A.I. KOMBOÏ: RE-IMAGINING XENAKIS' KOMBOÏ
THROUGH CYBER-HUMAN CO-CREATIVE
IMPROVISATION PRACTICE

Marco Fiorini, Lorenzo Colombo

► To cite this version:

Marco Fiorini, Lorenzo Colombo. A.I. KOMBOÏ: RE-IMAGINING XENAKIS' KOMBOÏ THROUGH CYBER-HUMAN CO-CREATIVE IMPROVISATION PRACTICE. Journées d'Informatique Musicale 2024, May 2024, Marseille, France. hal-04572304

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Submitted on 10 May 2024

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# A.I. Komboï: Re-Imagining Xenakis’ Komboï through Cyber-Human Co-Creative Improvisation Practice

Marco Fiorini, Lorenzo Colombo

► To cite this version:

Marco Fiorini, Lorenzo Colombo. A.I. Komboï: Re-Imagining Xenakis’ Komboï through Cyber-Human Co-Creative Improvisation Practice. Journées d'Informatique Musicale 2024, May 2024, Marseille, France. hal-04572304v2

HAL Id: hal-04572304

https://hal.science/hal-04572304v2

Submitted on 7 May 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# A.I. KOMBOÏ: RE-IMAGINING XENAKIS' KOMBOÏ THROUGH CYBER-HUMAN CO-CREATIVE IMPROVISATION PRACTICE

Marco Fiorini

IRCAM - STMS

CNRS - Sorbonne Université

Paris, France

marco.fiorini@ircam.fr

Lorenzo Colombo

DKDM

The Royal Danish Academy of Music

Copenhagen, Denmark

lorenzo.colombo@dkdm.dk

## RÉSUMÉ

Dans cet article, nous documentons une recherche artistique et scientifique dans laquelle nous réimaginons un morceau de musique contemporaine par le biais d'une pratique d'improvisation co-créative. Nous utilisons la partition originale de Iannis Xenakis, *Komboï*, comme une esquisse fondamentale, en extrayant des informations à la fois abstraites et structurées pour guider notre processus. En utilisant Somax2, un système d'IA cocréative pour l'improvisation issu du projet européen REACH auquel nous participons, nous avons reconstruit la partie clavecin de la pièce et conçu de nouvelles stratégies d'interaction adaptée pour un percussionniste en direct. Cette approche met en jeu des paramètres de contrôle de plus haut niveau permettant de naviguer dans la partition, ouvrant ainsi sur un nouveau paradigme d'interprétation et d'interaction. La nouvelle pièce, *A.I. Komboï*, a été créée en juin 2023 au Klang Festival à Copenhague. Cet article détaille les techniques, méthodes et stratégies à l'œuvre dans cette reconstruction improvisée qui constitue un véritable processus de réimagination de la composition de Xenakis et ouvre de nouvelles voies dans les aspects créatifs, performatifs et pédagogiques de la musique mixte dans le domaine de l'interaction Humain-IA.

## 1. INTRODUCTION

In the field of contemporary music, the convergence of human creativity with artificial intelligence has opened up a new area of compositional explorations. This article reports on an artistic and scientific research project in this field, in which a percussionist and a computer musician have reimagined Iannis Xenakis' seminal work, *Komboï*, through a process of improvisational practice. Central to this was the use of Somax2 [10], a co-creative AI-based software designed for improvisation, to augment the compositional process through real-time co-improvised interaction. We used Xenakis' original score as a foundational sketch, serving as a model for the extrapolation of musical abstraction parameters. These parameters, extracted from the score, were then transposed into specific instructions within the framework of Somax2. This symbiotic exchange between human interpretive intuition and the

generative capabilities of artificial intelligence led to the development of a detailed and distinctive musical work, culminating in a piece that not only pays homage to Xenakis' original vision, but also explores new concepts of co-creativity and interaction. Through this case study, we aim to contribute to the set of musical practices involving real-time human-machine interaction systems [43]. By examining this case, we seek to provide a comprehensive understanding of the methodologies and artistic choices that have guided our creative and research process.

In the following sections, we will contextualise our work within the sphere of music for percussion and live electronics, briefly detailing the corpus-based concatenative synthesis paradigm and the tools available within this domain, and we will elaborate on our complete workflow, providing insights into the interpretive processes, technological details and creative decisions that ended up into the creation of *A.I. Komboï*<fnref n="1" />. Subsequently, the results of this collaborative project will be discussed, reflecting on the broader implications and future prospects of these human-machine co-creative practices in the field of contemporary music composition and improvisation.

## 2. RELATED WORKS AND CONTEXT

Unresolved challenges are key to identifying possible new research directions. One such central challenge in computer music, as articulated by Miller Puckette, pertains to the need for a seamless mechanism that allows processes and representations of musical data to interoperate [49]. This work represents not only a personal take towards this unresolved challenge but also an exploration of the potential of human-machine co-creativity and improvisation practices, facilitated by state-of-the art software frameworks like Somax2. It presents a novel perspective on processes that were traditionally undertaken using specialized tools designed for Computer-Assisted Composition (CAC), such as OpenMusic [1], or the bach [2] and dada [31] libraries for Max. These platforms offered an important approach for real-time interaction and co-creativity in music creation by integrating score following techniques [23] with computational approaches [17].

<footnote n="1">1. https://www.youtube.com/watch?v=rUrYg-es7aI</footnote>
# A.I. KOMBOÏ: RE-IMAGINING XENAKIS' KOMBOÏ THROUGH CYBER-HUMAN CO-CREATIVE IMPROVISATION PRACTICE

Marco Fiorini

Sorbonne Université, IRCAM

CNRS, Ministère de la Culture, STMS

F-75004 Paris, France

marco.fiorini@ircam.fr

Lorenzo Colombo

DKDM

The Royal Danish Academy of Music

Copenhagen, Denmark

lorenzo.colombo@dkdm.dk

## RÉSUMÉ

Dans cet article, nous documentons une recherche artistique et scientifique dans laquelle nous réimaginons un morceau de musique contemporaine par le biais d'une pratique d'improvisation co-créative. Nous utilisons la partition originale de Iannis Xenakis, *Komboï*, comme une esquisse fondamentale, en extrayant des informations à la fois abstraites et structurées pour guider notre processus. En utilisant Somax2, un système d'IA cocréative pour l'improvisation issu du projet européen REACH auquel nous participons, nous avons reconstruit la partie clavecin de la pièce et conçu de nouvelles stratégies d'interaction adaptée pour un percussionniste en direct. Cette approche met en jeu des paramètres de contrôle de plus haut niveau permettant de naviguer dans la partition, ouvrant ainsi sur un nouveau paradigme d'interprétation et d'interaction. La nouvelle pièce, *A.I. Komboï*, a été créée en juin 2023 au Klang Festival à Copenhague. Cet article détaille les techniques, méthodes et stratégies à l'œuvre dans cette reconstruction improvisée qui constitue un véritable processus de réimagination de la composition de Xenakis et ouvre de nouvelles voies dans les aspects créatifs, performatifs et pédagogiques de la musique mixte dans le domaine de l'interaction Humain-IA.

## 1. INTRODUCTION

In the field of contemporary music, the convergence of human creativity with artificial intelligence has opened up a new area of compositional explorations. This article reports on an artistic and scientific research project in this field, in which a percussionist and a computer musician have reimagined Iannis Xenakis' seminal work, *Komboï*, through a process of improvisational practice. Central to this was the use of Somax2 [10], a co-creative AI-based software designed for improvisation, to augment the compositional process through real-time co-improvised interaction. We used Xenakis' original score as a foundational sketch, serving as a model for the extrapolation of musical abstraction parameters. These parameters, extracted from the score, were then transposed into specific instructions within the framework of Somax2. This symbiotic exchange between human interpretive intuition and the

generative capabilities of artificial intelligence led to the development of a detailed and distinctive musical work, culminating in a piece that not only pays homage to Xenakis' original vision, but also explores new concepts of co-creativity and interaction. Through this case study, we aim to contribute to the set of musical practices involving real-time human-machine interaction systems [43]. By examining this case, we seek to provide a comprehensive understanding of the methodologies and artistic choices that have guided our creative and research process.

In the following sections, we will contextualise our work within the sphere of music for percussion and live electronics, briefly detailing the corpus-based concatenative synthesis paradigm and the tools available within this domain, and we will elaborate on our complete workflow, providing insights into the interpretive processes, technological details and creative decisions that ended up into the creation of *A.I. Komboï*<fnref n="1" />. Subsequently, the results of this collaborative project will be discussed, reflecting on the broader implications and future prospects of these human-machine co-creative practices in the field of contemporary music composition and improvisation.

