An examination of the keyboard technique of Bach, Haydn, Chopin, Scriabin and Prokofiev

Master's Project (M.Mu.) University of Alaska Fairbanks, 2016In this research paper, I will explore the keyboard technique of each composer presented in my recital: J.S. Bach, Franz Joseph Haydn, Frederic Chopin, Alexander Scriabin and Sergei Prokofiev. I hope to elucidate the physical approach used by each composer, and show in turn how that same approach influenced the music of each composer by analyzing the pieces performed in my recital. To understand the distinct technique of the composers, it is important to know some context. The instrument each composer wrote for necessarily influenced their technique and resulting composition. However, the instrument cannot explain every facet of technique, and it becomes necessary to understand the underlying aesthetics of technique. Moving chronologically from Bach to Prokofiev, a general trend of expansion in the use of the hand and arm will be seen throughout. Keyboards became louder and heavier in touch and the hand faced greater reaches in every generation. The technique of Bach and Haydn was largely focused on compact and relaxed hands with distinct finger movements, while Scriabin and Prokofiev at the other end require sweeping gestures that occupy the entire arm. However, it would be too easy to present this progression as a story that technique is only getting better and better, implying that the older composers were inferior to the later. That is simply false. Instead, extended study of each composer shows that many technical principles are universal. The baroque keyboardists were likely playing with more weight than popularly imagined and one cannot play Scriabin with mittens on the hands

Social decision-making driven by artistic explore-exploit tension

We studied social decision-making in the rule-based improvisational dance $There$ $Might$ $Be$ $Others$, where dancers make in-the-moment compositional choices. Rehearsals provided a natural test-bed with communication restricted to non-verbal cues. We observed a key artistic explore-exploit tension in which the dancers switched between exploitation of existing artistic opportunities and riskier exploration of new ones. We investigated how the rules influenced the dynamics using rehearsals together with a model generalized from evolutionary dynamics. We tuned the rules to heighten the tension and modeled nonlinear fitness and feedback dynamics for mutation rate to capture the observed temporal phasing of the dancers' exploration-versus-exploitation. Using bifurcation analysis, we identified key controls of the tension and showed how they could shape the decision-making dynamics of the model much like turning a "dial" in the instructions to the dancers could shape the dance. The investigation became an integral part of the development of the dance

Deep Learning Techniques for Music Generation -- A Survey

This paper is a survey and an analysis of different ways of using deep learning (deep artificial neural networks) to generate musical content. We propose a methodology based on five dimensions for our analysis: Objective - What musical content is to be generated? Examples are: melody, polyphony, accompaniment or counterpoint. - For what destination and for what use? To be performed by a human(s) (in the case of a musical score), or by a machine (in the case of an audio file). Representation - What are the concepts to be manipulated? Examples are: waveform, spectrogram, note, chord, meter and beat. - What format is to be used? Examples are: MIDI, piano roll or text. - How will the representation be encoded? Examples are: scalar, one-hot or many-hot. Architecture - What type(s) of deep neural network is (are) to be used? Examples are: feedforward network, recurrent network, autoencoder or generative adversarial networks. Challenge - What are the limitations and open challenges? Examples are: variability, interactivity and creativity. Strategy - How do we model and control the process of generation? Examples are: single-step feedforward, iterative feedforward, sampling or input manipulation. For each dimension, we conduct a comparative analysis of various models and techniques and we propose some tentative multidimensional typology. This typology is bottom-up, based on the analysis of many existing deep-learning based systems for music generation selected from the relevant literature. These systems are described and are used to exemplify the various choices of objective, representation, architecture, challenge and strategy. The last section includes some discussion and some prospects.Comment: 209 pages. This paper is a simplified version of the book: J.-P. Briot, G. Hadjeres and F.-D. Pachet, Deep Learning Techniques for Music Generation, Computational Synthesis and Creative Systems, Springer, 201

Query-based Deep Improvisation

In this paper we explore techniques for generating new music using a Variational Autoencoder (VAE) neural network that was trained on a corpus of specific style. Instead of randomly sampling the latent states of the network to produce free improvisation, we generate new music by querying the network with musical input in a style different from the training corpus. This allows us to produce new musical output with longer-term structure that blends aspects of the query to the style of the network. In order to control the level of this blending we add a noisy channel between the VAE encoder and decoder using bit-allocation algorithm from communication rate-distortion theory. Our experiments provide new insight into relations between the representational and structural information of latent states and the query signal, suggesting their possible use for composition purposes

Project management and music in education and related fields

Project Management (PM) is a well-established field of research with the scope of inquiry now ranging far beyond the industrial and corporate sectors from which it first emerged. Starting from the premise that PM expertise is a valuable professional attribute and life skill of relevance to many if not all educational disciplines, questions emerge both as to how relevant techniques can be most effectively applied in educational contexts, and how insights might potentially be drawn from the study of different disciplines to enrich the PM profession. This paper focuses initially on higher education (specifically university level study) within the United Kingdom (UK) and other countries, and provides a contextual analysis of the discourse and practice of PM in undergraduate degree subjects. Discussion then narrows in on the discipline of music, as a specific context for consideration of PM through the educational and professional continuum. Identifying a relative absence of explicit PM theory or terminology in the vast majority of degree subjects at least in the UK, there is, nevertheless, an underlying presence of project-based activity at least implicit in all university education and music, in particular, presents a distinctive example of a creative, cultural, educational, where PM is an integral component and experience of subject and discipline. This paper concludes by identifying significant value in the development of a more explicit approach to PM in educational contexts and considerable scope for the development of professional relationships between PM organizations and the higher education sector in particular

Extended methods of notation in Josh Levine's Les yeux ouverts and Daniel Tacke's Einsamkeit

Master's Project (M.Mu.) University of Alaska Fairbanks, 201