THE TP-NEON: AN INFRA-INSTRUMENTAL CONTRAPTION WHICH MORPHS A MIDI TRUMPET BANDONEON-ERGONOMICS

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The TP-Neon: An Infra-instrumental Contraption which Morphs a MIDI Trumpet Bandoneon-Ergonomics

We describe a hardware-only improvisation and/or compositional set that merges a MIDI trumpet with a circuit bending interface that is inspired on bandoneon ergonomics by using the performer non-dominant hand -normally free in trumped playing. The instrument holistically abides by the principles of infrainstrumental design proposed by Bowens and Archers’s [1]. It is termed TP-Neon and its integration within an audio and video analogue modular synthesizer, along with its playability and musicality, is discussed.

As a reaction to the complexities and interface setup pitfalls of laptop music improvisation, there is a growing number of composers and improvisers interested in increasingly reductionist forms of musical instruments [7]. Busy and dense possibilities of laptop improvisation are driving musicians to consider the integration of modular synthesizers and dedicated hardware equipment into their improvisational and compositional workflows. One step further is the hacking and modifying of existing musical/video devices building simple electronic contraptions. Often, the aim is to research and experiment with surprisingly fresh lo-fi hands-on approaches to sound/video generation [1].

Consequently, there has being a significant influence of lo-fi methods into pop music and academic composition and improvisation. Pop artists such as Bjork, Radio Head and Venetian Snares have readily incorporated these approaches in their recent works [4]. Concomitantly, these lo-fi methods have been featured in performance and composition work by contemporary composers such as, just ti give an example, such as, Nick Collins on his piece The Bowerbird in which several individuals each armed with a loudspeaker and battery make ‘Victorian synthetic’ sounds [2].

Recently, the concept of lo-fi instrument has being formalized by J. Bowers and P. Archer on his paper, Not hyper, not meta, not cyber but infra-instruments [1]. In this work the authors expand on already established concepts like ‘circuit bending’ [3,5], or ‘hardware hacking [2,6] to define an emerging field of music and video improvisation which they term infrainstruments.

This paper describes a new improvisation set capriciously termed TP-Neon for audio and analogue video that has being inspired by Bowens and Archers’s 5-axial definition of infrainstrument, for instance the TP-Neon: (1) is constrained to a limited interactive repertoire; (2) engenders relatively unpredictable music – for instance non-symphonic, non-orchestral; (3) is performed in ways that are predetermined by the architecture of the instrument; (4) is of restricted virtuosity but with a rich set of performance-driven unpredicted explorations and; (5) is ultimately engaging in terms of its visual and sonic appeal, is technically provocative and ergonomically challenging.

The TP-Neon derives its name from the ergonomic morphing of a MIDI Trumpet (TP) and a Bandoneon-Like DIY control interface (Neon). The figure 1 depicts a numbered TP-Neon architecture. The TP-Neon controller based on a Yamaha EZ-TP MIDI trumpet with a DIY patchable momentary actuation matrix which can engage large number of circuit-bends’ combinations with simple presses. The Matrix ergonomically resembles keys on a bandoneon so the TP-Neon instrument can be played with two hands: the non-dominant hand controlling the bend matrix and the trumpet keys played with the dominant hand. From the TP-Neon several signals emerge. The direct audio out from the EZ-TP responds to humming dynamics from the mouthpiece microphone. These are used to generate a control voltage trough an envelope generator which is used ad-hoc within the modular synthetiser. This CV is reused (multiplexed) and modified to generate several daughter CV signals that modulate analogue audio and video signals in the modular. Concomitantly, MIDI messages control a Hacked (Circuit-bent) Roland JV1010 ROM synthetiser module and the audio output is modified in real time by engaging circuit bent combinations. There is a total of 50 bending points that the authors has researched over the past 2 years and all bending points react with each other producing a very large number of bent combinations. This is helped by the DIY bend matrix which consists of momentary switches in a matrix array that can be freely patched to incoming bend points from the JV1010.