## 2. RELATED WORKS AND CONTEXT

Unresolved challenges are key to identifying possible new research directions. One such central challenge in computer music, as articulated by Miller Puckette, pertains to the need for a seamless mechanism that allows processes and representations of musical data to interoperate [49]. This work represents not only a personal take towards this unresolved challenge but also an exploration of the potential of human-machine co-creativity and improvisation practices, facilitated by state-of-the art software frameworks like Somax2. It presents a novel perspective on processes that were traditionally undertaken using specialized tools designed for Computer-Assisted Composition (CAC), such as OpenMusic [1], or the bach [2] and dada [31] libraries for Max. These platforms offered an important approach for real-time interaction and co-creativity in music creation by integrating score following techniques [23] with computational approaches [17].

<footnote n="1">1. https://www.youtube.com/watch?v=rUrYg-es7aI</footnote>
The paradigm of Corpus-Based Concatenative Synthesis (CBCS), exemplified by tools such as CataRT [56], now fully integrated in MuBu [55], has modernised real-time sound exploration in live performance and the CAC creative process. By exploiting large sound corpora, components and performers have the ability to manipulate and concatenate audio segments, resulting in entirely new compositions. A recent addition to this scenario, the FluCoMa [65] package, provides a complete toolkit for manipulating corpora, offering new possibilities to computer musicians [11].

**2.1. Music for Percussion and Electronics**

Contemporary compositions combining percussion and electronics have evolved significantly since their emergence [52]. Early pioneers such as Bruno Maderna and Edgard Varèse opened the way with revolutionary works like *Musica sur due Dimensioni* (1952) and *Déserts* (1954). Karlheinz Stockhausen continued this exploration with *Kontakte* (1958-1960) [61], incorporating quadrophonic tapes together with piano and percussion. Noteworthy contributions emerged in the late 1960s and early 1970s: William Cahn's *Etude for Taperecorder and Percussion* and Hans Werner Henze's *Prison Song* marked crucial moments in the genre. Live electronics were first introduced in ensemble contexts, notably in John Cage's *Imaginary Landscapes* and *Credo in Us*, composed between 1939 and 1942. Mauricio Kagel with *Transición II* (1950s) extended this trajectory, integrating live electronics with piano, percussion and tape recorders. Stockhausen's pieces from the mid-1960s introduce live electronic elements, requiring multiple performers for their execution [62]. One example is *Mikrophonie I* (1964), which uses a single tam-tam with live electronic controlled by specific performers. Alvin Lucier's repertoire includes innovative intersections of live electronics and acoustic instruments, often incorporating percussion. His seminal work, *Music for Solo Performer* (1965), utilises amplified brainwaves for electronic resonance within distributed percussion instruments. This distinctive approach, along with others such as sympathetic resonance in percussion, distinguishes Lucier's contributions [30].

Advances in music development environments, notably Max/MSP and Pure Data in the 1990s, provided new possibilities for solo percussion with live electronics. The piece *Six Japanese Gardens* (1993) by Kaija Saariaho exemplifies this change, employing a pedal to activate electronic components, including pre-recorded sounds and live audio processing. In the following decades, compositions such as Ben Hackbarth's *Open End* (2007) expanded this structure. Hackbarth integrated sounds from loudspeakers controlled by a Pure Data patch with a solo vibraphone, using sound events triggered by a pedal to activate resonance properties within the instrument, similar to the techniques first employed by Lucier.

This evolution underlines the rich world of possibilities in contemporary music, illustrating the dynamic interaction between percussion and electronics [33].

**2.2. Motivation**

To enhance and extend the aforementioned paradigms, it is important to consider the emerging role of Artificial Intelligence and its contributions to the artistic and scientific domains. The idea of using the generative potential of AI in tandem with human creativity has opened up new musical exploration possibilities [22]. Recent surveys of Herremans, Chuan and Chew [36], Carnovalini and Rodà [19] and Hernandez [35] show how the integration of AI tools into the creative process is constantly growing, demonstrating the potential of AI-driven compositional techniques. In this connection of scientific and artistic fields, a central concept is that of the musical agent. This has gradually evolved into a taxonomy of diverse applications [63, 5] but, in music improvisation and co-creation, the Voyager system by George E. Lewis stands as an early successful embodiment, relevant even today [41]. Subsequently, through innovations like Omax [7] and the contributions of the REACH (Raising Co-Creativity in Cyber-Human Musicianship) project at IRCAM, this notion has been further refined. In particular, the project REACH represents one of the forefront examples on AI musical co-creativity [8] and interaction between humans and machine in cyber-human contexts [9], where Somax2 is one of the main software developed within this project. Other noteworthy human-machine systems for music composition and improvisation based on reactive agents developed through the years include Cypher [53], ListeningLearning [21], Virtualband [44], GenJam [13], The Continuator [48], Improtek [46] and Dicy2 [47].

This scientific and artistic research therefore aims to extend conventional compositional boundaries and their typical scenarios through human-machine co-creativity and improvisational practices.

**2.3. Komboï**

*Komboï* (in Greek: κομβοί, meaning "knots") is a 1981 stochastic composition for harpsichord and percussion by Greek composer Iannis Xenakis (1922-2001). Together with *Oophaa*, it is one of the only two compositions for harpsichord and percussion written by Xenakis. It was composed in collaboration with harpsichordist Elisabeth Chojnacka and percussionist Sylvio Gualda, who premiered it on November 22nd, 1981 at Metz Festival in France <fnref n="2" />. The composition, approximately 17 minutes in duration, features one harpsichord, one vibraphone, various percussion instruments, and terracotta flower pots.

The piece is structured into five sections, with distinctive instrumentation and interludes. The opening section introduces an ostinato on bongos and rising tone clusters on the harpsichord, where Xenakis juxtaposes ordered percussion sounds with pitched notes to create intricate textures. The remarkable second section, titled *Crystal-line*, melds harpsichord and vibraphone, showcasing their complementary sonorities (see Figure 1). The percussion

<footnote n="2">2. https://brahms.ircam.fr/en/works/work/12825/</footnote>
The paradigm of Corpus-Based Concatenative Synthesis (CBCS), exemplified by tools such as CataRT [56], now fully integrated in MuBu [55], has modernised real-time sound exploration in live performance and the CAC creative process. By exploiting large sound corpora, components and performers have the ability to manipulate and concatenate audio segments, resulting in entirely new compositions. A recent addition to this scenario, the FluCoMa [65] package, provides a complete toolkit for manipulating corpora, offering new possibilities to computer musicians [11].

**2.1. Music for Percussion and Electronics**

Contemporary compositions combining percussion and electronics have evolved significantly since their emergence [52]. Early pioneers such as Bruno Maderna and Edgard Varèse opened the way with revolutionary works like *Musica sur due Dimensioni* (1952) and *Déserts* (1954). Karlheinz Stockhausen continued this exploration with *Kontakte* (1958-1960) [61], incorporating quadrophonic tapes together with piano and percussion. Noteworthy contributions emerged in the late 1960s and early 1970s: William Cahn's *Etude for Taperecorder and Percussion* and Hans Werner Henze's *Prison Song* marked crucial moments in the genre. Live electronics were first introduced in ensemble contexts, notably in John Cage's *Imaginary Landscapes* and *Credo in Us*, composed between 1939 and 1942. Mauricio Kagel with *Transición II* (1950s) extended this trajectory, integrating live electronics with piano, percussion and tape recorders. Stockhausen's pieces from the mid-1960s introduce live electronic elements, requiring multiple performers for their execution [62]. One example is *Mikrophonie I* (1964), which uses a single tam-tam with live electronic controlled by specific performers. Alvin Lucier's repertoire includes innovative intersections of live electronics and acoustic instruments, often incorporating percussion. His seminal work, *Music for Solo Performer* (1965), utilises amplified brainwaves for electronic resonance within distributed percussion instruments. This distinctive approach, along with others such as sympathetic resonance in percussion, distinguishes Lucier's contributions [30].

Advances in music development environments, notably Max/MSP and Pure Data in the 1990s, provided new possibilities for solo percussion with live electronics. The piece *Six Japanese Gardens* (1993) by Kaija Saariaho exemplifies this change, employing a pedal to activate electronic components, including pre-recorded sounds and live audio processing. In the following decades, compositions such as Ben Hackbarth's *Open End* (2007) expanded this structure. Hackbarth integrated sounds from loudspeakers controlled by a Pure Data patch with a solo vibraphone, using sound events triggered by a pedal to activate resonance properties within the instrument, similar to the techniques first employed by Lucier.

