Conference PaperPDF Available

Sculpting the behaviour of the Feedback-Actuated Augmented Bass: Design strategies for subtle manipulations of string feedback using simple adaptive algorithms

Authors:

Abstract and Figures

This paper describes physical and digital design strategies for the Feedback-Actuated Augmented Bass-a self-contained feedback double bass with embedded DSP capabilities. A primary goal of the research project is to create an instrument that responds well to the use of extended playing techniques and can manifest complex harmonic spectra while retaining the feel and sonic fingerprint of an acoustic double bass. While the physical configuration of the instrument builds on similar feedback string instruments being developed in recent years, this project focuses on modifying the feedback behaviour through low-level audio feature extractions coupled to computationally lightweight filtering and amplitude management algorithms. We discuss these adaptive and time-variant processing strategies and how we apply them in sculpting the system's dynamic and complex behaviour to our liking.
Content may be subject to copyright.
Sculpting the behaviour of the Feedback-Actuated
Augmented Bass
Design strategies for subtle manipulations of string feedback using simple
adaptive algorithms
Halldor Ulfarsson
Emute Lab
University of Sussex
Falmer, Brighton BN1 9RH
h.ulfarsson@sussex.ac.uk
Adam Pultz Melbye
Sonic Arts Research Centre
Queen’s University
Belfast BT9 5BQ
amelbye01@qub.ac.uk
ABSTRACT
This paper describes physical and digital design strategies
for the Feedback-Actuated Augmented Bass – a self-contained
feedback double bass with embedded DSP capabilities. A
primary goal of the research project is to create an instru-
ment that responds well to the use of extended playing tech-
niques and can manifest complex harmonic spectra while
retaining the feel and sonic fingerprint of an acoustic dou-
ble bass. While the physical configuration of the instru-
ment builds on similar feedback string instruments being
developed in recent years, this project focuses on modify-
ing the feedback behaviour through low-level audio feature
extractions coupled to computationally lightweight filtering
and amplitude management algorithms. We discuss these
adaptive and time-variant processing strategies and how we
apply them in sculpting the system’s dynamic and complex
behaviour to our liking.
Author Keywords
NIME, augmented string instrument, electromechanical ac-
tuation, electroacoustic, string feedback, experimental lutherie
CCS Concepts
Human-centered computing Sound-based input
/ output; Information systems Music retrieval;
Applied computing Performing arts;
1. INTRODUCTION
The project builds on a method for feedback string instru-
ments developed in halldorophones [21], a cello-like, electro-
acoustic, feedback string instrument which has proven to be
of interest to experimentally minded string players in recent
years [8] [5].
In this project, a double bass is modified in that same
tradition: individual pickups located under each string are
routed through an amplifier to an embedded speaker at the
back of the instrument, in our implementation with the ad-
Licensed under a Creative Commons Attribution
4.0 International License (CC BY 4.0). Copyright
remains with the author(s).
NIME’20, July 21-25, 2020, Royal Birmingham Conservatoire,
Birmingham City University, Birmingham, United Kingdom.
dition of a Bela microprocessor1[10] running SuperCollider2
between pickups and amplifier. This results in a feedback
’loop’, as the electro-mechanically amplified string vibra-
tions re-vibrate the entire instrument in conjunction with
any excitation introduced by the player (plucking, bowing,
hitting, etc.).
Figure 1 provides a diagram of the instrument system con-
figuration, with a conceptualised visualisation of the acous-
tic and digital signal flow.
Figure 1: A diagram of the Augmented Double
Bass. Component configuration and feedback path-
way.
The design objective of this project is to create a robust,
portable and self-contained feedback string instrument that
compliments the basic electro-mechanical dynamics of the
feedback system through digital signal processing, all while
retaining the sonic fingerprint of the double bass as an aes-
thetic constraint. By extending the behaviour of a dou-
1https://shop.bela.io/collections/
bela-and-bela-mini/products/bela-starter-kit
(Accessed 30.04.2020)
2https://supercollider.github.io/
(Accessed 30.04.2020)
221
ble bass into electroacoustic and digital space, and employ-
ing a cybernetic approach to the ergodynamic3[9] design
strategy, we cause the instrument-system to exhibit semi-
autonomous and emergent behaviour. This calls for an ex-
plorative mindset on behalf of the player rather than a re-
liance on conceptions of technical and interpretative mas-
tery. Currently seven months into the project, this paper
reports on evaluation of the work with and the experience
of negotiating our design intent within the constraints of
the current system.