Improvisation with the system results in a rich/complex audiovisual output that is generated from the dynamically controlled CV and audio from the TP-Neon audio processed trough an analogue modular synthesizer (A), EZ-TP MIDI controlled audio from the JV1010 being modulated by the circuit-bending matrix (Neon) combinations. The author has used the TP-Neon live and in his last LP [8] and finds that the technical and musical constrains of the instruments is a powerful creative driving factor. Also, the highly unpredictable character of the instrument when performing enhances the ‘happening-effect’ and uniqueness of every improvisation. Given that the TP-Neon architecture is reproducible, a notation system can be proposed if more prescriptive compositional works are desired. For instance trumpet notation can be augmented with matrix indexing notation to describe the bend points whilst classic notation of dynamics could be used to describe control voltages at the envelope generator stage. The number of circuit bent combinations from the bandoneon-like keypad allows for combinatorics up to the order of ten to the power of 17 (i.e. 50 bent points with a 20 key patchable switch matrix). In other words, each voice of the JV1010 can be resynthesised to produce around 1.3*1017, a great number considering the simplicity and accessibility of the interface. Also, since humming dynamics at the EZ-TP is converted to continuous control multiplexed voltages in the modular synth, it is possible to control fine nuances of analogue patches with just dynamics alone. For instance, humming softer or louder gives the performer/improviser great control over a number of CV inputs (filter cut-offs, pitches, amplitudes, timing parameters, etc) in real time. This gives the instrument a gratifying sense of nuance control but paradoxically further expends on the unpredictability of results during performance.

4.   REFERENCES

[1]        Bowers, J. and Archer, J. “Not hyper, not meta, not cyber but infra-instruments,” in NIME ’05 Proceedings of the 2005 conference on New interfaces for musical expression. Singapore 2005. pp. 5-10.

[2]        Collins, N. Handmade Electronic Music: The Art of Hardware Hacking, London: Roultedge, 2009.

[3]        Ghazala, Q. R. “Circuit-bending and living instruments” Experimental Musical Instruments, 1993. 9: pp. 21-23.

[4]        Cascone, K. “The aesthetics of failure: “Post-digital” tendencies in contemporary computer music.” Computer Music Journal, 2000. 24(4): pp. 12-18.

[5]        Ghazala, Q. R. “The Folk Music of Chance Electronics: Circuit-Bending the Modern Coconut” Leonardo Music Journal, 2004. 14: pp. 97-104.

[6]        Richards, J. “Getting the Hands Dirty”, Leonardo Music Journal. 2008. 18: pp. 25-31.

[7]        Bach, G. “The extra-digital axis mundi: Myth, magic and metaphor in laptop music”, Contemporary Music Review, 2003. 22(4): pp. 3-9.

[8]        LopezDoNaDo. Todd’s Paresis. (LP) 2010. Brisbane: Tunecore. Track 3: Toods Pearesis: Room of Hearts.

QLD Conservatorium Electroacoustic Ensemble

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Live electroacoustic improv. Jesus LopezDoNaDo, Lloyd Barrett, Mitch, Sedelle, Sophia, Tim and Holly

As part of my doctorate in musical arts at the Quensland Conservatorium, I recently started contributing to the Electroacoustic Ensemble (EA). The EA is moderated by composer Lloyd Barrett who is being lately producing very interesting music with a tool called metasynth: [check his music]. So far it’s being a pleasure to work with the ensemble and it is of great value for my composition-practice since the EA is a safe place to experiment with unstable/new improvisation live-sets and compositional ideas.

A set using a cocoquantus processing a feedback loop from a grand piano being concominatly exited by a sustainiac guitar sustainer pedal.

The aim of the EA at the QLD-Con is: ” This ensemble provides an opportunity to work with computers, electronic devices and acoustic instruments in the creation of live performance works that do not rely on traditional notation or the pitch/duration paradigm.  Students will collaborate to develop soundscapes from flexible performative frameworks that emphasise audio-visuality, dynamic timbre, spatial/environmental awareness and human movement/interaction “

Holly was building an Auduino contraption.

Another EA member, Sedelle, heavily processes her trumpet with effects and looper pedals.

Music from Mental States: Data Base Generation

A diagram on preliminary ideas for data generation during initial stages of my PhD on Music Composition at the QLD Con. The proccess start with a series of precomposed themes that will be feed into tyhe system as audio files. Individual will listen to each them and during this process several sources of data will be explored – i.e.

(i) Mental State Examination and Diferential Diagnosis;

(ii) Selected physiological parameters traditional known to correlate with mental state changes, i.e. skin impedance, pulse rate, respiratory rate, blood pressure and body temperature. During this process of data acquisition some individual demographics will be recorded too, i.e. age, sex, gender, etc.

(iii) Electroencephalographic activity – these will be collected with the minimality invasive and readily available Emotiv EPOC EEG system.

