Composition Of Melodies Research Articles

ВЕЛИКАТА МУЗИКАЛНА КНИГА ОТ АЛ ФАРАБИ – СРЕДНОВЕКОВЕН ОБРАЗЕЦ ЗА МУЗИКАЛНОТЕОРЕТИЧНО ИЗСЛЕДВАНЕ

The Great Book of Music (Kitab al-Musiqa al-Kabir), by the Golden Age Islamic philosopher al-Farabi, is a X th. century treatise on music in Arabic. It consists of two parts, the first being an introduction in which the definition of melody and its subdivisions, the origin of music, and some acoustic problems are discussed. The second part is devoted to the specifics of musical instruments popular among Arabs, the variety of rhythms, and the composition of melodies. Influenced by Pythagoras' theory of harmonic relationships, Farabi gives us a detailed definition of music, reveals its categories, and describes the elements from which a musical work is formed. The author systematically and subversively explains the importance of induction, and supports his theory emphatically by evidence, asserting that many of the principles he derives are acquired through sense experience, as in astronomy, optics, medicine, and other sciences.

Glocalization: The Development and Localization of Chinese Christian Hymns between 1807 and 1949

The global dissemination of Christianity has resulted in diverse singing styles and historical narratives that incorporate different languages and musical traditions. Chinese Christian hymns, in particular, possess distinctive features that reflect the Chinese thinking mode and cultural values, showcasing the interplay between Western hymns and Chinese singing and poetic and cultural traditions within the Chinese historical context. This paper takes Chinese Christian hymnals published between 1807 and 1949 as its object of study. It conducts research on representative hymnals from three historical stages: the emergence, flourishing, and prosperity of hymns, and examines their compilation and publication. Using methods such as historical research, textual criticism, translation studies, and cross-cultural communication, the paper explores the evolution of Chinese Christian hymns. The paper analyzes such aspects of the hymnals as translating and writing strategies, thematic content, linguistic features, editing and formatting, as well as the selection and composition of melodies. It is concluded that the indigenization of Chinese hymns does not involve outright rejection of foreign elements or unquestioning adherence to local traditions, but rather represents a common ground between Chinese and Western languages and vocal traditions, reflecting the characteristic of glocalization.

비전공자를 위한 작곡 교양교과목 개발 운영 사례연구

This study aims to discuss the various advantages and problems that have emerged through the development and operation of a course called “Understanding Music through Composition Experience”, which was opened as a liberal arts course for college students without majoring in music at universities, and to suggest directions for development and improvement. In this three-step class, “Basic Music Theory, Melody Composition Method, Garage Band Application”, the basic music theory essential for composition was found out through the course operation, and melody composed by students were compared according to Schoenberg's tonal music composition theory. I tried to apply the melody and harmony created here to the Garage Band, and analyzed the satisfaction of the students. In conclusion, basic music theory regarding tonality, scale, and pitch interval is considered important for practical composition ability, more practice on rhythm and time is required, and emphasis should be placed on harmony with chords in melody composition. This study is meaningful in suggesting future development directions for creative music classes as liberal arts subjects in universities and class design using smart phone application.

Three applications of analysis-by-synthesis in music science

The article describes how my research has applied the analysis-by-synthesis strategy to (1) the composition of melodies in the style of nursery tunes, (2) music performance and (3) vocal singing. The descriptions are formulated as generative grammars, which consist of a set of ordered, context-dependent rules capable of producing sound examples. These examples readily reveal observable weaknesses in the descriptions, the origins of which can be traced in the rule system and eliminated. The grammar describing the compositional style of the nursery tunes demonstrates the paramount relevance of a hierarchical structure. Principles underlying the transformation from a music score file to a synthesized performance are derived from recommendations by a violinist and music performance coach, and can thus be regarded as a description of his professional skills as musician and pedagogue. Also in this case the grammar demonstrates the relevance of a hierarchical structure in terms of grouping, and reflects the role of expectation in music listening. The rule system describing singing voice synthesis specifies acoustic characteristics of performance details. The descriptions are complemented by sound examples illustrating the effects of identified compositional and performance rules in the genres analysed.