2. PREVIOUS WORK
The ergodynamics of feedback string instruments are fun-
damentally different to those of their acoustic and electroa-
coustic siblings in that the former are set up to introduce
mechanical energy (vibration) into the instrument in a cou-
pled relationship to the excitation of the strings. The points
of coupling in the feedback loop (detecting and actuating)
can be configured in different ways, affecting the feel and
behaviour of the system. However, the central principle
of electro-mechanically co-energising an acoustic resonating
body is a defining quality of the feedback instruments de-
scribed here. The halldorophone-method [21] and derived
augmented instrument projects [5] [8] are organised to feed
back through an actuator embedded in the body of the in-
strument, with individual pickups for each string allowing
for the mixing of string-prominence in the resulting feed-
back. A different approach is Melbye’s What the Frog’s Eye
tells the Frog’s Brain [11] where the dominant coupling is
through the body of the double bass, induced through the
application of contact pickups and actuators to the sound-
box. As a consequence, Melbye’s system favours the res-
onant frequencies of the instrument body rather than the
strings.
3. THE INSTRUMENT
Central to the design of the Feedback-Actuated Augmented
Bass (hereafter the FAAB) is a conception of simplicity; a
wish to keep all electronics embedded in the instrument, al-
lowing for a self-contained portable system where the only
protruding cables are for power and master amplitude con-
trol via a volume pedal. The Bela is placed underneath the
fingerboard in close proximity to the pickups and control
panel, while the amplifier is stored inside the double bass
body. The Bela and amplifier are powered through a power
supply (see figure 2), with the pickups running on separate
a 9-volt battery (significantly reducing system noise as op-
posed to powering them from the power supply).
The design rationale for a self-contained instrument is
practical as well as aesthetic: The instrument is quick to
set up, with a single switch powering up the electronics and
booting the software. Significantly excluding the ubiqui-
tous laptop from the performance setting while retaining the
ability to sculpt systemic behaviour afforded by DSP, the
instrument is physically self-contained, allowing the player
to focus on engaging with the familiar physical features of
the instrument, rather than a laptop or external controllers.
As such, this system favours tacit musical engagement, of-
fering an opportunity to grow into and deepen an embodied
relationship with the instrument.
3Thor Magnusson defines ergodynamics as a ‘term that
somewhat relates to the use of ‘gameplay’ in computer
games, but further signifies an awareness and experience of
the instrument in embodied, historical, and aesthetic prac-
tices’.
Figure 2: The FAAB, front
Figure 3: The FAAB, back
3.1 Hardware
Four electromagnetic Cycfi Nu4single-string pickups are
routed through the Bela, an amplifier and finally to an eight-
inch 150 watts mid-range speaker installed in the back of
the double bass. Here, a hole is cut and a ring of birch
plywood is fitted and glued to the rim for reinforcement.
The speaker is mounted, facing outwards, on that plywood
rim.
The Bela has been expanded with the CTAG Face cape
giving us four input channels at a sampling rate of 48000 Hz,
4https://www.cycfi.com/projects/nu-series-v2/
(Accessed 30.04.2020)
222
Figure 4: System electronics block diagram
crucial for sculpting feedback via signal processing5. Con-
trol parameters are constrained to the Bela’s eight analogue
inputs which are connected to slide and knob potentiome-
ters on the right-hand side control panel. The four slid-
ers are mapped to individual string volume controls (future
system design may move this step to an analogue mixer,
freeing up mappable control parameters). The remaining
controllers are available for additional DSP-mappings, so
far mainly adjusting the balance between the clean sig-
nal and various processing algorithms running concurrently.
See Figure 4 for a block diagram overview of the system.
The flexibility of working with individual audio streams
from the four pickups places a computational strain on the
Bela processor. We are currently using a buffer frame size
of 32 at a sampling rate of 48000 Hz, which we consider an
acceptable compromise between high-quality audio, compu-
tational flexibility and latency, without audio dropouts and
artefacts. In the painstaking work of reducing system noise
we have found that all cabling should be shielded. The
current iteration of the system excludes a preamplifier cir-
cuit designed to boost the signal of the Nu pickups before
the Bela stage. This served to reduce system noise during
early stages of development but has become redundant as
we shielded more cabling and introduced a better 5V regu-
lator.
3.2 Ergodynamic design intent
We are designing a feedback string instrument and as such,
focus on and attempt to magnify the qualities of the two
constituent main parts: feedback, as a very distinct elec-
troacoustic phenomenon as well as control principle, such
as described by Collins [1], and the string instrument itself,
being a highly familiar and refined mechano-acoustic inter-
face. Both parts allow for considerable depth of intimate
and intuitive sonic exploration.