This evolution underlines the rich world of possibilities in contemporary music, illustrating the dynamic interaction between percussion and electronics [33].

**2.2. Motivation**

To enhance and extend the aforementioned paradigms, it is important to consider the emerging role of Artificial Intelligence and its contributions to the artistic and scientific domains. The idea of using the generative potential of AI in tandem with human creativity has opened up new musical exploration possibilities [22]. Recent surveys of Herremans, Chuan and Chew [36], Carnovalini and Rodà [19] and Hernandez [35] show how the integration of AI tools into the creative process is constantly growing, demonstrating the potential of AI-driven compositional techniques. In this connection of scientific and artistic fields, a central concept is that of the musical agent. This has gradually evolved into a taxonomy of diverse applications [63, 5] but, in music improvisation and co-creation, the Voyager system by George E. Lewis stands as an early successful embodiment, relevant even today [41]. Subsequently, through innovations like Omax [7] and the contributions of the REACH (Raising Co-Creativity in Cyber-Human Musicianship) project at IRCAM, this notion has been further refined. In particular, the project REACH represents one of the forefront examples on AI musical co-creativity [8] and interaction between humans and machine in cyber-human contexts [9], where Somax2 is one of the main software developed within this project. Other noteworthy human-machine systems for music composition and improvisation based on reactive agents developed through the years include Cypher [53], ListeningLearning [21], Virtualband [44], GenJam [13], The Continuator [48], Improtek [46] and Dicy2 [47].

This scientific and artistic research therefore aims to extend conventional compositional boundaries and their typical scenarios through human-machine co-creativity and improvisational practices.

**2.3. Komboï**

*Komboï* (in Greek: κομβοί, meaning "knots") is a 1981 stochastic composition for harpsichord and percussion by Greek composer Iannis Xenakis (1922-2001). Together with *Oophaa*, it is one of the only two compositions for harpsichord and percussion written by Xenakis. It was composed in collaboration with harpsichordist Elisabeth Chojnacka and percussionist Sylvio Gualda, who premiered it on November 22nd, 1981 at Metz Festival in France <fnref n="2" />. The composition, approximately 17 minutes in duration, features one harpsichord, one vibraphone, various percussion instruments, and terracotta flower pots.

The piece is structured into five sections, with distinctive instrumentation and interludes. The opening section introduces an ostinato on bongos and rising tone clusters on the harpsichord, where Xenakis juxtaposes ordered percussion sounds with pitched notes to create intricate textures. The remarkable second section, titled *Crystal-line*, melds harpsichord and vibraphone, showcasing their complementary sonorities (see Figure 1). The percussion

<footnote n="2">2. https://brahms.ircam.fr/en/works/work/12825/</footnote>
<figure><img src="image_1.png" /><figcaption>**Figure 1** – One of the many knots, or clouds of notes during the piece, extrapolated from section 2, *Crystalline*. Both percussion and harpsichord play with the concept of density over a common beat, that is however not explicitly highlighted.</figcaption></figure>

later incorporates flower pots, adding a new unexpected timbral layer. This integration of disparate elements exemplifies Xenakis’ exploration of musical knots on different musical axis, from the harmonic to the rhythmic one. Overall, *Komboï* offers a novel nuanced portrayal of the harpsichord and percussion, and has been described as revealing a more delicate aspect of Xenakis’ compositional style [34].

# 3. WORKFLOW

## 3.1. Corpus Creation

As thoroughly explained in [10], [15] and [16], Somax2 is an interactive system which improvises around a given musical material, aiming to produce a stylistically coherent improvisation while jointly listening to and adapting to live musical input. The system is trained on musical material selected by the user, from which it constructs a *corpus*, that will serve as a basis for the improvisation. In our case, this material consist of harpsichord MIDI corpora extrapolated from the original score, and treated as a sketching material to be recombined by the software in the live performance together with the musician on stage.

Differently from other CBCS systems like CataRT [56], Somax2 utilizes a notion of echoic memory in the navigation of the provided corpus and in the interaction process [10] [15] [16]; thus, it performs better with corpora that already have an internal structure and form. Xenakis’ *Komboï*, like many of his later works, is rooted in sieve theory. He developed the implication of this ancient mathematical theory in his composition during his time in Berlin in the 1960s [28] and published foundational material on it in [67] and [68], culminating in [69]. In Xenakis’ practice, this theory primarily deals with the creation of scales, offering a method to filter elements and construct musical structures. He applies the concept of filtering not only by passing elements through a sieve but also by using specific starting points and step distances. While pure sieve composition is a rich area of study, way beyond the scope of this research, it continues to offer new

perspectives on music generation techniques. In his PhD dissertation, Exarchos [28] detailed the relation between Xenakis and sieve theory from a compositional and practical standpoint, analysing the composer’s repertoire and practice. Ariza’s work in [4] exemplifies ongoing advancements in sieve theory and computer music, providing a Python implementation of Xenakis’ sieve process.

We employed a computational method to generate 22 distinct MIDI corpora to feed it to the system. These corpora served as compositional material for real-time interaction with the live percussionist during performances. The process involved the utilization of the AthenaCL library [4] and MuseScore4³, which provided a flexible framework for creating and manipulating musical sieves. These sieves, based on Xenakis’ stochastic composition technique [26], formed the basis for generating rhythmic structures. We extended this approach by integrating stochastic pitch selection from a set of pitches defined by the sieves, thus providing the melodic and harmonic content for Somax2 to navitage the corpora. The 22 resulting MIDI Corpora (see excerpts in Figures 2 and 3) were then seamlessly integrated into Somax2 for real-time interaction with the live percussionist, and loaded in 2 different Somax2 players, with specific paramterization for each section of the piece, as later described in Section 3.4.

<figure><img src="image_2.png" /><figcaption>**Figure 2** – Excerpt of a sieve reduction for section 2 (see Figure 1). The extended version of this sieve has been loaded into a Somax2 player as corpus material for the same section.</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>**Figure 3** – Reduction and juxtaposition of the right and left hand of the harpsichord at the end of section 2 (see Figure 1). In this section two Somax2 players have been used to play at the same time, with different tempo flows, to recreate the effect of a granular cloud of note drops.</figcaption></figure>

## 3.2. Onset Detection

In Somax2, as in any concatenative synthesis or corpus based systems, onset detection plays a crucial role in segmenting audio files into meaningful discrete events. This process relies on well-defined segmentation of the training corpus, in the audio usecase. While other segmentation

<footnote n="3">3. https://musescore.com</footnote>
<figure><img src="image_2.png" /><figcaption>**Figure 1** – One of the many knots, or clouds of notes during the piece, extrapolated from section 2, *Crystalline*. Both percussion and harpsichord play with the concept of density over a common beat, that is however not explicitly highlighted.</figcaption></figure>

later incorporates flower pots, adding a new unexpected timbral layer. This integration of disparate elements exemplifies Xenakis’ exploration of musical knots on different musical axis, from the harmonic to the rhythmic one. Overall, *Komboï* offers a novel nuanced portrayal of the harpsichord and percussion, and has been described as revealing a more delicate aspect of Xenakis’ compositional style [34].

# 3. WORKFLOW

## 3.1. Corpus Creation

As thoroughly explained in [10], [15] and [16], Somax2 is an interactive system which improvises around a given musical material, aiming to produce a stylistically coherent improvisation while jointly listening to and adapting to live musical input. The system is trained on musical material selected by the user, from which it constructs a *corpus*, that will serve as a basis for the improvisation. In our case, this material consist of harpsichord MIDI corpora extrapolated from the original score, and treated as a sketching material to be recombined by the software in the live performance together with the musician on stage.

Differently from other CBCS systems like CataRT [56], Somax2 utilizes a notion of echoic memory in the navigation of the provided corpus and in the interaction process [10] [15] [16]; thus, it performs better with corpora that already have an internal structure and form. Xenakis’ *Komboï*, like many of his later works, is rooted in sieve theory. He developed the implication of this ancient mathematical theory in his composition during his time in Berlin in the 1960s [28] and published foundational material on it in [67] and [68], culminating in [69]. In Xenakis’ practice, this theory primarily deals with the creation of scales, offering a method to filter elements and construct musical structures. He applies the concept of filtering not only by passing elements through a sieve but also by using specific starting points and step distances. While pure sieve composition is a rich area of study, way beyond the scope of this research, it continues to offer new

perspectives on music generation techniques. In his PhD dissertation, Exarchos [28] detailed the relation between Xenakis and sieve theory from a compositional and practical standpoint, analysing the composer’s repertoire and practice. Ariza’s work in [4] exemplifies ongoing advancements in sieve theory and computer music, providing a Python implementation of Xenakis’ sieve process.

