Music System Research Articles

Towards decolonising university music education in Nigeria

ABSTRACT This article argues that coloniality is an ongoing feature of university music education in Nigeria. It uses a multiple colonialisms framework in exploring Nigerian higher music education systems as historical and contemporary sites of colonialism within which Nigerian universities engage in music knowledge generation to reach this conclusion. It relies on information gleaned from scholarly sources. It shows that the dominance of Euro-American classical musical practice in bicultural university music education in Nigeria since 1961 has received little questioning. It identifies decolonisation as indigenisation, Africanisation, Islamisation, Nigerianisation and globalisation of university music education discourses as competing with this dominant paradigm. From the anti-colonial perspective, it argues that these six Nigerian music knowledge systems should not be simply celebrated, valorised and utilised. They should be critically engaged, interrogated, transformed, altered if necessary, and studied relationally, contextually and comparatively. Decolonising university music education in any society, it posits, involves centring music knowledge creation, understanding and sharing on multiplicity and entanglements.

On the Application of Artistic Songs in Vocal Music Teaching in Colleges and Universities

In the course of thousands of years of development, China's history has produced a wealth of artistic content. National culture, as a magnificent treasure in art, embodies its corresponding value. As an important part of China’s music system, art songs have shown more unique artistic characteristics and are an extremely important part of Chinese music culture. In the teaching of vocal music in colleges and universities, the teaching of art songs cannot be ignored. It needs to be analyzed accordingly to understand the importance of effective integration of art songs in vocal music teaching in colleges and universities in China, and put forward the corresponding integration of art songs in vocal music teaching in colleges and universities based on the actual situation. In the end, it can make the vocal music teaching system in colleges and universities more complete, and the application value of art songs will be more obvious.

Statistical Analysis of Human Emotions to Suggest Suitable Music as per Individual's Mood

There is music recommendation software and music providers that are well explored and commonly used, but those are generally based on simple similarity calculations and manually tagged parameters. This project proposes a music recommendation system based on emotion detection of users, automatic computing, and classification. Music is recommended based on the emotion expressed and temper of the user. Like artists and genre, emotion of the user can also be a crucial recommendation point for music listeners. The different mооds in whiсh the system will сlаssify the imаges аre hаррy, neutrаl, аnd sаd. The system will рre-sоrt the songs according to their genre in the above-mentioned categories. This research project gives us advancement in the music industry with the help of machine learning and artificial intelligence and will reduce the hassle of selecting songs in our leisure time and will automatically play songs by detecting the emotion of the user. This data can be used to play the songs that match the current mood detected from the provided input by the user.

Maxine’s Turing Test – A Player-Program as Co-Ethnographer of Socio-Aesthetic Interaction in Improvised Music

Beyond the goal of refining system design to the needs and tastes of users, user evaluation of interactive music systems offers a method of examining the nature of musical creativity as understood by its human practitioners. In the case of improvising music systems, user study and evaluation of a system’s ability to improvise may be useful in the ethnomusicological study of musical interaction in contemporary improvised music. A survey of preliminary findings based on the interactions of an improvising system, Maxine, with several improvisers is discussed, with results suggesting methodological reconfigurations of the purpose and goals of evaluating of interactive musical metacreations.

Prediction and Proactivity in Real-Time Interactive Music Systems

We advocate for the use of predictive techniques in interactive computer music systems. We suggest that the inclusion of prediction can assist in the design of proactive rather than reactive computational performance partners. We summarize the significant role prediction plays in human musical decisions, and the only modest use of prediction in interactive music systems to date. After describing how we are working toward employing predictive processes in our own metacreation software we reflect on future extensions to these approaches.

The Generative Electronic Dance Music Algorithmic System (GEDMAS)

The Generative Electronic Dance Music Algorithmic System (GEDMAS) is a generative music system that composes full Electronic Dance Music (EDM) compositions. The compositions are based on a corpus of transcribed musical data collected through a process of detailed human transcription. This corpus data is used to analyze genre-specific characteristics associated with EDM styles. GEDMAS uses probabilistic and first order Markov chain models to generate song form structures, chord progressions, melodies and rhythms. The system is integrated with Ableton Live, and allows its user to select one or several songs from the corpus, and generate a 16 tracks/parts composition in a few clicks.