Mono-objective Evolutionary Model for Affective Algorithmic Composition

The Affective Music Composition study indicates that musical features can be associated to emotions. Thus, Affective Algorithmic Composition systems implements such features in order to generate melodies that can express or induce emotions. These systems can be applied to different fields, like health and entertainment. However, the composition of melodies with unlimited duration time and diversity is still an open question. This work aims to identify strategies to perform multiple affective transformations in melodies. Therefore, emotional models and the most implemented musical features in the literature are presented, as well as a evolutionary mono-objective model to an affective transformative system.

Stylistic Composition of Melodies Based on a Brain-Inspired Spiking Neural Network.

Current neural network based algorithmic composition methods are very different compared to human brain's composition process, while the biological plausibility of composition and generative models are essential for the future of Artificial Intelligence. To explore this problem, this paper presents a spiking neural network based on the inspiration from brain structures and musical information processing mechanisms at multiple scales. Unlike previous methods, our model has three novel characteristics: (1) Inspired by brain structures, multiple brain regions with different cognitive functions, including musical memory and knowledge learning, are simulated and cooperated to generate stylistic melodies. A hierarchical neural network is constructed to formulate musical knowledge. (2) Biologically plausible neural model is employed to construct the network and synaptic connections are modulated using spike-timing-dependent plasticity (STDP) learning rule. Besides, brain oscillation activities with different frequencies perform importantly during the learning and generating process. (3) Based on significant musical memory and knowledge learning, genre-based and composer-based melody composition can be achieved by different neural circuits, the experiments show that the model can compose melodies with different styles of composers or genres.

Usage of Deep Learning and Blockchain in Compilation and Copyright Protection of Digital Music

In order to explore the application of deep learning algorithms in arrangement and composition, and the role of blockchain in the protection of digital music copyright, a monophonic melody composition model based on the deep generative adversarial networks (DCGANs) is constructed firstly, and the composition performance of the model is analyzed using hymn as input sample in this study. Later, the multi-instrument co-arrangement (MICA) model based on the multi-task learning is proposed, and the composition performance is analyzed by taking the actual music as an input sample. Finally, the improved practical byzantine fault tolerance (IPBFT) algorithm is proposed, and a digital music copyright protection system is designed based on the blockchain in this study. The results indicate that the accuracies constructed DCGANs model in predicting the Soprano and Alto voice melody are higher than those of the DeepBatch model by 2.29% and 3.32%, respectively. The performance on the harmony score, note accuracy, Levenshtein similarity (LS), notes distribution mean square error, and empty as well as the convergence speed of the constructed MICA model are better than those of other models. The average transaction per second (TPS) value of the proposed IPBFT algorithm in the real digital music copyright protection system is 3469, which is superior to other blockchain technologies. Finally, the digital music copyright protection system is achieved, the error rate of completing the request is 0% in the state of many users operating concurrently, and a high TPS value can be guaranteed. In short, the DCGANs and MICA models pointed out in this study can be used in the composition of monophonic melodies and complex melodies, and the digital music copyright protection system based on the blockchain has excellent performance in practical applications.

Automatic Melody Composition Using Enhanced GAN

In traditional music composition, the composer has a special knowledge of music and combines emotion and creative experience to create music. As computer technology has evolved, various music-related technologies have been developed. To create new music, a considerable amount of time is required. Therefore, a system is required that can automatically compose music from input music. This study proposes a novel melody composition method that enhanced the original generative adversarial network (GAN) model based on individual bars. Two discriminators were used to form the enhanced GAN model: one was a long short-term memory (LSTM) model that was used to ensure correlation between the bars, and the other was a convolutional neural network (CNN) model that was used to ensure rationality of the bar structure. Experiments were conducted using bar encoding and the enhanced GAN model to compose a new melody and evaluate the quality of the composition melody. In the evaluation method, the TFIDF algorithm was also used to calculate the structural differences between four types of musical instrument digital interface (MIDI) file (i.e., randomly composed melody, melody composed by the original GAN, melody composed by the proposed method, and the real melody). Using the TFIDF algorithm, the structures of the melody composed were compared by the proposed method with the real melody and the structure of the traditional melody was compared with the structure of the real melody. The experimental results showed that the melody composed by the proposed method had more similarity with real melody structure with a difference of only 8% than that of the traditional melody structure.