We employed a computational method to generate 22 distinct MIDI corpora to feed it to the system. These corpora served as compositional material for real-time interaction with the live percussionist during performances. The process involved the utilization of the AthenaCL library [4] and MuseScore4³, which provided a flexible framework for creating and manipulating musical sieves. These sieves, based on Xenakis’ stochastic composition technique [26], formed the basis for generating rhythmic structures. We extended this approach by integrating stochastic pitch selection from a set of pitches defined by the sieves, thus providing the melodic and harmonic content for Somax2 to navitage the corpora. The 22 resulting MIDI Corpora (see excerpts in Figures 2 and 3) were then seamlessly integrated into Somax2 for real-time interaction with the live percussionist, and loaded in 2 different Somax2 players, with specific paramterization for each section of the piece, as later described in Section 3.4.

<figure><img src="image_3.png" /><figcaption>**Figure 2** – Excerpt of a sieve reduction for section 2 (see Figure 1). The extended version of this sieve has been loaded into a Somax2 player as corpus material for the same section.</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>**Figure 3** – Reduction and juxtaposition of the right and left hand of the harpsichord at the end of section 2 (see Figure 1). In this section two Somax2 players have been used to play at the same time, with different tempo flows, to recreate the effect of a granular cloud of note drops.</figcaption></figure>

## 3.2. Onset Detection

In Somax2, as in any concatenative synthesis or corpus based systems, onset detection plays a crucial role in segmenting audio files into meaningful discrete events. This process relies on well-defined segmentation of the training corpus, in the audio usecase. While other segmentation

<footnote n="3">3. https://musescore.com</footnote>
levels are possible, such as beat or bar, onset detection
typically serves as a prerequisite. Additionally, real-time
listening modules in Somax2 rely on onset detection to
handle input from live musicians. Detected onsets deter-
mine when to trigger new output and when to segment the
input stream for analysis.

There are two cases of onset detection in Somax2 : one
is computed offline on a user-specified corpus of audio
files, and the other is computed in real-time on input from
a musician. Somax2 is designed to be genre-agnostic, ca-
pable of working effectively with a wide range of classes
of sounds, from classical music to unpitched percussive
sounds, modern pop/rock, speech, etc. To accommodate
this diversity, the system employs different onset detection
algorithms. Notable examples include bonk [50], a low-
latency algorithm optimized for percussive sounds, and
yingb [7], a statistical model based on the Yin pitch de-
tection algorithm [25] for detecting onsets in monophonic
audio signals. Given the complex characteristics of dif-
ferent percussion instruments, we utilized the bonk al-
gorithm for conventionally "unpitched" instruments like
drums and congas. For melodic pitched instruments such
as vibraphone and flower pots, we employed the yin al-
gorithm to achieve accurate onset detection (see Figure 4).

<figure><img src="image_4.png" /><figcaption>**Figure 4** – Interaction scheme and signal flow for the se-
tup of the piece. Audio signal is in red, onset/beat detec-
tion in green, Somax2 core modules in blue, MIDI and
physical modelling in purple.</figcaption></figure>

**3.3. Real Time Beat Tracking**

Identifying the regular pulse, or beat, in music is a fun-
damental task, akin to tapping one's foot in time to a piece.
While humans often perform this task effortlessly, auto-
mating it in computer systems has proven challenging. As
Masataka Goto noted in [32], "the hierarchical beat struc-
ture that exists in the minds of performers is not explicitly

expressed in the music itself". Developing a real-time beat
tracker presents an additional challenge, as it must rely so-
lely on past and present information without access to fu-
ture data. This requires a causal approach, where predic-
tions of future beat locations are made based on historical
information alone.

Somax2 incorporates an integrated beat tracker develop-
ed by Laurent Bonnasse-Gahot, which draws on models
by Edward Large and John F. Kolen, as well as Petri Toi-
viainen [14, 40, 64]. However, the quality of the results of
this beat tracker on audio signals were not appropriate for
our specific task. Consequently, this beat tracker was not
utilized in testing and performances.

After thorough research, the btrack~ implementa-
tion by Adam M. Stark [60] was chosen as a suitable real-
time beat tracking algorithm for experimenting with So-
max2. This model combines tempo induction methods by
Davies and Plumbley [24], along with dynamic program-
ming by Ellis [27]. The algorithm, available under GNU
License, was adapted and compiled for the latest version
of Max/MSP as an external object and integrated into an
experimental version of Somax2 for testing with live au-
dio inputs.

The inclusion of a Max/MSP external for beat tracking
offers several advantages. It allows for the routing of tempo
information from both audio and MIDI influencers to the
players in Somax2. Additionally, each player can transmit
their own tempo information, enabling tempo feedback
within the group. This addition is expected to enhance the
tempo performances of the system and ensure its maintai-
nability in future developments. One could argue that the
addition of a new beat tracker goes against the maintai-
nability of the system. However, this turns out to be per-
fectly integrated, since, as mentioned earlier, Somax2 al-
ready has a beat tracker, although not optimized for our
specific case. This addition therefore relies on an external
Max/MSP object that turns out to be compiled once and
available on several iterations of processors and systems
(e.g., even on the new Apple Silicon ones) without requi-
ring special maintenance. In addition, the form of the data
output from the new object is homogeneous with Somax2
previous beat tracker, ensuring the integration, portability,
and eventual future maintenance of this prototype.

**3.4. Interaction Strategies with Somax2**

3.4.1. Navigation Model and Influence Match

The Somax2 system diverges from purely generative
approaches by directly constructing improvisation mate-
rial on the original musical data, eschewing the develop-
ment of an independent model. This methodology involves
segmenting the musical stream into *slices* and subjecting
each to a detailed analysis based on various musical fea-
tures, such as harmony, melody, and beats. The resulting
multilayer representation forms a *corpus* (as described in
Section 3.1). The corpus with its features will serve as the
core of Somax2 navigation model.
levels are possible, such as beat or bar, onset detection
typically serves as a prerequisite. Additionally, real-time
listening modules in Somax2 rely on onset detection to
handle input from live musicians. Detected onsets deter-
mine when to trigger new output and when to segment the
input stream for analysis.

There are two cases of onset detection in Somax2 : one
is computed offline on a user-specified corpus of audio
files, and the other is computed in real-time on input from
a musician. Somax2 is designed to be genre-agnostic, ca-
pable of working effectively with a wide range of classes
of sounds, from classical music to unpitched percussive
sounds, modern pop/rock, speech, etc. To accommodate
this diversity, the system employs different onset detection
algorithms. Notable examples include bonk [50], a low-
latency algorithm optimized for percussive sounds, and
yingb [7], a statistical model based on the Yin pitch de-
tection algorithm [25] for detecting onsets in monophonic
audio signals. Given the complex characteristics of dif-
ferent percussion instruments, we utilized the bonk al-
gorithm for conventionally "unpitched" instruments like
drums and congas. For melodic pitched instruments such
as vibraphone and flower pots, we employed the yin al-
gorithm to achieve accurate onset detection (see Figure 4).

<figure><img src="image_5.png" /><figcaption>**Figure 4** – Interaction scheme and signal flow for the se-
tup of the piece. Audio signal is in red, onset/beat detec-
tion in green, Somax2 core modules in blue, MIDI and
physical modelling in purple.</figcaption></figure>

3.3. Real Time Beat Tracking

Identifying the regular pulse, or beat, in music is a fun-
damental task, akin to tapping one's foot in time to a piece.
While humans often perform this task effortlessly, auto-
mating it in computer systems has proven challenging. As
Masataka Goto noted in [32], "the hierarchical beat struc-
ture that exists in the minds of performers is not explicitly

expressed in the music itself". Developing a real-time beat
tracker presents an additional challenge, as it must rely so-
lely on past and present information without access to fu-
ture data. This requires a causal approach, where predic-
tions of future beat locations are made based on historical
information alone.

Somax2 incorporates an integrated beat tracker develop-
ed by Laurent Bonnasse-Gahot, which draws on models
by Edward Large and John F. Kolen, as well as Petri Toi-
viainen [14, 40, 64]. However, the quality of the results of
this beat tracker on audio signals were not appropriate for
our specific task. Consequently, this beat tracker was not
utilized in testing and performances.

After thorough research, the btrack~ implementa-
tion by Adam M. Stark [60] was chosen as a suitable real-
time beat tracking algorithm for experimenting with So-
max2. This model combines tempo induction methods by
Davies and Plumbley [24], along with dynamic program-
ming by Ellis [27]. The algorithm, available under GNU
License, was adapted and compiled for the latest version
of Max/MSP as an external object and integrated into an
experimental version of Somax2 for testing with live au-
dio inputs.