For simplicity we strive to keep the number of manually
controllable DSP parameters to a minimum. This is a ma-
jor design concern since the performing bass player rarely
has any hands free. To facilitate this strategy we derive the
majority of control signals from simple audio feature extrac-
tion algorithms such as frequency detection and amplitude
tracking as well as higher-level analysis and comparisons of
those parameters. To that end, the DSP part of the system
5https://shop.bela.io/collections/
ctag-multi-channel-audio-system/products/
ctag-face (Accessed 30.04.2020)
depends on the careful scaling and mapping of control sig-
nals to signal processing algorithms, facilitating adaptive
and self-organising behaviour through systemic couplings.
We optimise this behaviour to play out with maximum re-
ciprocality between the acoustic and digital aspects of the
system while attempting to retain a certain acoustic feel
in regards to the behaviour of the processing algorithms
(avoiding obviously digital-sounding artefacts).
The DSP design builds on works by, amongst others,
Agostino Di Scipio [2] and Sanfilippo and Valle [16] whose
practices rely on feedback and are often to be found on an
instrument-installation continuum. Yet where the ambient
acoustic environment is often a determining factor in the
systems developed by these composers, we are concerned
with the relationship between instrument and performer
and the ergodynamics of the playing experience. Struc-
tural and systemic couplings of the constituent mechanical
(acoustic), electronic and digital parts of the system allow
us to compose a dynamic signal processing flow, shaped in
the interaction with a physically familiar instrument. The
control-signal feedback described by Sanfilippo and Valle
[16] is crucial in this context: By coupling audio feature
analysis back into the system, an inaudible feedback cou-
pling between control signals is created, facilitating adaptive
behaviour while increasing the number of attractors in the
system’s state space. The result is an increased variety in
how the system responds to its own states as well as inputs
from the player, resulting in a lively interface with complex,
yet comprehensible behaviour that may ultimately become
familiar to the performer.
3.3 Audio feature extraction
Our experiments have shown that FFT-based feature ex-
traction used for identifying higher-level features such as
spectral centroid and flatness explored in earlier laptop-
based feedback instruments such as What the Frog’s Eye
tells the Frog’s Brain is not computationally possible in our
current DSP (Bela) environment due to lack of processing
power. In order to shape the behaviour of the instrument,
our approach is instead to focus on frequency and ampli-
tude tracking and calculating differences between this data
across individual time scales and separate audio streams
(the four string inputs).
For detecting the center frequency of all four strings
summed together, we use SuperCollider’s Pitch U-Gen, while
computationally much cheaper and less precise zero-crossing
223
detections are used for individual strings. For amplitude we
use a number of RMS measurements, all based on applying
a low-pass IIR filter on the squared input signal and taking
the square root of the output of the filter [14]. By ap-
plying two RMS measurements with different filter cutoffs
(between 0.2 and 50 Hz) to the same signal and calculating
the resulting difference, we obtain a dynamically changing
signal useful for mapping to other parameters, such as the
smoothing factors of additional RMS-calculations as well as
band-pass and comb-filter variables mentioned later (3.4.3).
We find that using time-derivatives such as these is a musi-
cally satisfying and computationally efficient way of gener-
ating systemic variety.
3.4 Signal processing
In the following we describe a number of simple algorithms
used for processing the signals entering the Bela from the
pickups6:
3.4.1 Time-variant high-pass filter
Because of the large amount of power needed to drive low-
frequency feedback combined with resonant ‘dead spots’ on
the instrument, not all pitches can easily be provoked into
feedback, especially at lower volumes.
By introducing a high-pass filter with a low cutoff (<70
Hz), some pitches can be induced to feed back, even when
they are of a fundamental frequency lower than the cutoff.
The reason for this is not clear to us and requires further
research. However, our experiments suggest that the crit-
ical cutoff frequency for inducing feedback is a nonlinear
function of the relationships between string frequency, am-
plitude and resonant nodes on the instrument and as such,
varies dynamically with minute shifts in playing positions.
Consequently, any linear mapping from frequency detection
to filter cutoff is unfeasible. A simple solution has been
to map the inversely scaled RMS of each string to the fre-
quency of a triangle wave oscillator, scaled to sweep between
values of 30 and 70 and mapped to the cutoff of a high-pass
filter. The effect of this mapping is such that when the driv-
ing amplitude approaches the point where the string starts
to self-oscillate, the sweep slows down, ideally stopping com-
pletely when feedback becomes prominent. Since the sweep
is required to be rather slow to allow for the amplitude
tracker to correctly measure the variations in amplitude,
the algorithm is slow in adapting. However, this is aesthet-
ically desirable as too quick a sweep would be too sonically
obvious. This algorithm is particularly helpful at low vol-
ume, where consistent feedback across playing positions is
desired.
