody control, one of the subjective evaluation methods-MOS(Mean Opinion Score) method has been used. Synthesized speech has been tested on 10 listeners and each listener scored the speech between 1 and 5. Through the evaluation experiments, it is observed that the proposed prosody control helps TTS system synthesize the more natural speech.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.69-92
• /
• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.33 no.4
• /
• pp.655-665
• /
• 2009

The purpose of this study is to find out the Korean fashion brand purchasing behavior of Chinese woman college students who would be the one of major customers in Chinese market along with their preferences of Korean wave and fashion leadership. The data was collected from 379 Chinese female college students on Qingdao, China. The results based on the data analysis were as follows. 1. The students's preferences for Korean wave about Korean drama, popular song, films were relatively high. 2. Chinese female college students's evaluation of Korean fashion brand was high, especially, for the fashion trend, design/style, color, cutting and sewing, fitting, and material. However, they valued that its price was expensive. 3. The fashion leadership was classified as fashion innovation or fashion opinion leadership. 9.0% of the respondents were fashion dual leaders who were fashion innovator and fashion opinion leader. 4. The higher family income of the respondents was the better fashion leadership, preferences for Korean wave, perceived quality and attitude toward Korean fashion brand. The results showed that promotion strategy focused on keeping the Korean wave through drama, films, and popular song. And the development of high fashion brand and the word of mouth marketing through fashion dual leader were also needed in order to make inroads into China market.

• The Journal of the Korea Contents Association
• /
• v.9 no.8
• /
• pp.178-189
• /
• 2009

This paper investigates the influence of social networks on the satisfaction and loyalty of online game users. We gather the resulting questionnaires written by all respondents and compare social networks of users in the online game world. Social networks of online game users influence a sense of community. In consequence, the community sense influences the satisfaction and loyalty of online game users, respectively. Therefore, the companies which produce an online game and provide various services to users should consider the social networks and communities of their game users. Especially they have to try to manage the users who are the opinion leaders of the online game. If the companies make good relationships with users who are the opinion leaders of the online game, they would easily improve the loyalty of ordinary users by performing word-of-moth marketing of the users' opinions concerning about the online game.

• The KIPS Transactions:PartB
• /
• v.18B no.5
• /
• pp.325-332
• /
• 2011

Social Network Services(SNS) such as Twitter, Facebook and Myspace have gained popularity worldwide. Especially, sentiment analysis of SNS users' sentence is very important since it is very useful in the opinion mining. In this paper, we propose a new sentiment classification method of sentences which contains formal and informal vocabulary such as emoticons, and newly coined words. Previous methods used only formal vocabulary to classify sentiments of sentences. However, these methods are not quite effective because internet users use sentences that contain informal vocabulary. In addition, we construct suggest to construct domain sentiment vocabulary because the same word may represent different sentiments in different domains. Feature vectors are extracted from the sentiment vocabulary information and classified by Support Vector Machine(SVM). Our proposed method shows good performance in classification accuracy.

• Journal of Sasang Constitutional Medicine
• /
• v.10 no.1
• /
• pp.311-341
• /
• 1998

The objective of this article is to induce that the conception of 'Qi-jul(氣質) and Qi-pum(氣稟)' was introduced to the Sasang(四象) Constitutional Medicine from bibliographic study on the theory of 'Qi-pum(氣稟)'. The conclusions summerized as followings. 1. In the oriental medicine, qualitative difference of 'zheng-qi(正氣)' among the individuals, the opposing power against a disease, is regarded as constitution. Having been used as 'nature(素)', 'quality(質)' and 'character(氣質)' in the oriental medical book, the word of 'Che-Jil(體質)' was used in good earnest at the end of 'Qing(情)' dynasty. 2. The nature(性) is divided into two, original nature(本然之性) and charicteristic nature(氣質之性) in the 'New confucianism(新儒學)' and the former means a principle(理), is a pure and good thing and used as a conception of universality, the latter is a principle of character and a imperfect imitation of principle(理). 3. It was repeatedly confirmed that 'Qi-jil and Qi-pum' meant the difference among the individuals by the dispute of 'Li-Qi(理氣)' caused by Lee Hwang(李滉) and Lee Yi(李耳) and by that of 'Ho-Rak(湖洛)' in the Ch'o-son(朝鮮) dynasty. 4. Han Sok-Ji, based on Meng-Zi(孟子)'s doctrine that man's inborn nature is good, criticized the theory of 'Qi-pum' which was 'Zhu-Zi(朱子)'s opinion and his opinion about the life(命) was thought to clue to the classification of the 'Sasang(四象)' invented by Lee Je-Ma as Park Se-Dang's theory that everyone has common nature but has different life(命). 5. By introducing the theory of 'Qi-pum' and the conception of life(命) which was understood as a special character by Han Sok-Ji and Park Se-Dang to Sa-sang constitutional medicine, Lee Je-Ma explained the reason why each man who was classified four constitutions, 'Taiyang'(太陽), 'Taiyin'(太陰), 'Shaoyang'(少陽), 'Shaoyin'(少陰), had the different formation of the visceral department(臟局).