The inclusion of a Max/MSP external for beat tracking
offers several advantages. It allows for the routing of tempo
information from both audio and MIDI influencers to the
players in Somax2. Additionally, each player can transmit
their own tempo information, enabling tempo feedback
within the group. This addition is expected to enhance the
tempo performances of the system and ensure its maintai-
nability in future developments. One could argue that the
addition of a new beat tracker goes against the maintai-
nability of the system. However, this turns out to be per-
fectly integrated, since, as mentioned earlier, Somax2 al-
ready has a beat tracker, although not optimized for our
specific case. This addition therefore relies on an external
Max/MSP object that turns out to be compiled once and
available on several iterations of processors and systems
(e.g., even on the new Apple Silicon ones) without requi-
ring special maintenance. In addition, the form of the data
output from the new object is homogeneous with Somax2
previous beat tracker, ensuring the integration, portability,
and eventual future maintenance of this prototype.

**3.4. Interaction Strategies with Somax2**

3.4.1. Navigation Model and Influence Match

The Somax2 system diverges from purely generative
approaches by directly constructing improvisation mate-
rial on the original musical data, eschewing the develop-
ment of an independent model. This methodology involves
segmenting the musical stream into *slices* and subjecting
each to a detailed analysis based on various musical fea-
tures, such as harmony, melody, and beats. The resulting
multilayer representation forms a *corpus* (as described in
Section 3.1). The corpus with its features will serve as the
core of Somax2 navigation model.
From the sequence of slices, a statistical sequence model is built, expressing the motivic organization, the musical structure with its repetitions and variations. While other statistical models based on variable markov models [66] or Factor Oracle [6] have been used in previous projects, Somax2 uses a statistical model based on n-grams [10], enabling non-linear exploration of the original data through multilayer representation of each feature of the corpus analysis. This statistical model thus accounts for short-term memory and continuity when recombining patterns at generation time, while storing the original musical content along with the multilayer feature analysis and sequence model in the corpus.

<figure><img src="image_5.png" /><figcaption>**Figure 5** – An overview of the steps through which Somax2 generates its output at each given point in time, reacting to the incoming influences from a live musician. Source [29].</figcaption></figure>

During interactions with a musician, Somax2 engages in real-time segmentation and multilayer analysis of the live input stream (see Figure 5), consistent with that done previously offline on the corpus material. This segmentation and conversion of a real-time audio stream from a musical to a symbolic domain, generates what are called *influences*. These influences contain a representation of the signal, according to the multidimensional system, that allows the navigation model to make comparisons between the input data (converted in influences) and those recorded in the corpus, loaded into a given Somax2 player.

<figure><img src="image_6.png" /><figcaption>**Figure 6** – The mechanism of memory peak profile update at the occurrence of each new influence. Source [10].</figcaption></figure>

Any matches between the influences arriving in real time and the material contained in the corpus produce activations, called *peaks*, in the sequential memory, where the input aligns with the model. These peaks, akin to probability distributions, signify potential output candidates, and are present on each of the four dimensional levels of the statistical model, allowing a complex balancing of influences (see Figure 5, the four levels correspond to internal melody, internal harmony, external melody, external

harmony). It is important to note that as new influences arrive, previous peaks are shifted, decayed and combined with incoming new ones, thus creating a short-term echoic memory system that continues to influence the navigation model, as shown in Figure 6.

Somax2 co-improvisation process is thus defined by the interplay of these three fundamental concepts :

- *slices*: short segments of the corpus;

- *influences*: multilayer data derived from real-time analysis of the input stream;

- *peaks*: dynamic memory activations.

The system's ability to dynamically balance its internal logic, shaped by self-listening, with external input from the musician results in a coherent yet unpredictable musical output. This co-improvisation process convincingly simulates the presence of an active agent in the collaborative musical experience, offering a nuanced blend of coherence and unexpectedness [18].

Unlike other generative systems, Somax2 preserves the fine-grained complexity of certain musical aspects by integrating them directly into the model, offering a specific approach to generative music, which differs from the current trend of deep learning models, like Google's [37, 51], positioning the human-in-the-loop [45] in a fundamental role of responsibility and awareness of their musical gestures.

### 3.4.2. *Signal Processing and Analysis*

The percussion performance is captured and sent in real-time to the computer running Somax2. As shown in Figure 4, the signal is analyzed using Somax2's system of influences [10] [15] [16], categorizing onset (tempo), pitch (melodic content), and chroma (harmonic content). As mentioned in Section 3.2, different algorithms are applied based on instrument tuning, with *bonk~* for non-tuned and polyphonic material, and *yin~* for melodic sections.

### 3.4.3. *Rhythmic Synchronization*

The piece encompasses sections with distinct rhythmic character. Various techniques are employed to achieve precise synchronization. For synchronized rhythmic interventions with different meters, the beat tracker introduced in Section 3.3 was used, complementing Somax2 reactive capabilities. Each corpus was created with different time and rhythmic subdivisions, according to the various sections of the piece, as described in Section 3.1 and as shown in Figure 2. Somax2 interaction parameters were used to control in real-time the flow and adapt the response of the system, according to its navigation model (see Figure 5). In particular, the *output probability* parameter has been highly used to control the density of the material played by Somax2, while the different *weights* for internal or external melodic and harmonic layers controlled the listening direction of the model itself, balancing the different incoming influences (as detailed through the navigation model in Section 3.4.1). Rhythmic strategies implied also
From the sequence of slices, a statistical sequence model is built, expressing the motivic organization, the musical structure with its repetitions and variations. While other statistical models based on variable markov models [66] or Factor Oracle [6] have been used in previous projects, Somax2 uses a statistical model based on n-grams [10], enabling non-linear exploration of the original data through multilayer representation of each feature of the corpus analysis. This statistical model thus accounts for short-term memory and continuity when recombining patterns at generation time, while storing the original musical content along with the multilayer feature analysis and sequence model in the corpus.

<figure><img src="image_6.png" /><figcaption>**Figure 5** – An overview of the steps through which Somax2 generates its output at each given point in time, reacting to the incoming influences from a live musician. Source [29].</figcaption></figure>

During interactions with a musician, Somax2 engages in real-time segmentation and multilayer analysis of the live input stream (see Figure 5), consistent with that done previously offline on the corpus material. This segmentation and conversion of a real-time audio stream from a musical to a symbolic domain, generates what are called *influences*. These influences contain a representation of the signal, according to the multidimensional system, that allows the navigation model to make comparisons between the input data (converted in influences) and those recorded in the corpus, loaded into a given Somax2 player.

<figure><img src="image_7.png" /><figcaption>**Figure 6** – The mechanism of memory peak profile update at the occurrence of each new influence. Source [10].</figcaption></figure>

Any matches between the influences arriving in real time and the material contained in the corpus produce activations, called *peaks*, in the sequential memory, where the input aligns with the model. These peaks, akin to probability distributions, signify potential output candidates, and are present on each of the four dimensional levels of the statistical model, allowing a complex balancing of influences (see Figure 5, the four levels correspond to internal melody, internal harmony, external melody, external

harmony). It is important to note that as new influences arrive, previous peaks are shifted, decayed and combined with incoming new ones, thus creating a short-term echoic memory system that continues to influence the navigation model, as shown in Figure 6.

Somax2 co-improvisation process is thus defined by the interplay of these three fundamental concepts :

— *slices*: short segments of the corpus;

— *influences*: multilayer data derived from real-time analysis of the input stream;

— *peaks*: dynamic memory activations.

The system's ability to dynamically balance its internal logic, shaped by self-listening, with external input from the musician results in a coherent yet unpredictable musical output. This co-improvisation process convincingly simulates the presence of an active agent in the collaborative musical experience, offering a nuanced blend of coherence and unexpectedness [18].

Unlike other generative systems, Somax2 preserves the fine-grained complexity of certain musical aspects by integrating them directly into the model, offering a specific approach to generative music, which differs from the current trend of deep learning models, like Google's [37, 51], positioning the human-in-the-loop [45] in a fundamental role of responsibility and awareness of their musical gestures.

### 3.4.2. *Signal Processing and Analysis*

The percussion performance is captured and sent in real-time to the computer running Somax2. As shown in Figure 4, the signal is analyzed using Somax2's system of influences [10] [15] [16], categorizing onset (tempo), pitch (melodic content), and chroma (harmonic content). As mentioned in Section 3.2, different algorithms are applied based on instrument tuning, with *bonk~* for non-tuned and polyphonic material, and *yin~* for melodic sections.

