• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1184-1191
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• 2021

In a pop song, the creator's intention is communicated to the user through music and lyrics. Lyric meaning is as important as music, but in most cases lyrics are delivered to users in a static form without non-verbal cues. Providing lyrics in a static text format is inefficient in conveying the emotions of a music. Recently, lyrics video with kinetic typography are increasingly provided, but producing them requires expertise and a lot of time. Therefore, in this system, the emotions of the lyrics are found through the analysis of the text of the lyrics, and the deep learning model is trained with the data obtained by converting the melody into a Mel-spectrogram format to find the appropriate emotions for the music. It sets properties such as motion, font, and color using the emotions found in the music, and automatically creates a kinetic typography video. In this study, we tried to enhance the effect of conveying the meaning of music through this system.

• International Journal of Advanced Culture Technology
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• 제10권3호
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• pp.352-359
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• 2022

The study examined a sentiment analysis based on Tweeter messages between contemporary pop musicians and classical music composers. Musicians of each genre were carefully selected for the sentiment analysis. Many opinion messages on Tweets that users have discussed were collected, and the messages were evaluated by using Naïve Bayes Classifier. The results demonstrated that users showed high positive sentiments for the two different genres. However, on average, the positive sentiment values for classical music composers are higher than for contemporary pop musicians. In addition, the rankings of the highest positive sentiments among contemporary pop musicians and classical music composers did not coincide with the popularity of the two different genres of musicians. This study will contribute to the study of future sentimental analysis between music and musicians.

• 패션비즈니스
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• 제9권4호
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• pp.59-78
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• 2005

This study aims to know the deferences of hair fashion feeling group in accordance with hair styling activities, general characteristics, life styles objecting to capital area university women students and aid to hair fashion design. So the results are as belows. 1. Frequency Analysis of Categories A. Hair fashion feeling - Natural, sexy, romantic pretty, sophisticate, ethnic are 90% in total hair fashion feeling variables in sequence of frequency, so it can be said these are in vogue. B. Hair styling activities - The objections visit the hair salon once 1-2months, spend about 42,000 won a month, perform cut & wave perm to sentimental reasens & hair style changes, determine the hair style well coordinated in her image and managed easily. In her home, they manage her hair style 12 minutes a day, spend 17,000 won to buy hair aids, do hair blow dry or pin or pony tail mainly in the morning, scarcely use the hair styling aids but if use, essence or wax mainly. And the degree of interest to hair style is high. C. General Characteristics - The objections's average age is 21.1, residence is seoul kangnam 23.3%, seoul kangbook 18.4%, other capital areas 58.4%, the degree of education is university students 94.9%, graduated student 5.1%, marriage is married 96%, unmarried 2.8%, family who live with is married are mainly man & woman and living with father & mother in low in man's, unmarried are mainly live alone & nuclear family, personal expenses a month is 300,000 won in average, income of home is 4,000,000 won a month. D. Life style - The objections are not in interest of physical exercises but if are, do yoga & health, like drama & comedies program, watch TV or meet friend in leisure time, like balad & dance music, fashion magazine, meet friend in cafe or college. 2. Relationship of hair fashion feeling & other variables Using the $x^2$-test, level p<0.05, Hair styling activities(frequency of hair salon coming in and out, ordinary time representing hair style, preferred hair styling aids, the amount of hair style interest), General Characteristics(age), Life style(leisure time) variables are meaningful.