• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.483-490
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• 2021

In order to learn an existing song and create a new song using an artificial neural network, it is necessary to convert the song into numerical data that the neural network can recognize as a preprocessing process, and one-hot encoding has been used until now. In this paper, we proposed a note embedding method using notes as a basic unit and a bar embedding method that uses the bar as the basic unit, and compared the performance with the existing one-hot encoding. The performance comparison was conducted based on quantitative evaluation to determine which method produced a song more similar to the song composed by the composer, and quantitative evaluation methods used in the field of natural language processing were used as the evaluation method. As a result of the evaluation, the song created with bar embedding was the best, followed by note embedding. This is significant in that the note embedding and bar embedding proposed in this paper create a song that is more similar to the song composed by the composer than the existing one-hot encoding.

• Knowledge Management Research
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• v.19 no.2
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• pp.91-108
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• 2018

This study mainly focused on measuring the impact of comments for a particular song on the number of streamings and downloads. We modeled multiple regression equations to perform this analysis. We chose digital music market for the object of analysis because of its inherent characteristics, such as experience goods, high bandwagon effect, and so on. We carefully utilized text mining technique in accordance with the algorithm of Naïve Bayes classifier to distinguish whether a comment for a piece of music be regarded as positive or negative. In addition, we used 'size of agency' and 'existence of hit song' as moderating variables. The reason for usage of those variables is that those are assumed to affect users' decision for selecting particular song especially when downloading or streaming via music sites. We found empirical evidences that positive comments for a particular song increase the number of both downloads and streamings. However, positive comments may decrease the number of downloads when the size of agency of the artist is big. As a result, we were able to say that a positive comment for a particular song functioned as 'word-of-mouth' effect, inducing other users' behavioral response. We also found that other features of an artist such as size of the agency that the artist belongs to functioned as an external factor along with feature of the song itself.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.221-225
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• 2007

Recently, on account of stress relief and settlement of a healthy drinking culture, many people are visiting a song practice room. In case of such song practice room, since the mechanical voice through a loud accompaniment-music and microphone is on using, there has made a very loud noise, and it influences a lot to the adjacent other space and song practice room booth. Consequently, from the designing stage an efficient measures for soundproof and sound-insulation should be arranged. However, as most of the song practice room wall-bodies that already built up or under construction step were constructed merely with consideration on an interior-wise factor only, it is suffering at the soundproof and sound-insulation. Reflecting such viewpoint, this Study has measured Sound Transmission Loss on the subject for the song practice room wall-body recently built up, and based on the actually measured data, by practice of comparison?analysis on it using various evaluation methods, would intends to present a fundamental material for establishment an efficient sound-insulation measure.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.641-647
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• 2017

In this paper, we propose a method to automatically generate a configured song with melodies composed of front/middle/last parts by using hierarchical artificial neural networks in automatic composition. In the first layer, an artificial neural network is used to learn an existing song or a random melody and outputs a song after performing rhythm post-processing. In the second layer, the melody created by the artificial neural network in the first layer is learned by three artificial neural networks of front/middle/last parts in the second layer in order to make a configured song. In the artificial neural network of the second layer, we applied a method to generate repeatability using measure identity in order to make song with repeatability and after that the song is completed after rhythm, chord, tonality post-processing. It was confirmed from experiments that our proposed method produced configured songs well.

• CELLMED
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• v.6 no.4
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• pp.25.1-25.2
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• 2016

The purpose of this study is to examine Ssukdaemeori of Chunhyangga may have effect on depression for music therapy. Ssukdaemeori of Chunhyangga, one of the five surviving stories of pansori (a long epic song), is a touching, sad song in Han Ak (Korean music, 韓樂). In this paper, the author reports on the very sad song, Ssukdaemeori. While listening to the song, Koreans feel the same amount of despair when Ssudaemeori's heroine, Chunhyang, cries out in hopelessness and grief. The author argues that Koreans get to see the saddest parts of themselves reflected back at them in the sorrowful sight of the heroine. It is also believed that Ssukdaemeori has contributed to the healing of Koreans' indignation and pain. For example, depression is currently a social problem. However, listening to sorrowful music like Ssukdaemeori can have a good effect on people feeling sad and depressed.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.113-120
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• 2022