A multi-objective evolutionary approach to automatic melody generation

Abstract Existing evolutionary approaches to automatic composition generate only a few melodies in a certain style that is specified by the setting of parameters or the design of fitness functions. Thus, their composition results cannot cover the various tastes of music. In addition, they are not able to deal with the multidimensional nature of music. This paper presents a novel multi-objective evolutionary approach to automatic melody composition in order to produce a variety of melodies at once. To this end, two conflicting fitness measures are investigated to evaluate the fitness of melody; (1) stability and (2) tension . Resorting to music theory, genetic operators (i.e., crossover and mutation) are newly designed to improve search capability in the multi-objective fitness space of music composition. The experimental results demonstrate the validity and effectiveness of the proposed approach. Moreover, the analysis of composition results proves that the proposed approach generates a set of pleasant and diverse melodies.

An Analysis of Melody Composition Process and Product by Different Music Making Tools

본 연구는 음악소프트웨어 프로그램이 초등학생의 음악창작 과정과 결과에 미치는 영향을 탐색하였다. 연구는 대전 소재 초등학교 4학년 학생 10명을 대상으로, 건반악기와 소프트웨어를 사용하여 음악창작을 하고 그 과정과 결과를 비교분석하였다. 연구 결과 창작과정 범주 중 기보여부, 탐색 방식, 친숙한 선율 사용 등에서 창작도구 간 차이를 보였고, 창작결과 범주에서는 리듬패턴 사용에서 차이를 보였다. 특히 많은 학생들이 Music pro를 사용했을 때 가락 만들기-듣기의 과정을 반복하였다. 이와 같은 연구결과는 음악창작에서 테크놀로지의 활용, 특히 음악능력 하위집단에서 테크노로지의 유용함을 보여주는 것이라 할 수 있다.The development of computer technology and MIDI software has a lot of influence on music education. Especially students can make music composition more easily and efficiently than before. Like this, there are much of research about the effects of technology. But the comparative study of non-technological music compositions and technological music compositions is not yet carried out. So this study analysed melody composition process and product. 4th grade students made melodies by different tools : keyboard and music software program, music pro 4.0. As a results, They showed some meaningful differences in exploration behaviors, rhythmic features. And students felt more comfortable and interested in music pro composition than keyboard composition.

Algorithmically-generated Corpora that use Serial Compositional Principles Can Contribute to the Modeling of Sequential Pitch Structure in Non-tonal Music

We investigate whether pitch sequences in non-tonal music can be modeled by an information-theoretic approach using algorithmically-generated melodic sequences, made according to 12-tone serial principles, as the training corpus. This is potentially useful, because symbolic corpora of non-tonal music are not readily available. A non-tonal corpus of serially-composed melodies was constructed algorithmically using classic principles of 12-tone music, including prime, inversion, retrograde and retrograde inversion transforms. A similar algorithm generated a tonal melodic corpus of tonal transformations, in each case based on a novel tonal melody and expressed in alternating major keys. A cognitive model of auditory expectation (IDyOM) was used first to analyze the sequential pitch structure of the corpora, in some cases with pre-training on established tonal folk-song corpora (Essen, Schaffrath, 1995). The two algorithmic corpora can be distinguished in terms of their information content, and they were quite different from random corpora and from the folk-song corpus. We then demonstrate that the algorithmic serial corpora can assist modeling of canonical non-tonal compositions by Webern and Schoenberg, and also non-tonal segments of improvisations by skilled musicians. Separately, we developed the process of algorithmic melody composition into a software system (the Serial Collaborator) capable of generating multi-stranded serial keyboard music. Corpora of such keyboard compositions based either on the non-tonal or the tonal melodic corpora were generated and assessed for their information-theoretic modeling properties.

