Conducting the Wind Orchestra: Meaning, Gesture, and Expressive Potential, Student Edition

Pierre Boulez
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I include a small definition and bibliography of some Dalcroze resources. To my current understanding, the work of Dalcroze is not well known in instrumental music education circles, although it does have a strong following amongst some classroom music teachers. The Dalcroze method , also known as Dalcroze Eurhythmics, is another approach music educators use to foster music appreciation, ear training and improvisation towards improving musical abilities.

In this method, the body is the main instrument. Students learn to listen to the rhythm of a music piece and express what they hear through physical movement.

Simply put, this approach connects music, movement, mind, and body. Dalcroze was born on July 6, , in Vienna, Austria. He became a professor of harmony at the Geneva Conservatory in ; by which time he started developing his method of teaching rhythm through movement known as eurhythmics. He founded a school in Hellerau, Germany later moved to Laxenburg in , and another school in Geneva in , where students learned using his method. Dalcroze died on July 1, , in Geneva, Switzerland. Several of his students, such as ballet teacher Dame Marie Rambert, used eurhythmics and became influential in the development of dance and contemporary ballet during the 20th century.

Eurhythmics Greek for "good rhythm" - Musical expression is experienced through movement aiding the development of musical skills through kinetic exercises. Students experience both rhythm and structure through listening to music while expressing what they hear through spontaneous bodily movement.

WASBE Journal

For example, using stepping and clapping to represent note values and rhythms. The method also employs the use of Solfeggio to assist and develop ear-training and sight-singing skills. Improvisation is used to stimulate creativity while freeing students from inhibition in musical expression.

The improvisation exercises can also involve the use of instruments , movement or voice. Although it is generally referred to as a method, there is no set curriculum.

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Dalcroze himself didn't like his approach to be labeled as a method. When employed the Dalcroze Method can aid in further developing imagination, creative expression, coordination, flexibility, concentration, inner hearing, music appreciation and understanding and practical application of musical concepts.

There are several training opportunities available to teach this method. Holders of this diploma may teach other teachers and award certifications. Joan POPE ed. We have recently seen various improvements of interface design on tactile feedback and force guidance aiming to make instrument learning more effective. However, most interfaces are still quite static; they cannot yet sense the learning progress and adjust the tutoring strategy accordingly. To solve this problem, we contribute an adaptive haptic interface based on the latest design of haptic flute.

We first adopted a clutch mechanism to enable the interface to turn on and off the haptic control flexibly in real time. Finally, we incorporated the adaptive interface with a step-by-step dynamic learning strategy. Experimental results showed that dynamic learning dramatically outperforms static learning, which boosts the learning rate by MNT is being developed by a multidisciplinary group that explores gestural control of audio-visual environments and virtual instruments.

It uses infrared sensors, Hall sensors, and strain gauges to estimate deflection. These sensors each perform better or worse depending on the class of gesture the user is making, motivating sensor fusion practices. Residuals between Kalman filters and sensor output are calculated and used as input to a recurrent neural network which outputs a classification that determines which processing parameters and sensor measurements are employed.

Multiple instances 30 of layer recurrent neural networks with a single hidden layer varying in size from 1 to 10 processing units were trained, and tested on previously unseen data. The best performing neural network has only 3 hidden units and has a sufficiently low error rate to be good candidate for gesture classification.

This paper demonstrates that: dynamic networks out-perform feedforward networks for this type of gesture classification, a small network can handle a problem of this level of complexity, recurrent networks of this size are fast enough for real-time applications of this type, and the importance of training multiple instances of each network architecture and selecting the best performing one from within that set. Movement is tracked and mapped through extensive pre-processing to a high-dimensional acoustic space, using a many-to-many mapping, so that every small body movement matters.

Designed for improvised exploration, it works as both performance and installation. Through this re-translation of bodily action, position, and posture into infinite-dimensional sound texture and timbre, the performers are invited to re-think and re-learn position and posture as sound, effort as gesture, and timbre as a bodily construction. The sound space can be shared by two people, with added modes of presence, proximity and interaction. The aesthetic background and technical implementation of the system are described, and the system is evaluated based on a number of performances, workshops and installation exhibits.

Finally, the aesthetic and choreographic motivations behind the performance narrative are explained, and discussed in the light of the design of the sonification. Abstract BibTeX Download PDF Taking inspiration from research into deliberately constrained musical technologies and the emergence of neurodiverse, child-led musical groups such as the Artism Ensemble, the interplay between design-constraints, inclusivity and appro- priation is explored. A small scale review covers systems from two prominent UK-based companies, and two itera- tions of a new prototype system that were developed in collaboration with a small group of young people on the autistic spectrum.

It is argued that the design-constraints of the new prototype system facilitated the diverse playing styles and techniques observed during its development. Based on these obser- vations, we propose that deliberately constrained musical instruments may be one way of providing more opportuni- ties for the emergence of personal practices and preferences in neurodiverse groups of children and young people, and that this is a fitting subject for further research.

The system consists of 1 a computational analysis-generation algorithm, which not only formalizes musical principles from examples, but also guides the user in selecting note sequences; 2 a MIDI keyboard controller with an integrated LED stripe, which provides visual feedback to the user; and 3 a real-time music notation, which displays the generated output.