### 3.4.3. *Rhythmic Synchronization*

The piece encompasses sections with distinct rhythmic character. Various techniques are employed to achieve precise synchronization. For synchronized rhythmic interventions with different meters, the beat tracker introduced in Section 3.3 was used, complementing Somax2 reactive capabilities. Each corpus was created with different time and rhythmic subdivisions, according to the various sections of the piece, as described in Section 3.1 and as shown in Figure 2. Somax2 interaction parameters were used to control in real-time the flow and adapt the response of the system, according to its navigation model (see Figure 5). In particular, the *output probability* parameter has been highly used to control the density of the material played by Somax2, while the different *weights* for internal or external melodic and harmonic layers controlled the listening direction of the model itself, balancing the different incoming influences (as detailed through the navigation model in Section 3.4.1). Rhythmic strategies implied also
the changing of different tempo in the players, as well as
the use of the *cut* parameter to enhance the temporal syn-
chronisation of the players and the live musician (see Fi-
gures 7a and 7b). This particular parameter works on the
flow of onsets, controlling whether the currently played
event should be interrupted or not. By turning it on, the
current event is interrupted when a new onset arrives, trig-
gering immediately the generation of a new event, and
enforcing temporal synchronization via the beat tracker.
Thanks to these strategies we were able to structure dif-
ferent temporal synchronization levels, and we could re-
combine the corpus based on the related interaction stra-
tegy for each section. Furthermore, thanks also to its *conti-
nuous* mode, Somax2 is capable of overturning the inter-
action system based on reaction to influences (described
in Section 3.4.1) and propose material, not only waiting to
react to an incoming musical input, but starting the inter-
action, and then dynamically adapt to it as new influences
arrive [29].

3.4.4. Corpora and Cues

22 MIDI corpora have been used to align with Xenakis' compositional processes and rhythmic interactions. These are loaded into 2 Somax2 players during the performance. 16 cues facilitate corpus loading and piece navigation. Player characteristics are dynamically adjusted in cues, enhancing the interpretative nuances. Dynamics are controlled via the Arturia MiniFreak's <fnref n="4" /> master volume potentiometer, spanning from piano to fortissimo. The Novation Launchcontrol XL ⁵ facilitates real-time interaction with cues and internal Somax2 parameters.

These strategies establish a framework for a successful integration of live performance and Somax2-generated elements, ensuring a faithful yet co-creative rendition of the piece by following the original score while playing and manipulating the different parameters (see Figures 7a and 7b).

<figure><img src="image_7.png" /><figcaption>(a) Player in Section 1.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>(b) Player in Section 2.</figcaption></figure>

**Figure 7** – Overview of the same Somax2 player in two different sections of the piece. Note the different settings of the interaction parameters as described in Section 3.4.3

3.5. Technical Setup

For the performance at Klang Festival <fnref n="6" /> at the Royal Danish Academy of Music in Copenhagen on June 6th, 2023, the percussion ensemble comprises a vibraphone, two wood blocks, two bongos, three tumbas, four tom-toms, a bass drum and seven flowerpots. These instruments are captured using overhead narrow condenser microphones, with each group of percussion instruments assigned to a separate microphone pair (see Figure 8).

The audio from the percussion is routed to an Ableton Live session, and then to a second computer running Somax2. Two computers are used to separate the tasks : on the first one, we captured the percussion sound sources and grouped them as pairs of stereo signals, according to the different percussion groups played in every section ; these signals are sent to the second computer which is in charge of the performative co-improvisation side, running Somax2 and being controlled by one of the performers.

Somax2 serves as the core generative co-creative sys-
tem for the performance. A Max/MSP patch facilitates
real-time communication between the external musician
and the software. The Somax2 players are set to MIDI
mode, allowing them to interact with the pre-transcribed
MIDI corpora corresponding to different composed sec-
tions (as discussed in Section 3.1). The MIDI output is
sent to the Arturia MiniFreak for sound generation, and
then delivered to the front of house as a stereo signal.

To reconstruct the harpsichord sound in A.I. *Komboï*, a digital harpsichord tone was synthesized using physical modeling techniques based on Karplus-Strong string synthesis [38, 39, 58] on an Arturia MiniFreak hardware synthesizer. The Arturia MiniFreak was chosen for its versatility and capability to combine dual digital sound engines with analog filters, modulations, effects, and two oscillators. It features a VST version (MiniFreak V) for advanced preset management and seamless integration with the physical keyboard. Additionally, it provides MIDI in and out functionality, crucial for sending MIDI messages from the Max/MSP patch used in the performance. A Novation Launchpad XL is used to control Somax2 parameters and navigate the piece, with a direct connection to the Max/MSP patch.

4. DISCUSSION

Focusing on Iannis Xenakis’ composition *Komboï*, our
goal was to reimagine this seminal piece through the lens
of co-creative improvisation. The use of the AI-driven soft-
ware Somax2, was a central contribution in this research.
This software proved to serve not only as a tool for pure
improvisation, but it also facilitates a compositional ap-
proach to the creative process. This exemplifies a typi-
cal paradigm of contemporary music composition by ex-
tending both compositional and improvisational practices,
where *comprovisation* is already well established as a form

<footnote n="4">4. https://www.arturia.com/products/
hardware-synths/minifreak/minifreakv
5. https://novationmusic.com/products/
launch-control-x1</footnote>

<footnote n="6">6. https://klang.dk/2023/program/
lorenzo-colombo-debutkoncert</footnote>
the changing of different tempo in the players, as well as
the use of the *cut* parameter to enhance the temporal syn-
chronisation of the players and the live musician (see Fi-
gures 7a and 7b). This particular parameter works on the
flow of onsets, controlling whether the currently played
event should be interrupted or not. By turning it on, the
current event is interrupted when a new onset arrives, trig-
gering immediately the generation of a new event, and
enforcing temporal synchronization via the beat tracker.
Thanks to these strategies we were able to structure dif-
ferent temporal synchronization levels, and we could re-
combine the corpus based on the related interaction stra-
tegy for each section. Furthermore, thanks also to its *conti-
nuous* mode, Somax2 is capable of overturning the inter-
action system based on reaction to influences (described
in Section 3.4.1) and propose material, not only waiting to
react to an incoming musical input, but starting the inter-
action, and then dynamically adapt to it as new influences
arrive [29].

3.4.4. *Corpora and Cues*

22 MIDI corpora have been used to align with Xenakis’ compositional processes and rhythmic interactions. These are loaded into 2 Somax2 players during the performance. 16 cues facilitate corpus loading and piece navigation. Player characteristics are dynamically adjusted in cues, enhancing the interpretative nuances. Dynamics are controlled via the Arturia MiniFreak’s <fnref n="4" /> master volume potentiometer, spanning from piano to fortissimo. The Novation Launchcontrol XL ⁵ facilitates real-time interaction with cues and internal Somax2 parameters.

These strategies establish a framework for a successful integration of live performance and Somax2-generated elements, ensuring a faithful yet co-creative rendition of the piece by following the original score while playing and manipulating the different parameters (see Figures 7a and 7b).

<figure><img src="image_8.png" /><figcaption>(a) Player in Section 1.</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>(b) Player in Section 2.</figcaption></figure>

**Figure 7** – Overview of the same Somax2 player in two different sections of the piece. Note the different settings of the interaction parameters as described in Section 3.4.3

**3.5. Technical Setup**

For the performance at Klang Festival <fnref n="6" /> at the Royal Danish Academy of Music in Copenhagen on June 6th, 2023, the percussion ensemble comprises a vibraphone, two wood blocks, two bongos, three tumbas, four tom-toms, a bass drum and seven flowerpots. These instruments are captured using overhead narrow condenser microphones, with each group of percussion instruments assigned to a separate microphone pair (see Figure 8).

The audio from the percussion is routed to an Ableton Live session, and then to a second computer running Somax2. Two computers are used to separate the tasks : on the first one, we captured the percussion sound sources and grouped them as pairs of stereo signals, according to the different percussion groups played in every section ; these signals are sent to the second computer which is in charge of the performative co-improvisation side, running Somax2 and being controlled by one of the performers.

Somax2 serves as the core generative co-creative system for the performance. A Max/MSP patch facilitates real-time communication between the external musician and the software. The Somax2 players are set to MIDI mode, allowing them to interact with the pre-transcribed MIDI corpora corresponding to different composed sections (as discussed in Section 3.1). The MIDI output is sent to the Arturia MiniFreak for sound generation, and then delivered to the front of house as a stereo signal.