Autonomy in Music-Generating Systems

The word autonomy is often used in the discussion of software-based music-generating systems. Whilst the term conveys a very clear concept — the sense of self-determination of a system — attempts to formalise autonomy are at an early stage, and the term is subject to a range of interpretations when practically applied. We consider how the evaluation of music-generating systems will be enhanced by a clearer understanding of autonomy and its application to music. We discuss existing definitions and approaches to quantifying autonomy and consider, through a series of examples, the information that is required in order to make precise formal judgements about autonomy, and the identification of relevant levels at which the principle of autonomy applies in music. We conclude that automated measures can supplement human evaluation of autonomy, but that (a) automated measures must be supported by sound reasoning about the features and timescales used in the measurement, and (b) they are improved by a having knowledge of the internal working of the system, rather than taking a black box approach. We consider multi-dimensional representations of system behaviour that may capture a richer sense of the notion of autonomy. Finally, we propose an approach to automatically probing music systems as a means of determining an autonomy `portrait'.

Quantum Composition and Improvisation

Quantum mechanical systems exist as superpositions of complementary states that collapse to classical, concrete states upon becoming entangled with the measurement apparatus of observer-participants. A musical composition and its performance constitute a quantum system. Historically, conventional musical notation has presented the appearance of a composition as a deterministic, concrete entity, with interpretation approached as an extrinsic act. This historical perspective inhabits a subspace of the available quantum space. A quantum musical system unifies the composition, instruments, situated performance and perception as a superposition of musical events that collapses to concrete musical events via the interactions and perceptions of performers and audience. A composer captures superposed musical events via implicit or explicit conditional event probabilities, and human and/or machine performers create music by collapsing interrelated probabilities to zeros and ones via observer-participancy.

Virtud, alma y música: Plat., R., 443d y los desarrollos filosóficos posteriores

From his soul-dividing model (through a comparison with music 443d) Plato presents in the Republic the predominance of certain virtues in each part and its political meaning. This idea is later developed by other Greek philosophical schools in imperial time. Plutarch’s commentary on the Platonic passage let us know how Neoplatonists, Neo-Pythagoreans and Stoics have enriched the identification between Soul and Virtue with elements taken from the musical system and from the latestdoctrine on virtues, even establishing links with theory of knowledge.

Virtud, alma y música: Plat., R., 443d y los desarrollos filosóficos posteriores

From his soul-dividing model (through a comparison with music 443d) Plato presents in the Republic the predominance of certain virtues in each part and its political meaning. This idea is later developed by other Greek philosophical schools in imperial time. Plutarch’s commentary on the Platonic passage let us know how Neoplatonists, Neo-Pythagoreans and Stoics have enriched the identification between Soul and Virtue with elements taken from the musical system and from the latestdoctrine on virtues, even establishing links with theory of knowledge.

Guided Music Synthesis with Variable Markov Oracle

In this work the problem of guided improvisation is approached and elaborated; then a new method, Variable Markov Oracle, for guided music synthesis is proposed as the first step to tackle the guided improvisation problem. Variable Markov Oracle is based on previous results from Audio Oracle, which is a fast indexing and recombination method of repeating sub-clips in an audio signal. The newly proposed Variable Markov Oracle is capable of identifying inherent datapoint clusters in an audio signal while tracking the sequential relations among clusters at the same time. With a target audio signal indexed by Variable Markov Oracle, a query-matching algorithm is devised to synthesize new music materials by recombination of the target audio matched to a query audio. This approach makes the query-matching algorithm a solution to the guided music synthesis problem. The query-matching algorithm is efficient and intelligent since it follows the inherent clusters discovered by Variable Markov Oracle, creating a query-by-content result which allows numerous applications in concatenative synthesis, machine improvisation and interactive music system. Examples of using Variable Markov Oracle to synthesize new musical materials based on given music signals in the style of Jazz are shown.

Appropriating Biosensors as Embodied Control Structures in Interactive Music Systems

We present a scoping review of biosensors appropriation as control structures in interactive music systems (IMSs). Technical and artistic dimensions promoted by transdisciplinary approaches, ranging from biomedicine to musical performance and interaction design fields, support a taxonomy for biosensor-driven IMSs. A broad catalog of 70 biosensor-driven IMSs, ranging in publication dates from 1965 to 2019, was compiled and categorized according to the proposed taxonomy. From the catalog data, we extrapolated representative historical trends, notably to critically verify our working hypothesis that biosensing technologies are expanding the array of control structures within IMSs. Observed data show that our hypothesis is consistent with the historical evolution of the biosensor-driven IMSs. From our findings, we advance future challenges for novel means of control across humans and machines that should ultimately transform the agents involved in interactive music creation to form new corporalities in extended performative settings.