Then i-iii, along with the predetermined ‘audio themes’ will be subject to a, still to be envisaged, process of dimensionality reduction and parametrization which will populate a database.

This database will be subjected to Data Mining proccess in order to extract Mental State Biased Compositional Rules. For instance, decision trees, cluster representaions, or just knowledege from sensitivity analysis.

Pls – feel free to comment by posting in this space.

Salut!

Doctorate in Composition: Proposal

Discovering mental-state biased compositional paradigms for microtonal electro acoustic instruments

The idea is to explore the mathematics /mental-state/music-perception continuum by using artificial intelligence (AI) techniques applied to music composition. This shall not be a scientific endeavor but rather the generation of a compositional framework that will guide my compositional outcomes during the last stages of my research time at the Conservatorium. Not only musical pieces will be composed, but also, specific electro-acoustic instruments will be designed for these. Therefore, this proposal pretends to be a project on electro-acoustic music composition. Finally, despite this proposal is based on a rigorous and highly systematic approach, the final outcomes will be exceedingly modulated by compositional creativity, previous compositional experience, my cultural background and ultimately my vision of the world. Artificial Intelligence for the generation of a compositional framework AI or machine learning approaches can be either supervised or unsupervised. As I shall potentially apply them to composition, supervised methodologies attempt to generate compositional paradigms by learning from previous experiences sampled from human or previous compositions! input. Unsupervised techniques use well-known mathematics/biology inspired algorithms, which are universal, or al lest live within their own realm, and attempt to loosely classify a compositional space of themes.

Whether we considering supervised or unsupervised approaches, the target – or motivation – would be the listener mental state as induced by short musical passages (or themes). All themes would have to be as de-correlated as possible to western traditional musical forms to rule out trivial compositional/cultural biases, i.e. minor vs major triads, simple vs odd signatures, or traditional jazz forms. Ultimately, a large number of microtonal systems will be considered.

Themes will also have to be parameterized in terms of their dynamics, timbers, tempo, and other second order mathematical measures of music, i.e. density of microtonal system, melodic range, counterpoint descriptives, and second order measures like the Laplacian on frequency time series, etc. Also, a rigorous notation system should be adopted to facilitate discussing themes from an aesthetic perspective and to allow interpreters to generate the themes in a way that is minimizes ambiguity. Nonetheless, such notation system= should be open-ended to allow for moderninterpretation but also with little dichotomies so it could be easily translated into natural language to be interpreted by the AI algorithms. I would preliminary use an adaptation of Schenker diagrams and perhaps lilypond package as a computational framework.


Given, such archive of the themes (many issues to solve here – see challenges below), listeners will contribute their mental state by choosing from a set of images while listening to the music. This will annotate set of themes, hopefully, with, at least, pseudo-universal states of mind. If universality of theme and mental-states pairs is not achieved, this should not pose any constrain since the objective of this project is to generate a “guiding” compositional paradigm rather than proving that persons are universally biased in the same way by the same musical forms.

After the themes are classified and an annotated archive is generated, a neural network (a supervised AI method) will be used to learn compositional paradigms that are meant to induce mental states – again hopefully with certain level of universality. These neural networks could also be potentially used to augment the themes-set by generating new themes in a generative basis. Concomitantly, Knohonen maps (an unsupervised AI approach) will be generated to discover clusters of compositional parameters – clues – that might also correlate with mental sates and subsequently enrich my compositional framework.

If all goes well [nervousness pause] we should end up with an intelligent artificial framework that will allow composers to guide their creative process based on (1) themes annotate by metal states they induce; (2) Neural networks that will generate themes that will potentially generate predetermined mental sates; (3) Kohonen clusters of compositional and improvisational clues that should either induce mental state sequences in the listener or perhaps augment/inform the performance experience of a given his/her current mental-state.

With this intelligent framework at certain level of maturity, I intend to achieve the following objectives: (1) Generate a series of compositions based on predetermined mental state sequences. Ideally, the compositions will include a great deal of improvisation guidelines also based on the discovered compositional paradigms that shall be adopted by the interpreter/improviser at he/she leisure as informed by they current mental state. (2) Since the paradigms departed from highly open-ended themes (i.e., micro tonality, and variations of the real-time variations electronics) instruments will be specially designed and constructed for these pieces. These instruments will be based on traditional musical instruments with altered tunings, spatial arrangements, and electro-acoustic modifications.

Kraig Grady’s Lake Aloe: microtonal vibraphone

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