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  • Research

    The fundamental principle of IRCAM is to encourage productive interaction among scientific research, technological developments, and contemporary music production. Since its establishment in 1977, this initiative has provided the foundation for the institute’s activities. One of the major issues is the importance of contributing to the renewal of musical expression through science and technology. Conversely, sp…

    • Research Topics
    • The STMS Lab
    • Research Teams
    • Sound Systems and Signals: Audio/Acoustics, InstruMents
    • Acoustic and Cognitive Spaces
    • Sound Perception and Design
    • Sound Analysis-Synthesis
    • Sound Music Movement Interaction
    • Musical Representations
    • Analysis of Musical Practices
    • Projects
    • Sound Workshop
    • The Musical Body
    • Creative Dynamics
    • Finished Projects
  • Creation

    IRCAM is an internationally recognized research center dedicated to creating new technologies for music. The institute offers a unique experimental environment where composers strive to enlarge their musical experience through the concepts expressed in new technologies.

    • Composers & Artists in Studio
    • Sivan Eldar in Studio
    • Mauro Lanza in studio
    • Chloé Thévenin in studio
    • Oren Boneh in studio
    • Tristan Murail in studio
    • Martin Matalon in studio
    • Sébastien Gaxie in studio
    • Murcof in the studio
    • Vimala Pons in studio
    • Lucie Antunes in studio
    • Deena Abdelwahed in the studio
    • Music-Fictions
    • Artistic Research Residency
    • Artistic Residencies: The Blog
    • Rendez Vous 24.25
    • 2024-2025
    • Replay Concerts
    • Seasons from 1996 to present
    • ManiFeste-2024 Website
    • ManiFeste festival from 2012 to 2024
    • L’Étincelle, IRCAM’s journal of creation
  • Transmission

    In support of IRCAM's research and creation missions, the educational program seeks to shed light on the current and future meaning of the interactions among the arts, sciences, and technology as well as sharing its models of knowledge, know-how, and innovations with the widest possible audience.

    • Training Courses
    • Training Courses 2025.26
    • Max, Max for Live
    • Computer-Assisted Composition
    • ASAP & Partiels
    • Sound spatialization
    • Generative AI
    • Practical Information
    • Higher Education
    • Cursus Program on Composition and Computer Music
    • Master ATIAM
    • Sound Design Master's Program
    • Mixed-Music
    • AIMove Master
    • Discover Research at IRCAM
    • Cultural Outreach
    • Cultural Mediation at Middle School Students
    • Médiations culturelles au lycée
    • Digital Workshops
    • TACT
    • Images of a Work Collection
    • Group Tours
    • ManiFeste-2025 Festival Academy
    • 2025 ÉLAN award
    • Spatial Composition Workshop
    • In Situ Polytopes
    • ULYSSES Ensemble
    • Auditors
  • Innovations

    Engaged with societal and economic issues at the intersection of culture and IT, research at Ircam has forged a reputation for itself in the world of international research as an interdisciplinary benchmark in the science and technology of sound and music, constantly attentive to the new needs and uses in society.

    • The IRCAM Forum
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Mauro Lanza in studio

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In the Dust of this Planet
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Prehistory of the Future | Artistic issues

Mauro LanzaThe story takes place in a far far away future, thousands, even millions of years away… It has been ages now since humankind has left this valley of tears. Traces of its past existence however, are everywhere, scattered in the dust of our planet. Some archaeologist from the future – is it a team of alien explorers? An artificial intelligence sent from a faraway land? Or maybe a human-made machine that has just woken up from a very long sleep? – discovers amongst the ruins and remains of our succeeding civilizations several devices and objects that grab their attention. In the course of their research, this Indiana Jones from outer space realizes that these objects and devices work in pair: the objects carry data, while the devices are intended to read that data. But what is that data and what purpose does it serve? Why is there so much of it and why has it been duplicated identically millions of times?

