• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1358-1366
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• 2015

This paper proposes an automatic composition method using the training capability of artificial neural networks and chord progression rules that are widely used by human composers. After training a given song, the new melody is generated by the trained artificial neural networks through applying a different initial melody to the neural networks. The generated melody should be modified to fit the rhythm and chord progression rules for generating natural melody. In order to achieve this object, we devised a post-processing method such as chord candidate generation, chord progression, and melody correction. From some tests we could find that the melody after the post-processing was very improved from the melody generated by artificial neural networks. This enables our composition system to generate a melody which is similar to those generated by human composers.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4E
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• pp.141-149
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• 2003

As music of digital form has been widely used, many people have been interested in the automatic extraction of natural information of music itself, such as key of a music, chord progression, melody progression, tempo, etc. Although some studies have been tried, consistent and reliable results of musical information extraction had not been achieved. In this paper, we propose a method to extract chord and tempo information from general polyphonic music signals. Chord can be expressed by combination of some musical notes and those notes also consist of some frequency components individually. Thus, it is necessary to analyze the frequency components included in musical signal for the extraction of chord information. In this study, we utilize a sinusoidal modeling, which uses sinusoids corresponding to frequencies of musical tones, and show reliable chord extraction results of sinusoidal modeling. We could also find that the tempo of music, which is the one of remarkable feature of music signal, interactively supports the chord extraction idea, if used together. The proposed scheme of musical feature extraction is able to be used in many application fields, such as digital music services using queries of musical features, the operation of music database, and music players mounting chord displaying function, etc.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.622-628
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• 2020

This paper proposes a music generation technique that automatically generates trot music using a Generative Adversarial Network (GAN) model composed of a Recurrent Neural Network (RNN). The proposed method uses a method of creating a chord as a skeleton of the music, creating a melody and bass in stages based on the chord progression made, and attaching it to the corresponding chord to complete the structured piece. Also, a new chorus chord progression is created from the verse chord progression by applying the characteristics of a trot song that repeats the structure divided into an individual section, such as intro, verse, and chorus. And it extends the length of the created trot. The quality of the generated music was specified using subjective evaluation and objective evaluation methods. It was confirmed that the generated music has similar characteristics to the existing trot.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1456-1462
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• 2016

In this paper, we apply a chord progression learning model to a rule-based generation of a four-part chorus. The proposed system is given a 32-note melody line and completes the four-part chorus based on the rule of harmonics, predicting the chord progression with the CRBM model. The data for the training model was collected from various harmony textbooks, and chord progressions were extracted with key-independent features so as to utilize the given data effectively. It was shown that the output piece obtained with the proposed learning model had a more natural progression than the piece that used only the rule-based approach.

• Journal of Korea Entertainment Industry Association
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• v.15 no.1
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• pp.63-73
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• 2021

This study aims to analyze music of Yoon-sang, as a part of musical research, which is the most fundamental approach among academic studies on Korean popular music. Yoon-Sang is a representative composer, who has gone through the 1980s to the present. The result of analysis of 21 songs created by Yoon-Sang showed that his songs are mostly characterized by tonal music, in which chord relationships develop focusing on keynotes. The reason why his music does not sound uniform pursuing stability is he properly added the progression of chromatic chords, based on diatonic chords and melodies. Dominant 7th chord and diminished 7th chord are used the most among diverse techniques adding chromatic colors. Along with these chords, chromatic intervals are used not only in chord progression but also in melodies. The successive, ascending or descending movement of the base line is his common composition and arrangement technique revealed in every song. One of formal changes with the stream of the times is that the number of measured in the pre-chorus and interlude that were of great importance in his songs of the 1990s decreased over time. With regard to harmonic changes, whereas modulation between parts was applied to his 2 songs created in the 2010s. Yoon-Sang's music had one strong tonality overall, but his music began to have more than two tonalities starting the 2010s, and this is a big variation in his music.

• Journal of Korea Multimedia Society
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• v.23 no.6
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• pp.765-771
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• 2020

To enable AI(artificial intelligence) to realize visual emotions, it attempts to create music centered on color, an element that causes emotions in paintings. Traditional image-based music production studies have a limitation in playing notes that are unrelated to the picture because of the absence of musical elements. In this paper, we propose a new algorithm to set the group of music through the average color of the picture, and to produce music after adding diatonic code progression and deleting sound using median value. And the results obtained through the proposed algorithm were analyzed.

• Journal of KIISE
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• v.43 no.2
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• pp.204-211
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• 2016

In this paper, we propose an automatic melody composition system that can generate a sophisticated melody by adding non-harmony tone in the given chord progression. An overall procedure consists of two steps, which are the rhythm generation and melody generation parts. In the rhythm generation part, we designed new fitness functions for rhythm that can be controlled by a user setting parameters. In the melody generation part, we designed new fitness functions for melody based on harmony theory. We also designed evolutionary operators that are conducted by considering a musical context to improve computational efficiency. In the experiments, we compared four metaheuristics to optimize the rhythm fitness functions: Simple Genetic Algorithm (SGA), Elitism Genetic Algorithm (EGA), Differential Evolution (DE), and Particle Swarm Optimization (PSO). Furthermore, we compared proposed genetic algorithm for melody with the four algorithms for verifying performance. In addition, composition results are introduced and analyzed with respect to musical correctness.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.265-270
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• 2017

This study purposed to investigate harmonic compositions and progressions that are appropriate for emotion vocabulary. In study 1, eight(8) professional music therapists were asked to provide harmonic compositions and progressions reflecting the tonal characteristics of emotion vocabulary and the rationales. Various attributes of harmonic compositions and progressions were examined and the content analysis were administered. In study 2, the obtained data on study 1 were evaluated by 124 music therapy and music majors for the validity. In the first study, analyzed results showed that 'happy' vocabulary utilized major, tonic, consecutive chord changes, 'angry' vocabulary utilized minor, augmented, $9^{th}$, $11^{th}$, unsolved $7^{th}$ chord progression, 'sad' vocabulary utilized minor, diminish, chromatic chord progressions. In the second study, there was statistically significant difference with 'happy' vocabulary. These results can provide basic evidences for musical ideas of harmonic compositions and progressions to better communicate emotional aspects of lyrical messages when composing melody in a song.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.1-8
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• 2006

We suggest a graphical representation of the tension flow in tonal music using a piecewise parametric curve, which is a function of time illustrating the changing degree of tension in a corresponding chord progression. The tension curve can be edited by using conventional curve editing techniques to reharmonize the original music with reflecting the user's demand to control the tension of music. We introduce three different methods to measure the tension of a chord in terms of a specific key, which can be used to represent the tension of the chord numerically. Then, by interpolating the series of numerical tension values, a tension curve is constructed. In this paper, we show the tension curve editing method can be effectively used in several interesting applications: enhancing or weakening the overall feeling of tension in a whole song, the local control of tension in a specific region of music, the progressive transition of tension flow from source to target chord progressions, and natural connection of two songs with maintaining the smoothness of the tension flow. Our work shows the possibility of controlling the perceptual factor (tension) in music by using numerical methods. Most of the computations used in this paper are not expensive so they can be calculated in real time. We think that an interesting application of our method is an interactive modification of tension in background music according to the user's emotion or current scenario in the interactive environments such as games.