유전알고리즘 기반의 사용자 파라미터 설정과 코드 진행을 고려한 리듬과 멜로디 자동 작곡 시스템

본 논문에서는 주어진 코드 진행에서 비화성음을 활용한 화려한 멜로디를 자동으로 생성하는 새로운 진화적 자동 음악 작곡 시스템을 제안한다. 전체 시스템은 리듬 생성과 멜로디 생성의 두 단계로 나누어지며, 사용자 설정 파라미터로 제어되는 리듬 적합도 평가 함수와 화성학 기반으로 설계된 멜로디 적합도 평가 함수, 그리고 멜로디 최적화 성능 향상을 위해 설계된 음악적 문맥을 고려한 진화연산을 소개한다. 제안하는 리듬 적합도 평가 함수의 최적화에서 표준 유전알고리즘과 엘리티즘이 적용된 유전알고리즘, 차분진화 알고리즘, 그리고 입자군집최적화 알고리즘의 비교 실험을 하였으며, 멜로디 적합도 평가함수 최적화에서 위 4가지 알고리즘과 제안하는 진화연산을 적용한 유전알고리즘과의 비교 실험을 통해 성능을 검증하고, 생성된 멜로디에 대한 음악적 분석을 수행하였다.

Memetic Music Composition

Computers and artificial intelligence play a key role in the production of artwork through the designing of synthetic agents that are able to reproduce the capabilities of human artists in assembling high-quality artefacts such as paintings and sculptures. In this context, music composition represents one of the art disciplines that can greatly benefit from the appropriate use of computational intelligence, as witnessed by the large number of research activities performed in this field over the recent years. Nevertheless, the automatic composition of music is far from being completely and precisely perfected due to the intrinsic virtuosity that characterizes human musicians’ capabilities. This paper reduces this gap with the proposal of an intelligent scheme for the efficient composition of melodies based on a musical method that is inspired by and strongly characterized by human virtuosity: the unfigured bass technique. In particular, we formulate this music composition technique as an optimization problem and solve it with an adaptive multiagent memetic approach comprising diverse metaheuristics, the composer agents that cooperate to create high-quality four-voice pieces of music starting from a bass line as input. A collection of experimental studies on the famous Bach’s four-voice chorales showed that the cooperation among different optimization strategies yields improved performance over the solutions obtained by conventional and hybrid evolutionary algorithms.

Automatic melody composition based on a probabilistic model of music style and harmonic rules

The aim of the present work is to perform a step towards the design of specific algorithms and methods for automatic music generation. A novel probabilistic model for the characterization of music learned from music samples is designed. This model makes use of automatically extracted music parameters, namely tempo, time signature, rhythmic patterns and pitch contours, to characterize music. Specifically, learned rhythmic patterns and pitch contours are employed to characterize music styles. Then, a novel autonomous music compositor that generates new melodies using the model developed will be presented. The methods proposed in this paper take into consideration different aspects related to the traditional way in which music is composed by humans such as harmony evolution and structure repetitions and apply them together with the probabilistic reutilization of rhythm patterns and pitch contours learned beforehand to compose music pieces.

Automatic composition of happy melodies based on relations

To compose some happy melodies which have hierarchical structures, this paper proposes an automatic melody composition algorithm based on relations. First, various types of melody structure are formalized and saved into a database, so the melody structure form preferred by a user can be elected by human-computer interaction. Second, some sequences of trunk-note and several algorithms of splitting note are constructed by means of the pitch interval features of happy melody, and the theme phrase of happy melody is generated by splitting some trunk notes of the trunk-note-sequence. Third, several types of operators for developing the theme phrase, which include pitch offsetting, phrase inversing and repeating-developing, are constructed using relationship methods. Finally, under the guidance of the elected melody structure, some happy melodies of songs are produced automatically by the interreaction of the theme phrase and these operators. Experimental results demonstrate that this algorithm can make the obtained melodies have musically meaningful structures, and it is not easy to distinguish these machine-generated melodies from human-generated melodies.

‘Nsumwinu’: meaning and role in the structural composition of melodies in the urban music of the Democratic Republic of the Congo

The examination of the inserted nsumwinu (singular - Kasumwinu), in the lyrics of popular songs in the Democratic Republic of the Congo (DRC), reveals hidden roles that are both musical and linguistic. Musically, the compositional technique of the melodic contour is derived from the observation of the semantic level of the language represented by the sequential pattern of tones on words that compose the kasumwinu. Linguistically, this sequential pattern of tones that determines the meaning of the word, must be faithfully observed in the music’s compositional process of the basic melodic contour, i.e., the linguistic tones dictate the direction of musical intervals, leaving the decision of the size of the interval to the creative discretion of the composer.1 This essay will reveal the linguistic significance and role of nsumwinu, in the urban music of the DRC, and to conclude that they provide the musical flexibility without altering the overall meaning of their intended message.

