Electronic Music Production Research Articles

Fuzzy Cluster Pitch Synthesis System for the Violin Sound with Machine Learning

Pitch synthesis with violin sound involves the generation of musical pitches using technology to mimic the distinctive tonal characteristics of a violin. This process typically employs digital signal processing techniques to recreate the timbre, articulation, and nuances of a real violin. Advanced algorithms analyze and model the acoustic properties of a violin sound, allowing for the synthesis of realistic pitch variations and expressive qualities. Whether utilized in electronic music production, virtual instruments, or sound design, pitch synthesis with violin sound aims to emulate the rich and complex sonic palette of the violin, offering musicians and composers versatile tools for creative expression and sonic exploration. In this paper proposed Fuzzy Pitch Clustering Machine Learning (FPC-ML) for the violin Music Pitch Synthesis using Machine Learning. The proposed FPC-ML model uses the Fuzzy Clustering model for the estimation of pitches in the violin music signal. Based on the Fuzzy clustering model membership degree is computed for the proposed FPC-ML for the estimation of the pitch in the violin music. With the estimation of linguistic variables, clustering is performed in the Music signal for the computation of pitches. With the estimated pitches in the violin music, the features are trained in the machine learning model for the classification and estimation of features in the Violin Music. Simulation analysis demonstrated that the proposed FPC-ML model computes the features of the Violin Music Pitch values based on the estimated clustering values synthesis performed for the classification of the Violin Music signal. The proposed FPC-ML technique achieves an accuracy value of 0.98 for the violin signal with an iteration of 20. With the increase in several iterations and epoch, the accuracy of the FPC-ML model is further increased for the synthesis of the Violin Music.

‘This felt more like a conversation’: challenging gender norms in electronic music production through alternative education programs

ABSTRACT This article argues that problematic gender norms in electronic music contexts – namely, their association with masculinity and overrepresentation by cis men – can be subverted through alternative education methods. We use the case study of the Electronic Music Accelerator (EMA) program, run by youth organization The Push in Melbourne, Australia, to illustrate this. Specifically, we evaluate strategies used in the EMA program to teach Ableton and related skills on building electronic music production careers. The EMA s program was designed to increase the numbers of women and gender non-conforming or gender diverse people involved in electronic music production, in response to evidence that these groups continue to be underrepresented in this area. We focus on how so-called soft skills, as opposed to the strictly technical skills normally the main focus in an Ableton course, were taught in this program. In the EMA, rather than insisting that the participants take up a ‘masculine’ attitude to adapt to the existing electronic music scene that is dominated by men, the course presented ways of working with, and even reclaiming, traits perceived as feminine, such as humility and community-mindedness. This approach offers possibilities for reconfiguring expectations in electronic music spaces.

Research on the trend and innovation of electronic music production

Nowadays, the level of science and technology in our country gradually develops, and the corresponding electronic music production is experiencing rapid progress. At present, people's demand for the quality of electronic music production is higher and higher. It should not only give people a good sense of hearing, but also be able to combine with high and new technology for application. Throughout the evolution of Chinese electronic music production, it is not difficult to find that it has experienced a process of gradual improvement of technology and is developing towards the direction of computerization. This paper will briefly introduce the evolution process of electronic music production and traditional technologies such as wave table synthesis, addition synthesis, subtraction synthesis, sampling synthesis, modulation synthesis and other sound synthesis methods, and briefly describe the application of the new ROLI Seaboard technology in electronic music production.

The SoundBike: musical sonification strategies to enhance cyclists’ spontaneous synchronization to external music

The spontaneous tendency of people to synchronize their movements to music is a powerful mechanism useful for the development of strategies for tempo adaptation of simple repetitive movements. In the current article, we contribute to such strategies—applied to cycling—by introducing a new strategy based on the sonification of cyclists’ motor rhythm. For that purpose, we developed the SoundBike, a stationary bike equipped with sensors that allows interactive sonification of cyclists’ motor rhythm using two distinct but compatible sonification methods. One is based on the principle of step sequencers, which are frequently used for electronic music production. The other is based on the Kuramoto model, allowing automatic and continuous phase alignment of beat-annotated music pieces to cyclists’ motor rhythm, i.e., pedal cadence. Apart from an in-depth presentation of the technical aspects of the SoundBike, we present an experimental study in which we investigated whether the SoundBike could enhance spontaneous synchronization of cyclists to external music. The results of this experiment suggest that sonification of cyclists’ motor rhythm may increase their tendency to synchronize to external music, and helps to keep a more stable pedal cadence, compared to the condition of having external music only (without sonification). Although the results are preliminary and should be followed-up by additional experiments to become more conclusive, SoundBike seems anyhow a promising interactive sonification device to assist motor learning and adaptation in the field of sports and motor rehabilitation.