3.4.2 Amplitude sync
This patch is designed to make every string attempt to sync
its amplitude to the mean of the individually weighted am-
plitude of its two immediate neighbours, considering the 1st
and 4th string neighbours for the sake of symmetry.
The difference in RMS between individual strings and
the weighted RMS of their neighbours is mapped to the fre-
quency of four triangle wave oscillators. These oscillators
scale the input gain of each string to between 0.0 and 1.0,
meaning that the closer strings are to each other in am-
plitude, the slower their gain is adjusted. The amplitude
variance across all strings is used as a measure of ampli-
tude homogeneity and mapped (via sample and hold) to
the frequency of a phasor sweeping from 0.0 to 1.0. When
the sweep crosses a pre-defined threshold (currently set to
6The code is available at:
https://github.com/adampultz/faab_nime_2020
(Accessed 22.04.2020)
0.9) and the variance exceeds 0.01, a new set of weights
is generated and the phasor reset while the new distribu-
tion range is sampled and mapped to the phasor frequency.
The weights are evolved by a genetic algorithm [6] [4], the
crossover points and mutation of which constitute the only
randomized features of the system7.
See figure 5 for a diagram of the patch. For the sake of
simplicity, only the second string is represented.
Inspired by Strogatz’ writing on locally coupled oscilla-
tors [18], the syncing algorithm rarely achieves perfect sync,
yet exhibits dynamic and adaptive behaviour conducive to
performative exploration.
Figure 5: Amplitude sync
3.4.3 Adaptive filtering
Since the instrument generally favours low-end feedback, we
are currently exploring two approaches to amplifying upper
partials through the use of adaptive filtering:
One approach is to apply an array of band-pass filters
tuned to the prime ratios of a fixed fundamental relative to
the tuning of the instrument (currently 55 Hz). In order
to avoid static behaviour due to the fixed fundamental of
the filters, we let the difference between slow and fast ampli-
tude tracking determine a frequency offset so that amplitude
spikes will push the filters into an inharmonic range, return-
ing in proportion to the convergence of the two amplitude
measurements8.
Secondly, we have implemented an array of comb filters,
the resonant frequencies of which are tuned to prime ratios
of a zero-crossing frequency-estimate of individual strings.
In order to avoid fast or apparent filter sweeps due to changes
in the tracked pitch, the signal is smoothed over a window
7Amplitude sync example: https://vimeo.com/413504674
(Accessed 30.04.2020)
8Band-pass filter: https://vimeo.com/413504674#t=33s
(Accessed 30.04.2020)
224
of 5 seconds. The filter amount is the inverse of the dif-
ference between a fast frequency tracker and a slow-moving
frequency average, meaning that many filter sweeps will oc-
cur while the dry signal is being favoured9.
Our preference for prime number odd partials produced
by the filters is due to the ambition of adding spectral com-
plexity to the signal. A variety of filter tunings can be
applied and will be explored in future work.
Both filter implementations result in an extended fre-
quency response that varies dynamically with changes in
amplitude and sound spectrum. Through the emergence
of additional harmonic and inharmonic content, the filters
allow for extended explorations of complex spectra pro-
duced by multiphonics and dyads but additionally effect a
coupled amplitude-to-timbre relationship, increasing the in-
strument’s sensitivity to bow-placement and pressure, which
is a creative asset to our ears.
3.4.4 Amplitude saturation
This patch is a modified adaption from Chris Kiefer [7] and
uses the SuperCollider Integrator UGen - a simple low-pass
filter with the formula:
out(0) = in(0) + (coef out(1))
By calculating the reciprocal of the Integrator and multiply-
ing this with the input signal, the system becomes saturated
with gain. The balance between the clean and saturated sig-
nal is a function of RMS: when amplitude is low, the wet
signal is favoured, whereas higher amplitude causes the dry
signal to dominate. Where Kiefer uses the mean ampli-
tude to drive a single Integrator with a summed input of all
four strings, we have opted for applying an individual sat-
uration process to each string. Additionally, by letting the
RMS time window become a function of RMS changes over
time (as mentioned in 3.3) we add yet another layer of adap-
tive dynamic behaviour. The behaviour of the saturator is
sometimes reminiscent of a sustainer, pushing amplitude up
to promote feedback, even at low volume levels. This is a
desirable quality for us when, for example, used in combi-
nation with pizzicato harmonics.