Characterizing chaotic melodies in automatic music composition

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests.

音楽で「遊ぶ」ことを目的とした作曲システムの構築に関する検討

In this paper, we propose an automatic composing system by using chaotic neural network. Chaotic neural network is possessed of a function as associative memory, so we apply the associative memory to automatic composition of melodies. User interface of proposed system “Chaotic Music Composer”is very simple and straightforward because an aim of the system is that it is pleasure to use it for people who aren't familiar with music composition and how to use computers. Users of the system can get some new melodies only by “selecting”and “listening”melodies which are given by the system. They select some favorite melodies from melody database, and put them into the system. The system divides the melodies into two elements, which are pitch of note and length of note, and memorizes those elements separately. The system generates pitch parts and length parts from inputted random patterns, and makes a piece of phrase compounded from two parts. In this way, user gets some phrase, and makes a piece of melody with arranging those phrases.

Making Music with Algorithms: A Case-Study System

19 Computer Music Journal, 23:2, pp. 19–30, Summer 1999 © 1999 Massachusetts Institute of Technology. Musicians, perhaps more so than any other group of artists, have always been quick to embrace technology in all its forms. From early attempts at synthesis with the Telharmonium (Roads 1996) to the latest digital-audio workstations (see, for example, Lehrman 1997; Manning 1993), musicians have looked to science to provide them with new and challenging ways of working. One composition method that has benefited greatly from advances in technology is algorithmic composition. Algorithmic composition is by no means new—formal techniques for melody composition date back to at least 1026, when Guido d’Arezzo proposed a scheme that assigned pitches to each vowel sound in a religious text (Loy 1989)—but the advent of affordable and powerful computing resources has meant that more and more people, armed with no more than a little programming knowledge and some musical ideas, have been able to realize their composition algorithms from the comfort of their own desktops. The use of computers as composition generators was pioneered in the mid-1950s by such people as Lejaren Hiller (Hiller and Isaacson 1959), whose 1956 work, The Illiac Suite for String Quartet, is recognized as being the first computer-composed composition. Iannis Xenakis (Xenakis 1960, 1971), although not the first to publish a computer-composed work, had been composing stochastically generated pieces by hand for some time before the premier of The Illiac Suite. Later, Gottfried Koenig developed the Project 1 and 2 composition programs (Koenig 1970a, b). Computer-based algorithmic composition continues the post-war trend toward formalized and systematic composition methods, such as Arnold Schoenberg’s tone-row and Anton Webern’s serialism methods (Roads 1996). Considered thus, it is apparent that the computer is merely a tool for the realization of abstract design constructs, and is best employed as a labor-saving device to free the composer from performing menial calculations by hand. Using a computer, it is possible to preview and test the musical capabilities of many different algorithmic types and judge whether they have the potential to be developed into full-fledged composition systems. This is also the view subscribed to by the authors. Computers in music, and indeed, the algorithmic composition systems themselves, are best thought of as composition tools rather than one-stop music solutions. It was with this in mind that we developed CAMUS 3D, a composition system of our own design that likens the process of music composition to that of pattern propagation. In this article, we introduce the system and show how two classes of algorithms are used to generate musical data.

Towards a Theory of Melody

Given a certain well-defined class of melodies, what are the principles and laws by means of which the metric, harmonic, and tonal facts of these melodies can be derived? The present paper describes an attempt to formulate such a system of rules that specify the logical organization of melodic structure in a set of Swedish nursery songs. Our approach is based on the assumption that fundamental rules of linguistic prosody underlie the composition of such melodies. A large body of metric, harmonic, and tonal data can be accounted for with the aid of this assumption. Our results indicate many parallels between the organization of linguistic and musical structure and support the idea that musical processes cannot be adequately described in terms of Markovian or stochastic models; rather, our results indicate that available evidence suggests that the formal machinery developed within the study of language may turn out to be of value also in the construction of future theories of music. The paper contains taped illustrations of melodies that can be generated with the present system of rules.