Breakbeats and Backshifts: A Time Series Analysis of Musical Groove

In nearly all human musical traditions, repetitive patterns of amplitude are employed to create specific rhythms. Interactions between multiple rhythmic signals (instruments) can give rise to a phenomenon known as the “groove” — a pronounced cycle of fluctuating loudness and/or timing, which conveys an enjoyable subjective quality to listeners. Understanding the forces which give rise to and govern the groove is a key focus of centuries-old music theory as well as modern digital signal processing. Breakbeats are useful for analysis of musical grooves due to their fast, syncopated phrases (which typically repeat every one or two bars), the interplay between drums and bass, and the nuanced fluctuations in loudness which result in exciting, danceable rhythms. These aspects have contributed to the popularity of breakbeats as the rhythmic core of many diverse styles of contemporary music. However, the characteristic groove of early jazz and funk breakbeats can be difficult to emulate using modern digital sampling and composition technology. Time series analysis provides a robust set of well-tested methods for modeling the behavior of signals across time, and these methods can be readily applied to signals representing the amplitude of recorded music. In this paper I demonstrate that time series methodology, applied to datasets of the amplitude of musical signals, can be used to quantitatively model and estimate the groove, where “groove” is defined as the variation in relative loudness from note to note in a piece of recorded music. I first present a procedure for resampling recordings of musical instruments in a method conducive to discrete-time signal processing for musical analysis. I then present several theoretical models of recorded music where the amplitude of an instrument at time t is a function of its past values, the exogenous input of other instruments, and stochastic error. Several different models are estimated and compared using criteria such as AIC, BIC, and explanatory variable parsimony. Based on these comparisons, I suggest a seasonal autoregressive integrated moving-average model with explanatory variables (SARIMAX) as an efficient modeling strategy for this type of data. I also estimate a simple application of the model using amplitude datasets derived from recorded audio. I demonstrate how the model can be used to determine certain features of a recorded groove, such as the relative influence of specific divisions of musical time on the drummer’s overall dynamics. Finally, I demonstrate that these data and modeling procedures can generate predicted values of musical amplitudes in a statistically robust way. I close with a discussion of the implications of my results in terms of statistics and music theory, the generalizability of the selected model, and potential applications in fields such as electronic music production and sound design. By quantitatively modeling and predicting the groove produced by human musicians, “humanization” of electronic instruments might be achieved in a more robust manner than the simple randomization procedures employed currently.

The Concrete and the Ephemeral of Electronic Music Production

The Concrete and the Ephemeral of Electronic Music Production

Musical Chameleons: Fluency and Flexibility in Online Remix Contests

Musical Chameleons: Fluency and Flexibility in Online Remix Contests

The Use of Density Groups in Electroacoustic Music

While the recent explosion of affordable software has placed powerful electronic music production tools within reach of anyone with a smart phone or a tablet, there are important aspects of music composition that technology has failed to address. In fact, much audio software subtly encourages prefabricated aesthetic solutions via the user interface, resulting in a cookie-cutter approach to music creation. As a result, much of the electronic music we hear today rarely ventures into new territory by exploring new structures. One solution could be to employ a compositional tool that enables a composer to generate new and unusual structures derived from mathematical relationships such as the Fibonacci series, the Golden Ratio or other mathematical patterns found in nature. Luckily, such a tool exists and is part of a vast system of music composition created in the twentieth century by the visionary music theoretician and composer Joseph Schillinger. In this article the author explores a Schillinger technique called ‘composing with density groups’ which can be used to create unique musical structures on paper or in any digital audio workstation (DAW).

The producer as composer: shaping the sounds of popular music

In the 1960s, rock and pop music recording questioned the convention that recordings should recreate the illusion of a concert hall setting. The Wall of Sound that Phil Spector built behind various artists and the intricate eclecticism of George Martin's recordings of the Beatles did not resemble live performances -- in the Albert Hall or elsewhere -- but instead created a new sonic world. The role of the record producer, writes Virgil Moorefield in The Producer as Composer, was evolving from that of organizer to auteur; band members became actors in what Frank Zappa called a movie for your ears. In rock and pop, in the absence of a notated score, the recorded version of a song -- created by the producer in collaboration with the musicians -- became the definitive version. Moorefield, a musician and producer himself, traces this evolution with detailed discussions of works by producers and producer-musicians including Spector and Martin, Brian Eno, Bill Laswell, Trent Reznor, Quincy Jones, and the Chemical Brothers. Underlying the transformation, Moorefield writes, is technological development: new techniques -- tape editing, overdubbing, compression -- and, in the last ten years, inexpensive digital recording equipment that allows artists to become their own producers. What began when rock and pop producers reinvented themselves in the 1960s has continued; Moorefield describes the importance of disco, hip-hop, remixing, and other forms of electronic music production in shaping the sound of contemporary pop. He discusses the making of Pet Sounds and the production of tracks by Public Enemy with equal discernment, drawing on his own years of studio experience. Much has been written about rock and pop in the last 35 years, but hardly any of it deals with what is actually heard in a given pop song. The Producer as Composer tries to unravel the mystery of good pop: why does it sound the way it does?

On the process and aesthetics of sampling in electronic music production

Most scholars writing on the use of samplers express anxiety over the dissolution of boundaries between human-generated and automated musical expression, and focus on the copyright infringement issues surrounding sampling practices without adequately exploring samplists' musical and political goals. Drawing on musical examples from various underground electronic music genres and on interviews with electronic musicians, this essay addresses such questions as: What is a sampler, and how does the sampling process resonate with or diverge from other traditions of instrument-playing? How do electronic musicians use the ‘automated’ mechanisms of digital instruments to achieve nuanced musical expression and cultural commentary? What are some political implications of presenting sampled and processed sounds in a reconfigured compositional environment? By exploring these issues, I hope to counter the over-simplified, uninformed critical claims that sampling is a process of ‘theft’ and ‘automation’, and instead offer insight into the myriad and complex musical and political dimensions of sampling in electronic music production.