Would this conscious being, so distant from us, be able to hypothesize that this data is actually code to reproduce a soundwave? Would they understand what sound – that is to say, the vibration of air – even is? And if they don’t, could they comprehend the concept of music, even if they are not receptive to it? Would they be able to differentiate sound data from other kinds of data? And finally, would they be able to apprehend the concept of form or, being deprived of any notion of threshold, would they consider that everything in on a continuum, or on the contrary, a discretized series of moments or gestures?

In order to justify their expedition to their investors, or simply to write down their observations and synthesize their thoughts, our researcher starts composing from its parts what they imagine could be the whole. By doing so, they create a big mashup made up of all of these sounds and non-sounds, a kind of “in the style of human beings” where all time periods, all ideas, everything that might have moved them in some way or another, – but also all the flaws resulting from the conditions the objects were found in: glitches, scratch marks, dust, distortions caused by the heat, the cold or by magnetic fields – are mixed together. 

Imitating the machine | Technological Issues

For Mauro Lanza, the most technologically challenging aspect of his piece In the Dust of this Planet is to be able to put himself “in the shoes” of this future intelligence who he imagines to be using the same “learning” process as current learning machines – or at least to create the illusion. What results from this learning process naturally depends on the dataset it is based on (which can contain samples that have nothing to do with music, but also be influenced by different biases), as well as the set modalities (which vary according to the chosen parameters, such as the characteristics of sound he finds interesting, the level of granularity selected to analyze them, etc.). It is as if the composer himself became a sort of “black box”, in the same way the internal workings of the learning algorithms we use today still remain a mystery.

“I am using a huge dataset which contains more than 100.000 sound samples, with a single common denominator: a sort of vintage vibe, which includes sounds from old synthesizers, vinyl discs and tapes, as well as a whole song; the classic jazz tune Stardust, which is a nod to the title of the piece” tells Lanza

“I also used modular synthesizers that produce more or less chaotic sounds, as well as more traditional synthesis engines in the Csound application, oscillators, and sound and feedback generators.”

“All samples were analyzed automatically by the machine: I chose settings such as the noise level, the zero-crossing rate (which is the number of times the function representing the signal goes through 0), the spectral centroid (which is an average of the frequencies resulting from the spectral analysis of the sample), the degree of harmonicity, and the analysis of the main peaks… Then, I wrote an algorithm, using LISP language, that would dig around in my dataset for sounds matching certain criteria that seem relevant in terms of human sound perception depending on the part of the piece I was working on – while also defining a scope for deviation from the request. This step is conducted kind of blindly, in order to let the machine operate freely. The results I get are surprising every time. I then choose amongst them the samples I like the most.”

“Next step is analyzing the selected sample and its reproduction… And most importantly how it fits within the general form: what I find interesting is to see how sounds come together. Especially when dealing with chaotic sounds, that can completely transform into something else when a parameter on a synthesis module is even slightly modified…” As for the form, the idea is the same: to give the impression that operations are carried out by a non-human intelligence: “The structure is very rigid, set by unmovable rhymical workings. The form can be reminiscent of a slow deep-learning process: the beginning suggesting a process that is lacking in maturity, before the machine catches up and ends up learning too well, until it slips into excessive learning. Because when everything is considered the same by the machine, then nothing really matters anymore...”

Photo: Composer Mauro Lanza © Andris Kozlovskis

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Listen to: Mauro Lanza

  1. Burger Time ou les tentations de saint Antoine by Mauro Lanza (recorded at IRCAM, 2002)
  2. Ludus de Morte Regis by Mauro Lanza (recorded at the Maison de Radio France, 2016)
  3. Aschenblume by Mauro Lanza (recorded at IRCAM, 2002)
  4. The 1987 Max Headroom Broadcast Incident by Mauro Lanza (recorded at Centre Pompidou, 2017)

Biography

person

Lanza Mauro

Mauro Lanza  (né en 1975) étudie le piano à Venise et la musique électronique à l’Ircam. Teintées d’ironie, ses compositions sont, depuis ses débuts, le résultat d’un effort s…

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Concert
Transmission

Concert de clôture 2

Saturday 28 June 2025
Ircam
Premieres by Mauro Lanza, Sara Glojnaric and trainee composers from the Academy with the Ensemble Ulysses
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