An interesting side effect of the gain saturation is that
analog and digital system noise will inevitably become am-
plified when the strings are dampened. While generally
aiming for a low-noise system, the creative possibilities of
exploring the balance between string feedback and noise
saturation are very attractive and a current path for explo-
ration10.
4. DISCUSSION
We like this instrument. Considering the FAAB from the
perspective of our previous work along similar lines, it has
definite benefits and it is clear to us that here is a project
on which we will keep working.
From ´
Ulfarsson’s perspective, in comparison to halldor-
phones, the lower register, larger resonant body and higher
power ratings for the amp and speaker give it a distinct
’rolling-thunder’ quality. To give into sentiment, this au-
thor feels: ’its aural presence is awe-inspiring.’
An experimental version of the halldorophone is already
Bela-endowed and ´
Ulfarsson’s experience of working with
that instrument as well as the FAAB is gradually making
the DSP design-space more familiar for these instruments.
9Comb filter: https://vimeo.com/413504674#t=82s
(Accessed 30.04.2020)
10Amplitude saturation:
https://vimeo.com/413504674#t=149s
(Accessed 30.04.2020)
To this author, there is a latent risk of losing interesting sys-
temic behaviour and rendering the instrument predictably
manageable by pursuing a route of implementing algorithms
that render this manner of feedback as purely a sustain fea-
ture (which is certainly possible). The most salient affor-
dances seem to be devising strategies of dynamically con-
trolling gain based on monitoring of the system state, an
opinion supported by early findings of Eldridge and Kiefer
on their Feedback Cello project [5].
From Melbye’s perspective, the ergodynamic shift from
an acoustic double bass to the extended instrumental prop-
erties of the FAAB demands a new approach to develop-
ing performance skills. The adaptive and often nonlinear
behaviour of the instrument imbues it with a sense of au-
tonomy that, on the one hand supports exploration, and
on the other, resists the traditional notion of instrumen-
tal mastery [17] [12]. The intimate coupling between string
and bow required by a number of bowing techniques (such
as spiccato, multiphonics, subharmonics and sul ponticello)
is greatly impacted by the increased amplitude throughput
and self-sustaining string oscillations caused by the feed-
back. Whereas the execution of some of these techniques
flow easier on the FAAB, traditionally simple bowing tasks
such as the retention of consistency in amplitude and tim-
bre across the instrument become an uncertain enterprise,
given the impact of the feedback.
The embedded electronics are an important feature to
Melbye: The double bass, DSP engine, amp and speaker,
are perceived as a coherent instrument and allow for an em-
bodied engagement with a physically bounded object rather
than spatially distributed discrete entities. Phenomenologi-
cally speaking, the feel of a physically singular instrument is
carried over from the double bass and into the FAAB, allow-
ing the player to keep a strong baseline feeling of familiarity
with the system even when the augmented behaviour of that
system is unfamiliar.
5. CONCLUSIONS
In the DSP design for a self-contained, feedback-configured
double bass with the constraints of onboard processing, we
have developed strategies which make for complex, struc-
turally coupled behaviour in the ergodynamics of this hy-
brid instrument.
The self-imposed computational limitations of aiming for
a low-latency and responsive four-channel system running
on an on-board microprocessor such as the Bela, is a cre-
ative constraint calling for specific coding solutions that
could otherwise be executed from a laptop. We have de-
veloped low-level audio feature extraction strategies, specif-
ically through the smoothing of control signals over dif-
ferent and varying time scales. Coupling these to filters
and amplitude management algorithms, we have created a
complex and adaptive environment within the constraints
of the current configuration of the instrument. However,
being in the preliminary stages of development, we recog-
nize that there are additional computationally cheap time-
domain processes to explore, such as those recently pro-
posed by Dario Sanfilippo [15].
The instrument exhibits complex, time-variant and adap-
tive behaviour and as such, demands the development of
new performance practices, inviting of explorative interac-
tion rather than an aspiration toward mastery. For exper-
imentally minded players the FAAB offers an open-ended
avenue for the research and development of new techniques
and playing idioms, which counts as a positive to the au-
thors.
Feedback and signal processing, by amplifying and gener-
225
ating spectral features that cannot otherwise be produced
by purely acoustic means, has fundamental consequences for
how this instrument can be played. Extended and alterna-
tive bowing and pizzicato techniques recently developed in
contemporary acoustic double bass performance practices
[3] [20] [19] are fundamentally applicable to performance
with the FAAB. Yet, the physical excitation and timbral
colouration supplied by amplification and signal processing
requires the performer to adapt any skill set to the addi-
tional electromechanical response of the instrument, being
offered an extended sonic and dynamic field for exploration
in exchange.