To reconstruct the harpsichord sound in *A.I. Komboï*, a digital harpsichord tone was synthesized using physical modeling techniques based on Karplus-Strong string synthesis [38, 39, 58] on an Arturia MiniFreak hardware synthesizer. The Arturia MiniFreak was chosen for its versatility and capability to combine dual digital sound engines with analog filters, modulations, effects, and two oscillators. It features a VST version (MiniFreak V) for advanced preset management and seamless integration with the physical keyboard. Additionally, it provides MIDI in and out functionality, crucial for sending MIDI messages from the Max/MSP patch used in the performance. A Novation Launchpad XL is used to control Somax2 parameters and navigate the piece, with a direct connection to the Max/MSP patch.

4. DISCUSSION

Focusing on Iannis Xenakis’ composition *Komboï*, our goal was to reimagine this seminal piece through the lens of co-creative improvisation. The use of the AI-driven software Somax2, was a central contribution in this research. This software proved to serve not only as a tool for pure improvisation, but it also facilitates a compositional approach to the creative process. This exemplifies a typical paradigm of contemporary music composition by extending both compositional and improvisational practices, where *comprovisation* is already well established as a form

<footnote n="4">4. https://www.arturia.com/products/hardware-synths/minifreak/minifreakv
5. https://novationmusic.com/products/launch-control-xl</footnote>

<footnote n="6">6. https://klang.dk/2023/program/lorenzo-colombo-debutkoncert</footnote>
<figure><img src="image_9.png" /><figcaption>**Figure 8** – Technical and instrumental setup for A.I. Komboï, as performed at Klang Festival at the Royal Danish Academy of Music in Copenhagen on June 6th 2023.</figcaption></figure>

of reinterpretation and live augmentation of a composed piece [57] and has even led to psychological studies on creative thinking [20].

The decision to employ the original score of *Komboï* as a foundational sketch was guided by the understanding that Xenakis’ notation encapsulated a wealth of abstract musical ideas. Xenakis, a pioneer in the exploration of mathematical and architectural concepts in composition, was known for his innovative approach to utilizing sketches in composition [70]. His use of graphic notation and mathematical models served as a precursor to our own approach, emphasizing the potential richness that can be extracted from a composer’s notational framework. While interpretations of Xenakis’ piano [3] and trombone [42] compositions from sketches have been previously explored, to our knowledge such practices have not yet been extended to percussion pieces in his repertoire, particularly within the context of real-time co-improvisation. Our approach therefore starts from the typical practices of Computer-Assisted Composition (CAC), seeking to take new directions in the practice of collective creation between human and machine. By distilling abstract musical parameters from the score, we were able to extract essential compositional elements that formed the basis for our exploration within the Somax2 software. This process facilitated a coherent transition from Xenakis’ original composition to our reimagined interpretation, ensuring a cohesive link between the two works.

In addition, it is worth noting that in our reinterpretation of *A.I. Komboï*, we synthesized the sound of the harpsichord using physical modeling techniques [12]. This approach expanded the sound palette of the original work, transforming it into a piece of mixed music. The combination of an acoustic instrument and live electronics creates a blend of traditional and contemporary elements, offering listeners a new auditory experience of the piece.

## 4.1. Future Works

Building on what we have learned from *A.I. Komboï*, our future intentions are to aim to further extend the ideas of co-creative interaction and co-improvisational practices. Significant attention will be paid to re-imagining another

Xenakis’ composition, *Psappha*, originally written for solo percussion. In this new project, the performer will take a central role in the system, directly controlling Somax2 through gesture and movement interaction techniques. This approach departs from the kind of collaborative structure detailed in *A.I. Komboï*, offering a new perspective on the potential of human-machine interaction in solo musical performance.

The adaptation of *Psappha* presents a unique opportunity to explore the role of solo performance within co-creative practices. By placing the performer under the direct control of Somax2, we wish to explore even further the interaction link between human expressiveness and algorithm responsiveness. Thanks to this, we aim to explore in more depth the boundaries of creative instrumentality and machine musicianship. This new concept of creative instrument [54], where the instrument itself takes on an autonomous role but plays also together with a performer, pursues the idea of a cyber-human reality, central to the REACH project, where the user’s body itself is augmented by the instrument’s capacity, and the feedback loop that is created between the machine and the human’s mind and body represents new dimensions of musical expression and co-creative musical thinking.

## 5. CONCLUSIONS

In this paper, we presented a specific case of recreating a musical work from an existing piece of Xenakis’ repertoire and re-imagining it using Somax2, a real-time reactive co-improvisation system. Starting from the CBCS paradigm, we detailed a working process in which this technique, widely employed in compositional contexts, is now directed towards co-improvisation practices in order to obtain a new rendition of the original composition.

After an analysis of the piece, *Komboï*'s compositional techniques were studied and extrapolated into interaction and control parameters within the our framework, creating a new version of the original piece, called *A.I. Komboï*. Our interpretation not only proves to be consistent with the original work, but having been performed live with the composer's score as a guide and structural sketch, it turns out to be the result of a synergy work between AI processes and human creativity. This specific setting argues in favour of the co-creative intervention between human and machine, which is necessary to find typical factors of unpredictability and emergence of complex situations within a structured musical interaction, normally difficult to achieve with purely generative AI systems.

We believe our research may have significant implications for future co-creative practices in composition and improvisation. Furthermore, as each new piece approached from this perspective may result in new challenges of system management and interaction strategies, this paradigm opens up new explorations, contributing to the broad field of human-computer interaction and positioning itself as a valid approach not only in performative and creative contexts but also in the educational sphere.
<figure><img src="image_10.png" /><figcaption>**Figure 8** – Technical and instrumental setup for A.I. Komboï, as performed at Klang Festival at the Royal Danish Academy of Music in Copenhagen on June 6th 2023.</figcaption></figure>

of reinterpretation and live augmentation of a composed piece [57] and has even led to psychological studies on creative thinking [20].

The decision to employ the original score of *Komboï* as a foundational sketch was guided by the understanding that Xenakis’ notation encapsulated a wealth of abstract musical ideas. Xenakis, a pioneer in the exploration of mathematical and architectural concepts in composition, was known for his innovative approach to utilizing sketches in composition [70]. His use of graphic notation and mathematical models served as a precursor to our own approach, emphasizing the potential richness that can be extracted from a composer’s notational framework. While interpretations of Xenakis’ piano [3] and trombone [42] compositions from sketches have been previously explored, to our knowledge such practices have not yet been extended to percussion pieces in his repertoire, particularly within the context of real-time co-improvisation. Our approach therefore starts from the typical practices of Computer-Assisted Composition (CAC), seeking to take new directions in the practice of collective creation between human and machine. By distilling abstract musical parameters from the score, we were able to extract essential compositional elements that formed the basis for our exploration within the Somax2 software. This process facilitated a coherent transition from Xenakis’ original composition to our reimagined interpretation, ensuring a cohesive link between the two works.

In addition, it is worth noting that in our reinterpretation of *A.I. Komboï*, we synthesized the sound of the harpsichord using physical modeling techniques [12]. This approach expanded the sound palette of the original work, transforming it into a piece of mixed music. The combination of an acoustic instrument and live electronics creates a blend of traditional and contemporary elements, offering listeners a new auditory experience of the piece.

**4.1. Future Works**

Building on what we have learned from *A.I. Komboï*, our future intentions are to aim to further extend the ideas of co-creative interaction and co-improvisational practices. Significant attention will be paid to re-imagining another

Xenakis’ composition, *Psappha*, originally written for solo percussion. In this new project, the performer will take a central role in the system, directly controlling Somax2 through gesture and movement interaction techniques. This approach departs from the kind of collaborative structure detailed in *A.I. Komboï*, offering a new perspective on the potential of human-machine interaction in solo musical performance.

The adaptation of *Psappha* presents a unique opportunity to explore the role of solo performance within co-creative practices. By placing the performer under the direct control of Somax2, we wish to explore even further the interaction link between human expressiveness and algorithm responsiveness. Thanks to this, we aim to explore in more depth the boundaries of creative instrumentality and machine musicianship. This new concept of creative instrument [54], where the instrument itself takes on an autonomous role but plays also together with a performer, pursues the idea of a cyber-human reality, central to the REACH project, where the user’s body itself is augmented by the instrument’s capacity, and the feedback loop that is created between the machine and the human’s mind and body represents new dimensions of musical expression and co-creative musical thinking.