Streaming’s Effects on Music Culture: Old Anxieties and New Simplifications

This article identifies five key themes, or sets of criticisms, that have emerged in online commentary on the new musical system centred on streaming platforms, and in related academic research: Streaming encourages ‘functional’ rather than meaningful, aesthetic musical experience. Streaming encourages bland, unchallenging music. Streaming makes musical experience passive and distracted, and music recedes into the background (here the article also discusses limitations of the widely used concepts of ‘ubiquitous music’ and ‘ubiquitous listening’). Streaming makes music tracks and songs shorter, and musical experience more fragmented. Streaming discourages and/or limits musical discovery and adventurousness. The article addresses each of these themes in turn, examining the degree to which criticisms of streaming’s effects on musical experience along these lines might be considered valid, and the degree to which they might genuinely enhance critical understanding of contemporary musical experience. It also considers these themes in relation to older forms of evaluation, particularly those that developed in the 20th century in response to the industrialisation of music, and argues that many recent criticisms problematically reproduce older anxieties and assumptions.

Artificial intelligence-based classification with classical Turkish music makams: Possibilities to Turkish music education

Makams of Classical Turkish Music have been tried to be classified through various studies for the past years. Significant differences of opinion have emerged in the classification process of the makams in Music Education and Literacy from past to present. This situation creates problems in learning the makams related to music education and recognizing the makams heard. Additionally, there are uncertainties in the classification of the makam genre of the song, as individual mistakes were made while notating the musical notes. Apart from that, this situation constitutes a problem not only for the ones studying Turkish Classical Music but also for the ones interested in this certain type of Music. Therefore, the objective of the research is to contribute to the makam classification in Classical Turkish Music Education by developing an MIR system that determines the makam of the songs. Theoretically, we can extract the properties of sound signals with Time Wavelet Scattering Feature Extraction, classify them with SVM and distinguish between types of makams. In this study, upon eight different Makams, a Musical Information Retrieval system has been created via the Artificial Intelligence (AI) method of Support Vector Machines (SVM) and Time Wavelet Scattering Feature Extraction and through using a Graphics Processing Unit (GPU) accelerator for the sake of feature extraction. We performed the classification process by modeling it on the MATLAB program. The study's success rate was identified as 98.21% and it acquired a higher success rate compared to the other studies in the literature. After completing the classification procedure, the Makams were identified by sending samples belonging to different sound files from the system consisting of a database belonging to eight different Makams. In our study, the classification and detection processes were realized with nearly a hundred percent success. The difficulties encountered in classifying the makams in Classical Turkish Music mentioned above, with the application of artificial intelligence, the classification difficulty of individuals who have received this type of training or are interested in this subject has been overcome.

Agostino Di Scipio and Dario Sanfilippo: Machine Milieu

Agostino Di Scipio and Dario Sanfilippo: Machine Milieu

WITHDRAWN: Music Composition Feasibility using a Quality Classification Model based on Artificial Intelligence

There are several explanations for building music systems, including computer-generated settings, playing musical instruments, reflecting on the art of sound recordings, and others. The main challenge in music composition identifies the student's time, and it shows dissatisfaction with their lack of basic musical skills. The music compositions help develop a student's greater stronger vocabulary to determine that they are rising musicians. Therefore, this paper suggests the Music Composition and Melody Generation Adjustable (MCMGA) structure develop adaptive music. MCMGA's main objective is to build music in real-time that reflects various moods that can accomplish through a single combination of the chord-sequence generator on a cross graph. A search melody predictor and an emotional-expression concept have been analysed. Melody generation uses a novel technique for evolution that combines the Feasible Population Method (FPM) with vector optimization. FPM helps to explore a Pareto front of various solutions under vector optimization functions that are creatively equivalent. To test the program, two quantitative user studies are carried out. The first is based on music generation and the second on valence expression by adding dissonances. The study's outcome shows that every other part of the production and propagation increases the perceptual quality of the generated music and the relative effectiveness of the interpretation of reactivity through dissonance based on these parameters music experience 96.7%, usability and accessibility 98.4%, interaction analysis 99.5%, music teaching analysis 96.3%, music performance anxiety analysis 29.8% Stage fright analysis 22.5%. • A search melody predictor and an emotional-expression concept have been analysed. • To test the program, two quantitative user studies are carried out. • Vector optimization is simply interpreted and self-explaining of music algorithms.