Ultimately, AMIGO allows the intuitive creation of new musical structures and the acquisition of Western music formalisms, such as musical notation. The application enables music creation in a specific expanded format: four separate mono tracks, each one able to manipulate up to eight audio samples per channel.

It uses an adaptive audio slicing mechanism and it is based on interaction design for multi-touch screen features. This paper describes the graphical interface features, some development decisions up to now and perspectives to its continuity.

Abstract BibTeX Download PDF We introduce a machine learning technique to autonomously generate novel melodies that are variations of an arbitrary base melody. These are produced by a neural network that ensures that with high probability the melodic and rhythmic structure of the new melody is consistent with a given set of sample songs. We train a Variational Autoencoder network to identify a low-dimensional set of variables that allows for the compression and representation of sample songs. By perturbing these variables with Perlin Noise—a temporally-consistent parameterized noise function—it is possible to generate smoothly-changing novel melodies.

We show that 1 by regulating the amount of noise, one can specify how much of the base song will be preserved; and 2 there is a direct correlation between the noise signal and the differences between the statistical properties of novel melodies and the original one. Users can interpret the controllable noise as a type of "creativity knob": the higher it is, the more leeway the network has to generate significantly different melodies.

Abstract BibTeX Download PDF This paper presents a system that allows users to quickly try different ways to train neural networks and temporal modeling techniques to associate arm gestures with time varying sound. We created a software framework for this, and designed three interactive sounds and presented them to participants in a workshop based study. We build upon previous work in sound-tracing and mapping-by-demonstration to ask the participants to design gestures with which to perform the given sounds using a multimodal, inertial measurement IMU and muscle sensing EMG device.

We presented the user with four techniques for associating sensor input to synthesizer parameter output. Two were classical techniques from the literature, and two proposed different ways to capture dynamic gesture in a neural network.

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These four techniques were: 1. A Static Position regression training procedure, 2. A Hidden Markov based temporal modeler, 3. Whole Gesture capture to a neural network, and 4. Our results show trade-offs between accurate, predictable reproduction of the source sounds and exploration of the gesture-sound space. Several of the users were attracted to our new windowed method for capturing gesture anchor points on the fly as training data for neural network based regression.

This paper will be of interest to musicians interested in going from sound design to gesture design and offers a workflow for quickly trying different mapping-by-demonstration techniques. Abstract BibTeX Download PDF This paper describes the process of developing a shared instrument for music—dance performance, with a particular focus on exploring the boundaries between standstill vs motion, and silence vs sound. The piece Vrengt grew from the idea of enabling a true partnership between a musician and a dancer, developing an instrument that would allow for active co-performance. The exploration used a "spatiotemporal matrix," with a particular focus on sonic microinteraction.

In the final performance, two Myo armbands were used for capturing muscle activity of the arm and leg of the dancer, together with a wireless headset microphone capturing the sound of breathing. Abstract BibTeX Download PDF We have built a new software toolkit that enables music therapists and teachers to create custom digital musical interfaces for children with diverse disabilities.

WASBE Journal – World Association for Symphonic Bands and Ensembles

It was designed in collaboration with music therapists, teachers, and children. It uses interactive machine learning to create new sensor- and vision-based musical interfaces using demonstrations of actions and sound, making interface building fast and accessible to people without programming or engineering expertise. Interviews with two music therapy and education professionals who have used the software extensively illustrate how richly customised, sensor-based interfaces can be used in music therapy contexts; they also reveal how properties of input devices, music-making approaches, and mapping techniques can support a variety of interaction styles and therapy goals.

Abstract BibTeX Download PDF With a new digital music instrument DMI , the interface itself, the sound generation, the composition, and the performance are often closely related and even intrinsically linked with each other. Similarly, the instrument designer, composer, and performer are often the same person. The Academic Festival Overture is a new piece of music for the DMI Trombosonic and symphonic orchestra written by a composer who had no prior experience with the instrument.

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The piece underwent the phases of a composition competition, rehearsals, a music video production, and a public live performance. This whole process was evaluated reflecting on the experience of three involved key stakeholder: the composer, the conductor, and the instrument designer as performer. Thus, to deliberately avoid an early collaboration between a DMI designer and a composer bears the potential for new inspiration and at the same time the challenge to seek such a collaboration in the need of clarifying possible misunderstandings and improvement. Abstract BibTeX Download PDF This paper presents a detailed explanation of a system generating basslines that are stylistically and rhythmically interlocked with a provided audio drum loop.

The proposed system is based on a natural language processing technique: word-based sequence-to-sequence learning using LSTM units. The novelty of the proposed method lies in the fact that the system is not reliant on a voice-by-voice transcription of drums; instead, in this method, a drum representation is used as an input sequence from which a translated bassline is obtained at the output.

The drum representation consists of fixed size sequences of onsets detected from a 2-bar audio drum loop in eight different frequency bands. The basslines generated by this method consist of pitched notes with different duration. The proposed system was trained on two distinct datasets compiled for this project by the authors.