A multi-performer survey analysing the ergodynamics of
the instrument is warranted and of interest. However, the
focus here is on the design of an instrument tailored to
the preferences of a specific performer (Melbye) to whom
it holds a promise of continued fascination during future
exploration. As such, the work to date may be a guide to
other designers and artists looking for discrete solutions to
bespoke instruments of similar constraints and characteris-
tics.
6. FUTURE WORK
With the majority of the work in this research project being
focused on DSP feature design, it is beyond the scope of
this paper to discuss the complex relationship between the
acoustics of the double bass and the electro-mechanically
actuated feedback network. We recognise this as a valuable
topic for further research.
A priority for Melbye is the exploration the instrument
as it is currently set up, in order to achieve a degree of
familiarity (comparable to what he has with a traditional
double bass). This work will include developing new tech-
niques and performance tactics while slowly adapting to -
and co-evolving with the physical and digital features of the
instrument.
Working towards lower system noise and structural sta-
bility, we will incorporate shielded casings for the system
components, and potentially shield all cabling (as shielding
has given good results in some instances).
In an effort to optimize the processing power of the Bela
we may reprogram the SuperCollider code in C++ or Heavy
Audio Tools [13] to potentially gain more computational
headroom, allowing for increased processing possibilities
and/or lower audio buffer frames.
Despite the benefits of having a petite, easy to work with,
fast to boot, on-board DSP engine, we intend to implement
a version of the software on a laptop, allowing us to work
with several higher-level FFT-based feature extractions that
we have been unable to successfully run on the Bela. Open-
ing up to off-board processes would afford more processing
possibilities on the individual string signals and addition-
ally expand the number of inputs, facilitating the creation
of coupled networks of multiple instruments.
7. ACKNOWLEDGEMENT
This work was supported by The Nordic Culture Fund’s
Opstart Grant.
8. REFERENCES
[1] N. Collins. ’Pea Soup’ - A History. http://www.
nicolascollins.com/texts/peasouphistory.pdf,
2011. Accessed: 30.04.2020.
[2] A. Di Scipio. Listening to yourself through the
otherself: On background noise study and other
works. Organised Sound, 16(2):97–108, 2011.
[3] M. Dresser. Guts (DVD), 2010.
[4] A. Eldridge and O. Bown. Biologically inspired and
agent-based algorithms for music. In The Oxford
Handbook of Algorithmic Music, number May 2020,
pages 209–244. 2018.
[5] A. Eldridge and C. Kiefer. The Self-resonating
Feedback Cello: Interfacing gestural and generative
processes in improvised performance. Proceeding of
New Interfaces for Musical Expression, pages 25–29,
2017.
[6] J. H. Holland. Signals and Boundaries: Building
Blocks for Complex Adaptive Systems. The MIT
Press, 2014.
[7] C. Kiefer. A Patch Explained. https:
//www.feedbackcell.info/algorithms/algo7/,
2017. Accessed: 30.04.2020.
[8] T. P. Liontiris. Low Frequency Feedback Drones : A
non-invasive augmentation of the double bass.
Proceeding of New Interfaces for Musical Expression,
pages 340–341, 2018.
[9] T. Magnusson. Ergodynamics and a semiotics of
instrumental composition. Tempo (United Kingdom),
73(287):41–51, 2019.
[10] A. P. McPherson and V. Zappi. An environment for
submillisecond-latency audio and sensor processing on
beaglebone black. In 138th Audio Engineering Society
Convention 2015, volume 2, pages 965–971, 2015.
[11] A. P. Melbye. What the Frog’s Eye tells the Frog’s
Brain. https://vimeo.com/327281165, 2019.
Accessed: 30.04.2020.
[12] A. P. Melbye. Resistance, mastery, agency:
Improvising with the feedback-actuated augmented
bass. Organised Sound, 26(1), forthcoming 2021.
[13] G. Moro, A. Bin, R. H. Jack, C. Heinrichs, A. P.
McPherson, and Others. Making High-Performance
Embedded Instruments with Bela and Pure Data.
Proceedings of the International Conference on Live
Interfaces, pages 1–5, 2016.
[14] J. D. Reiss and A. P. McPherson. Audio effects:
theory, implementation and application. CRC Press,
Taylor and Francis Group, 2019.
[15] D. Sanfilippo. Complex Musical Behaviours via
Time-Variant Audio Feedback Networks and
Distributed Adaptation: a Study of Autopoietic
Infrastructures for Real-Time Performance Systems.
PhD thesis, The University of Edingburgh, 2019.
[16] D. Sanfilippo and A. Valle. Feedback systems: An
analytical framework. Computer Music Journal,
37(2):12–27, 2013.