Matching Subsequence Music Retrieval in a Software Integration Environment

This paper firstly introduces the basic knowledge of music, proposes the detailed design of a music retrieval system based on the knowledge of music, and analyzes the feature extraction algorithm and matching algorithm by using the features of music. Feature extraction of audio data is the important research of this paper. In this paper, the main melody features, MFCC features, GFCC features, and rhythm features, are extracted from audio data and a feature fusion algorithm is proposed to achieve the fusion of GFCC features and rhythm features to form new features under the processing of principal component analysis (PCA) dimensionality reduction. After learning the main melody features, MFCC features, GFCC features, and rhythm features, based on the property that PCA dimensionality reduction can effectively reduce noise and improve retrieval efficiency, this paper proposes vector fusion by dimensionality reduction of GFCC features and rhythm features. The matching retrieval of audio features is an important task in music retrieval. In this paper, the DTW algorithm is chosen as the main algorithm for retrieving music. The classification retrieval of music is also achieved by the K-nearest neighbor algorithm. In this paper, after implementing the research and improvement of algorithms, these algorithms are integrated into the system to achieve audio preprocessing, feature extraction, feature postprocessing, and matching retrieval. This article uses 100 different kinds of MP3 format music as the music library and randomly selects 4 pieces each time, and it tests the system under different system parameters, recording duration, and environmental noise. Through the research of this paper, the efficiency of music retrieval is improved and theoretical support is provided for the design of music retrieval software integration system.

Music Rhythm Detection Algorithm Based on Multipath Search and Cluster Analysis

Music rhythm detection and tracking is an important part of the music comprehension system and visualization system. The music signal is subjected to a short-time Fourier transform to obtain the frequency spectrum. According to the perception characteristics of the human auditory system, the spectrum amplitude is logarithmically processed, and the endpoint intensity curve and the phase information of the peak value are output through half-wave rectification. The Pulse Code Modulation (PCM) characteristic value is extracted according to the autocorrelation characteristic of the endpoint intensity curve. This article proposes a rhythm detection algorithm based on multipath search and cluster analysis; that is, based on the clustering algorithm, it absorbs the idea of multipath tracking and proposes its own detection and tracking algorithm. It overcomes the weakness of the clustering algorithm that needs to use Musical Instrument Digital Interface (MIDI) auxiliary input to achieve the desired effect. This algorithm completely uses the PCM signal as the input, which is more robust than the clustering algorithm. The whole process is carried out in the time domain, and the amount of calculation is much smaller than the frequency domain calculation of multipath tracking, and the linear relationship with the rhythm of the music is much better than the filter bank algorithm. This algorithm can successfully detect the rhythm of the music with a strong sense of rhythm and can track the specific position of the rhythm point.

Semiotic hybridization in Persian poetry and Iranian music

Abstract This article demonstrates how Iranian classical music and Persian medieval poetry, taken as separate semiotic systems, form together, in certain contexts, a single hybrid semiotic system with overlapping structural features and shared aesthetic principles. Hjelmslev’s description of connotative semiotic systems serves as a theoretical framework to show the modalities of this hybridization. This phenomenon can be observed through comparative analysis of the interdependence of poetry and music in the Persianate World from a semiotic point of view. On the one hand, the quantitative (chronemic) meter of the Persian classical versification, called ‘aruz, as well as its extraordinarily heavy use of rhyme display a formal structure that evokes that of a musical phrase. On the other hand, the dependence of the structure of the Iranian musical system upon the rhythmic structure of classical poetry suggests a unique character of which few examples exist. This interdependence manifests itself particularly in the mystic (Sufi) poetry of the medieval period, specifically in the work of such renowned poets as Rumi, Sa’di Shirāzi, and Hāfez, who are among the best-known in the West. Examples of their lyric works are examined here to demonstrate occurrences of the collusion between the two semiotic systems.

Evaluative conditioning of responses to unfamiliar chords by exposure to valenced images

The extent to which emotional responses to musical elements are influenced by their past associations with specific emotional responses is largely unknown. To assess this possibility, the present study tested whether pairing positive, negative, or neutral chords from an unfamiliar musical system (a microtonal Bohlen–Pierce tuning) with positively or negatively valenced pictures would have an effect on subsequent liking ratings. The microtonal chords used in this experiment had been previously rated, independent of any other affective input, in an earlier experiment; this allows us to class each chord as intrinsically positive, negative, or neutral. It was found that exposure with an image increases liking ratings independent of the valence of the images, compared with no exposure which supports a mere exposure effect; but, interestingly, we did not find substantial evidence for evaluative conditioning. Results are discussed in light of theoretical accounts of evaluative conditioning and musical implications.