• The Journal of Korean Philosophical History
• /
• no.52
• /
• pp.107-130
• /
• 2017

The purpose of this study is to catch the characteristics of the Hanju Yi Jinsang (寒洲 李震相, 1818~1886)'s thought of the 'Li(理)' through Hanju's view on the Ido-seol(理到說), the Toegye Yi Hwang(退溪 李滉, 1501~1570)'s latter Mulgyuk(物格) theory, and to establish the foundation for identifying the aspects of development about Toegye School's concept of Li from Toegye's Ido-seol. The Ido-seol was criticized for regarding Li - the immovable principle - as 'living thing'. Toegye School's scholars tried to solve this problem by translating the 'word' correctly. Hanju also translated the word 'Do(到)', the verb of 'Ido', as meaning of 'perfectly understood' based on his translation of the word 'Gyuk(格)' as 'Ku(究)'. On the other hand, he also regarded the principle-application structure of Li and the its characteristic the 'Li as Hwalmul(活物)' as the main point of Toegye's Neo-confucianism thought his methodology 'Three viewpoints[三看法]'. Before Hanju, scholars dose not have more opinion from the translation of the word, and it is too difficult to identifying their scholarly identity through their viewpoints on Ido-seol. On the other hand, Hanju thought that the lack of the idea for comprehensive approach between Xin(心) and Li(理) will cause the misunderstanding the relationship between Xin and Li. In this reason, he evaluated Toegye's Ido-seol based on the concept of 'One principle and its manifoldness[理一分殊]'. Consequently, he concatenated the characteristic of Xin which includes all things with concept of Mulgyuk, and emphasized that Xin which penetrates the principle of all things has the characteristic of 'One principle(理一)'.

• Journal of Korean Elementary Science Education
• /
• v.35 no.2
• /
• pp.150-165
• /
• 2016

This study aims to analyze types of science museum worksheets developed by elementary pre-service teachers and their perspectives on the requirements and necessity of science museum worksheets. As analysis subjects, this study selected 38 kinds of worksheets and reports developed by 114 elementary pre-service teachers who were in the third year of university of education. In this study, the science museum selected for elementary pre-service teachers to develop worksheets was a national science museum, composed of 'Nature and Discovery Museum', 'Science Technology and Industry Museum' and 'Children's Museum', which was located in a metropolitan city and opened in 2013. The results of this study can be summarized as follows; Firstly, as a result of analyzing the science museum worksheets developed by elementary pre-service teachers, this study found out that the experience type with hands-on and observation techniques applied was most, and as an approach method, direct manipulation, look-in observation and close observation were most. However, although these science museum worksheets were experience-oriented, many of them were survey-oriented ones that suggested too many questions through various exhibits. Secondly, as a result of analyzing requirements of science museum worksheets elementary pre-service teachers thought and described through the word tree of NVivo 10, this study extracted 10 kinds of main themes, out of which the requirement, 'A limited amount of activity should be required', showed the highest frequency. Thirdly, as a result of analyzing the necessity of science museum worksheets elementary pre-service teachers thought and described through the word tree of NVivo 10, this study extracted 9 kinds of main themes, out of which the opinion, 'It is required to help students check an exhibit which may be passed by', was most.

• Journal of Digital Contents Society
• /
• v.14 no.4
• /
• pp.581-587
• /
• 2013

In this paper, we propose a method of sentiment classification which uses Levenshtein distance. We generate BOW(Bag-Of-Word) applying Levenshtein daistance in sentiment features and used it as the training set. Then the machine learning algorithms we used were SVMs(Support Vector Machines) and NB(Naive Bayes). As the data set, we gather 2,385 reviews of movies from an online movie community (Daum movie service). From the collected reviews, we pick sentiment words up manually and sorted 778 words. In the experiment, we perform the machine learning using previously generated BOW which was applied Levenshtein distance in sentiment words and then we evaluate the performance of classifier by a method, 10-fold-cross validation. As the result of evaluation, we got 85.46% using Multinomial Naive Bayes as the accuracy when the Levenshtein distance was 3. According to the result of the experiment, we proved that it is less affected to performance of the classification in spelling errors in documents.

• The KIPS Transactions:PartB
• /
• v.17B no.1
• /
• pp.93-98
• /
• 2010

In this paper, we introduce a system that summarizes product evaluation through linguistic analysis to effectively utilize explosively increasing product reviews. Our system analyzes polarities of product reviews by product features, based on which customers evaluate each product like 'design' and 'material' for a skirt product category. The system shows to customers a graph as a review summary that represents percentages of positive and negative reviews. We build an opinion word dictionary for each product feature through context based automatic expansion with small seed words, and judge polarity of reviews by product features with the extracted dictionary. In experiment using product reviews from online shopping malls, our system shows average accuracy of 69.8% in extracting judgemental word dictionary and 81.8% in polarity resolution for each sentence.