[17] P. Stapleton. Dialogic Instruments: Virtuosity
(Re)Located in Improvised Performance. Leonardo,
15(11), 2008.
[18] S. H. Strogatz. Sync: The Emerging Science of
Spontaneous Order. Allen Lane, 2003.
[19] H. Thelin. Multiphonics on the double bass: An
investigation on the development and use of
multiphonics on the double bass in contemporary
music. The Norwegian Academy of Music, 2011.
[20] H. Thelin. New techniques – new works. The
Norwegian Academy of Music, 2011.
[21] H. ´
Ulfarsson. The halldorophone: The ongoing
innovation of a cello-like drone instrument. Proceeding
of New Interfaces for Musical Expression, 2018.
226
... The nature of the coupling between the electronics and the instrument is such that as the system's amplitude is increased, the speaker mechanically vibrates the double bass body and consequently the strings, causing them to enter into self-oscillation (feedback). A technically involved discussion of the FAAB has been published elsewhere (Úlfarsson and Melbye 2020), while Movie Example 1 documents an improvisation with the instrument. ...
... In the digital domain, operational closure manifests in the relationship between audio feature extraction (AFE) algorithms and the digital signal processing (DSP) stage, where filtering and amplitude management algorithms shape the feedback loop by modulating the response of the instrument body and hence the behaviour of the strings. However, at the AFE stage, control signals derived from amplitude and pitch analysis of the strings are mapped to DSP variables, completing a self-referential secondary feedback loop such as initially described by Ross Ashby in his discussion of double feedback (Ashby 2014: 83) and widely used in audio feedback performance systems (Collins 2011;Sanfilippo and Di Scipio 2017;Úlfarsson and Melbye 2020). To fully appreciate the importance of this phenomenon, I follow Sanfilippo and Di Scipio in their juxtaposition of operationally closed algorithms with stochastic and automated processes and how the latter operate in a domain 'fundamentally (in)different to, the domain where musical action takes place, namely sound' (Sanfilippo and Di Scipio 2017: 22). ...
Article
Full-text available
In this article I describe the development of a performance practice with a new electroacoustic instrument – the FAAB (feedback-actuated augmented bass). Drawing on a background in improvisation, I discuss how the feedback-induced behaviour of the instrument sets it apart from an acoustic bass and how the implementation of operationally closed digital signal processing algorithms facilitates greater systemic autonomy. In identifying resistance as a key feature of improvisation, I propose the term ‘diachronic mastery’ as a way of addressing the equilibration of sensorimotor schemes in the context of developing a performance practice with a complex hybrid system such as the FAAB. Through a discussion of the term ‘agency’ as it appears in recent literature, I develop a preliminary framework for addressing both the immediate experience of agency emerging in performance ecosystems and the biologically informed definition of the term that may be useful in the design of increasingly autonomous instruments and performance systems.
... 3BP is a new international trio of improvisors formed in the autumn of 2020 on the occasion of an online live performance at Queen's University's Sonic Arts Research Centre, Belfast, subsequently performing at Northern Ireland Science Festival and New York City Electroacoustic Improvisation Summit. The trio connects artistresearchers in Belfast, Northern Ireland, Newcastle, United Kingdom, and Berlin, Germany, through an online performance ecology comprising previously developed NIMEs [1] [2] in combination with newly created systems. Despite several earlier collaborations between the individual members [3][4][5] [6], the trio is network-native in that it was created, and has so far only existed, online. ...
Article
Full-text available
In this article I describe the development of a performance practice with a new electroacoustic instrument – the FAAB (feedback-actuated augmented bass). Drawing on a background in improvisation, I discuss how the feedback-induced behaviour of the instrument sets it apart from an acoustic bass and how the implementation of operationally closed digital signal processing algorithms facilitates greater systemic autonomy. In identifying resistance as a key feature of improvisation, I propose the term ‘diachronic mastery’ as a way of addressing the equilibration of sensorimotor schemes in the context of developing a performance practice with a complex hybrid system such as the FAAB. Through a discussion of the term ‘agency’ as it appears in recent literature, I develop a preliminary framework for addressing both the immediate experience of agency emerging in performance ecosystems and the biologically informed definition of the term that may be useful in the design of increasingly autonomous instruments and performance systems.
Conference Paper
Full-text available
Bela is an embedded platform for ultra-low latency audio and sensor processing. We present here the hardware and software features of Bela with particular focus on its integration with Pure Data. Sensor inputs on Bela are sampled at audio rate, which opens to the possibility of doing signal processing using Pure Data's audio-rate objects.