Mongolian folk songs are inspired by Mongolian labor songs and are classified into long and short songs. Mongolian long songs have ancient origins, are rich in legends, and are a great source of folklore. So it was inscribed by UNESCO in 2008. Mongolian written literature is formed under the direct influence of oral literature. Mongolian long song has 3 classes: ayzam, suman, and besreg by their lyrics and structure. In ayzam long song, the world perfectly embodies the philosophical nature of world phenomena and the nature of human life. Suman long song has a wide range of topics such as the common way of life, respect for ancestors, respect for fathers, respect for mountains and water, livestock and animal husbandry, as well as the history of Mongolia. Besreg long songs are dominated by commanded and trained characters. In this paper, we proposed a method to classify their 3 types of long songs using machine learning, based on their lyrics structures without semantic information. We collected lyrics of over 80 long songs and extracted 11 features from every single song. The features are the name of a song, number of the verse, number of lines, number of words, general value, double value, elapsed time of verse, elapsed time of 5 words, and the longest elapsed time of 1 word, full text, and type label. In experimental results, our proposed features show on average 78% recognition rates in function type machine learning methods, to classify the ayzam, suman, and besreg classes.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.263-273
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• 2020

In 2019, Disney's musical film "Aladdin" was newly introduced with Princess Jasmine's theme song "Speechless," which was not featured in the animation "Aladdin" in 1992. Written as a theme song, "Speechless" expresses Princess Jasmine as a self-reliant, enterprising and dignified woman. The song made the change in Princess Jasmine's character very articulate. She has developed herself as an active and enthusiastic character from a rather passive and reserved figure. The musical film "Aladdin" has drawn much attention and love from many audiences with its own narrative and original songs, but the addition of a new theme song "Speechless", which was not in the animation in 1992, made the musical film "Aladdin" even more powerful and meaningful. The study examined the organic relationship between the musical features and narratives of the newly included theme song 'Speechless' in the musical film Aladdin. Through the analysis of the six scenes that include the musical features of the theme song "Speechless," the study looked at how the relationship between music and narratives had an influence on cinematic expression.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.314-319
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• 2019

Computing chromagram similarity is indispensable in constructing cover song identification system. This paper proposes a code-based chromagram similarity to reduce the computational and the storage costs for cover song identification. By learning a song-specific codebook, a chromagram sequence is converted into a code sequence, which results in the reduction of the feature storage cost. We build a lookup table over the learned codebooks to compute chromagram similarity efficiently. Experiments on two music datasets were performed to compare the proposed code-based similarity with the conventional one in terms of cover song search accuracy, feature storage, and computational cost.

• Animal cells and systems
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• v.9 no.2
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• pp.47-55
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• 2005

Avian vocalization has been main topics in studying animal communication. The structure and usage as well as development and function of vocalization vary enormously among species and even among populations, and thus we reviewed the general patterns of song learning and the consequences of song communication in birds at the behavioural level: first, we compared the different learning phenomena between non-songbird and songbird, and we investigated the learning process of songbird both in the field and in the lab, which are needed to fully understand vocal communication. Second, we discussed a recent trend of sexual selection hypothesis explaining the structural and functional diversity of song in songbirds with repertoire and presented how the repertoire is actually used between neighbours based on individual recognition.

• Journal of Ecology and Environment
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• v.29 no.3
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• pp.219-225
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• 2006

To study song themes and variation of Yellow-throated Bunting, we obtained and analyzed recordings from 45 males breeding in 16 deciduous forests of 6 provinces. We classified the 3,245 songs into a total of 164 song themes and 1,024 song variants according to the identification on the base of difference(lexicon) in 640 syllable compositions. Males had one to six song themes and averaged 3.5 themes. No males shared an identical song theme. Males had $5{\sim}14$ syllables (ave. 9.4) in one song theme and males increased effectively their repertoire size by changing syllable composition (i.e. adding, deleting, or substituting one or more syllables) in a single song theme. The number of variants averaged 5.1 (range 1 to 31) per song theme. Individual variability was highest in the terminal elements of the song. In PCA, the 16 populations are clearly separated on Co. I based on shared syllable and on Co. II based on unique syllable. Similarity of songs based on shared syllables by distance coefficients, showed a pattern of concordance with geography. Pairwise similarity declined with increasing distance among recording sites. 16 different geographical regions by the syllable were divided in UPGMA tree.