Article
This article examines the techno-philosophical aspects of how we create and understand musical systems in twenty-first century computational media. Arguing that processor-based media have exploded the compositional language of new music, the article proposes a set of concepts that might help us navigate this new space of instrumental possibilities. The term ‘ergodynamics’ – and related concepts – is proposed as a useful concept when describing the phenomenological, historical and aesthetic aspects of musical instruments, as well as a lens for looking at new compositional practices that can be defined as being either ‘idiomatic’ or ‘supra-instrumental’. The article explores the difference in composing for acoustic, electronic and digital instruments, and suggests that new musical practice can be characterised by a move from composing work to inventing systems.
Book
Audio Effects: Theory, Implementation and Application explores digital audio effects relevant to audio signal processing and music informatics. It supplies fundamental background information on digital signal processing, focusing on audio-specific aspects that constitute the building block on which audio effects are developed. The text integrates theory and practice, relating technical implementation to musical implications. It can be used to gain an understanding of the operation of existing audio effects or to create new ones. In addition to delivering detailed coverage of common (and unusual) audio effects, the book discusses current digital audio standards, most notably VST and AudioUnit. Source code is provided in C/C++ and implemented as audio effect plug-ins with accompanying sound samples. Each section of the book includes study questions, anecdotes from the history of music technology, and examples that offer valuable real-world insight, making this an ideal resource for researchers and for students moving directly into industry.
Chapter
This chapter examines a range of approaches to algorithmic music making inspired by biological systems, and considers topics at the intersection of contemporary music, computer science, and computational creativity. A summary of core precursor movements both within and beyond musical practice (A Life, cybernetics, systems art, etc.) sets the scene, before core models and algorithms are introduced and illustrated. These include evolutionary algorithms, agent-based modelling and self-organizing systems, adaptive behaviour and interactive performance systems, and ecosystemic approaches to composition and computational creative discovery. The chapter closes by reviewing themes for future work in this area: autonomy and agency, and the poetics of biologically inspired algorithms.
Article
This paper presents a new environment for ultra-low-latency processing of audio and sensor data on embedded hardware. The platform, which is targeted at digital musical instruments and audio effects, is based on the low-cost BeagleBone Black single-board computer. A custom expansion board features stereo audio and 8 channels each of 16-bit ADC and 16-bit DAC for sensors and actuators. In contrast to typical embedded Linux approaches, the platform uses the Xenomai real-time kernel extensions to achieve latency as low as 80 microseconds, making the platform suitable for the most demanding of low-latency audio tasks. The paper presents the hardware, software, evaluation and applications of the system.
Article
This paper introduces a series of new musical instruments that have been designed to address questions relating to performative virtuosity in the area of ensemble-based improvisation. The intentionally exploited inconsistent nature of these instruments raises questions around traditional notions of instrument mastery and opens up possible methods of reconfiguring the performer-instrument relationship. This paper is an attempt to introduce not only a new series of musical instruments, but also an approach to the instrument-performer relation in improvised performance. I will begin by briefly describing the context in which the instruments were created, followed by a discussion on a type of performative virtuosity afforded by these instruments. A series of largely metallic instruments were created in a collaboration between me and designer-makers Neil Fawcett and Kiran Singh, as part of my practice-led PhD research project The Development of Dialogic Music (2001-2004) at the University of Central Lancashire (UK) (Figure 1). In this project I sought to investigate, through a range of corroborative reflective practices, the many relationships at play within specific forms of ensemble-based improvisation. The instrument creation process played a key role in the research, employing both user-centered and heuristic design methods. The resulting behavior of the instruments themselves (as will soon be elaborated) significantly contributed to the study. The instruments have since been reemployed in a broad range of contexts, including the site-specific works of UK-based interdisciplinary performance group theybreakinpieces (of which I am a co-director), as well as in the practices of several other academics, students and professional artists.
Article
The use of feedback-based systems in the music domain dates back to the 1960s. Their applications span from music composition and sound organization to audio synthesis and processing, as the interest in feedback resulted both from theoretical reflection on cybernetics and system theory, and from practical experimentation on analog circuits. The advent of computers has made possible the implementation of complex theoretical systems in audio-domain oriented applications, in some sense bridging the gap between theory and practice in the analog domain, and further increasing the range of audio and musical applications of feedback systems. In this article we first sketch a minimal history of feedback in music; second, we briefly introduce feedback systems from a theoretical point of view; then we propose a set of features that characterize them from the perspective of music applications; finally, we propose a typology targeted at feedback systems used in the audio/musical domain and discuss some relevant examples.
Article
Scitation is the online home of leading journals and conference proceedings from AIP Publishing and AIP Member Societies