**5. CONCLUSIONS**

In this paper, we presented a specific case of recreating a musical work from an existing piece of Xenakis’ repertoire and re-imagining it using Somax2, a real-time reactive co-improvisation system. Starting from the CBCS paradigm, we detailed a working process in which this technique, widely employed in compositional contexts, is now directed towards co-improvisation practices in order to obtain a new rendition of the original composition.

After an analysis of the piece, *Komboï*'s compositional techniques were studied and extrapolated into interaction and control parameters within the our framework, creating a new version of the original piece, called *A.I. Komboï*. Our interpretation not only proves to be consistent with the original work, but having been performed live with the composer's score as a guide and structural sketch, it turns out to be the result of a synergy work between AI processes and human creativity. This specific setting argues in favour of the co-creative intervention between human and machine, which is necessary to find typical factors of unpredictability and emergence of complex situations within a structured musical interaction, normally difficult to achieve with purely generative AI systems.

We believe our research may have significant implications for future co-creative practices in composition and improvisation. Furthermore, as each new piece approached from this perspective may result in new challenges of system management and interaction strategies, this paradigm opens up new explorations, contributing to the broad field of human-computer interaction and positioning itself as a valid approach not only in performative and creative contexts but also in the educational sphere.
# 6. ACKNOWLEDGMENTS

The authors would like to thank the Institut de Recherche et Coordination Acoustique/Musique (IRCAM) and the Royal Danish Academy of Music (DKDM) for their support during the research and for providing the necessary facilities for it to take place, as well as Klang Festival for commissioning the project. This research is supported by the European Research Council (ERC) as part of the Raising Co-Creativity in Cyber-Human Musicianship (REACH) Project directed by Gérard Assayag, under the European Union's Horizon 2020 research and innovation programme (GA #883313), and by Koda Kultur.

# 7. REFERENCES

[1] Agon, C., Assayag, G., Laurson, M., and Rueda, C. "Computer Assisted Composition at Ircam", *Computer Music Journal*, 23-5, MIT press, 1999

[2] Agostini, A., and Ghisi, D. "A Max Library for Musical Notation and Computer-Aided Composition", *Computer Music Journal*, 39-2, MIT press, 2015

[3] Antoniadis, P., Paschalidou, S., Duval, A., Jégo, J.-F., and Bevilacqua, F. "Rendering embodied experience into multimodal data : concepts, tools and applications for Xenakis’ piano performance", *Xenakis 22 : Centenary International Symposium*, 2022

[4] Ariza, C. "The Xenakis Sieve as Object : A New Model and a Complete Implementation", *Journal of New Music Research*, 29-2, MIT press, 2005

[5] Armitage, J., and Magnusson, T. "Agential Scores : Artificial Life for Emergent, Self-Organising and Entangled Music Notation" *Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR*, 2023

[6] Assayag, G., and Dubnov, S. "Using Factor Oracles for machine Improvisation" *Soft Computing*, 8-9, 2004

[7] Assayag, G., Bloch, G., Chemillier, M., Cont, A., and Dubnov, S. "Omax brothers : a dynamic topology of agents for improvization learning", *Proceedings of the 1st ACM workshop on Audio and music computing multimedia*, 2006

[8] Assayag, G. "Co-créativité humains-machines. Une réflexion sur les indisciplines symboliques" *Revue Francophone d'Informatique et Musique*, 8-7, Culture du code, 2020

[9] Assayag, G. "Human-Machine Co-Creativity" *Bernard Lubat, Gérard Assayag, Marc Chemillier. Artisticiel / Cyber-Improvisations*, Phonofaune, Dialogiques d'Uzeste, 2021

[10] Assayag, G., Bonnasse-Gahot, L., and Borg, J. "Co-creative Interaction : Somax2 and the REACH Project", *Computer Music Journal*, 1-19, MIT press, 2024.

[11] Bell, J. "Maps As Scores : “Timbre Space” Representations in Corpus-Based Concatenative Synthesis", *Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR*, 2023

[12] Bilbao, S. D. *Numerical sound synthesis : finite difference schemes and simulation in musical acoustics*, Wiley Publishing, 2009

[13] Biles, J. "GenJam : A genetic algorithm for generating jazz solos" *Proceedings of the international computer music conference*, 1994

[14] Bonnasse-Gahot, L. "Donner à OMax le sens du rythme : vers une improvisation plus riche avec la machine", *École des Hautes Études en sciences sociales, Internal Report*, 2010

[15] Borg, J. "The Somax 2 Theoretical Model", *STMS-IRCAM, Technical Report*, 2021

[16] Borg, J. "The Somax 2 Software Architecture Rev. 0.2.0", *STMS-IRCAM, Technical Report*, 2021

[17] Bresson, J. and Chadabe, J. "Interactive Composition : New Steps in Computer Music Research", *Journal of New Music Research*, 46-1, MIT press, 2017

[18] Canonne, C., and Garnier, N. B. "Cognition and segmentation in collective free improvisation : An exploratory study" *International Conference on Music Perception and Cognition*, 2012

[19] Carnovalini, F., and Rodà, A. "Computational Creativity and Music Generation Systems : An Introduction to the State of the Art", *Frontiers in Artificial Intelligence*, 14-3, 2020

[20] Collins, D. "A synthesis process model of creative thinking in music composition", *Psychology of Music*, 33-2, SAGE, 2005

[21] Collins, N. "LL : Listening and learning in an interactive improvisation system" *Technical Report*, University of Sussex, 2011

[22] Cook, N. *Beyond the Score : Music as Performance*, Oxford University Press, 2019

[23] Cont, A. "ANTESCOFO : Anticipatory Synchronization and Control of Interactive Parameters in Computer Music", *International Computer Music Conference (ICMC)*, 2008

[24] Davies, M. E. P., and Plumbley, M. D. "Context-dependent beat tracking of musical audio", *IEEE Transactions on Audio, Speech and Language Processing*, 15-3, 2007

[25] De Cheveigné, A., and Kawahara, H. "YIN, a fundamental frequency estimator for speech and music", *The Journal of the Acoustical Society of America*, 111-4, 2002

[26] Di Scipio, A. "Compositional Models in Xenakis’s Electroacoustic Music" *Perspective of New Music*, 36-2, 1998
# 6. ACKNOWLEDGMENTS

The authors would like to thank the Institut de Recherche et Coordination Acoustique/Musique (IRCAM) and the Royal Danish Academy of Music (DKDM) for their support during the research and for providing the necessary facilities for it to take place, as well as Klang Festival for commissioning the project. This research is supported by the European Research Council (ERC) as part of the Raising Co-Creativity in Cyber-Human Musicianship (REACH) Project directed by Gérard Assayag, under the European Union's Horizon 2020 research and innovation programme (GA #883313), and by Koda Kultur.

# 7. REFERENCES

[1] Agon, C., Assayag, G., Laurson, M., and Rueda, C. "Computer Assisted Composition at Ircam", *Computer Music Journal*, 23-5, MIT press, 1999

[2] Agostini, A., and Ghisi, D. "A Max Library for Musical Notation and Computer-Aided Composition", *Computer Music Journal*, 39-2, MIT press, 2015

[3] Antoniadis, P., Paschalidou, S., Duval, A., Jégo, J.-F., and Bevilacqua, F. "Rendering embodied experience into multimodal data : concepts, tools and applications for Xenakis’ piano performance", *Xenakis 22 : Centenary International Symposium*, 2022

[4] Ariza, C. "The Xenakis Sieve as Object : A New Model and a Complete Implementation", *Journal of New Music Research*, 29-2, MIT press, 2005

[5] Armitage, J., and Magnusson, T. "Agential Scores : Artificial Life for Emergent, Self-Organising and Entangled Music Notation" *Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR*, 2023

[6] Assayag, G., and Dubnov, S. "Using Factor Oracles for machine Improvisation" *Soft Computing*, 8-9, 2004

[7] Assayag, G., Bloch, G., Chemillier, M., Cont, A., and Dubnov, S. "Omax brothers : a dynamic topology of agents for improvization learning", *Proceedings of the 1st ACM workshop on Audio and music computing multimedia*, 2006

[8] Assayag, G. "Co-créativité humains-machines. Une réflexion sur les indisciplines symboliques" *Revue Francophone d'Informatique et Musique*, 8-7, Culture du code, 2020

[9] Assayag, G. "Human-Machine Co-Creativity" *Bernard Lubat, Gérard Assayag, Marc Chemillier. Artisticiel / Cyber-Improvisations*, Phonofaune, Dialogiques d'Uzeste, 2021

[10] Assayag, G., Bonnasse-Gahot, L., and Borg, J. "Co-creative Interaction : Somax2 and the REACH Project", *Computer Music Journal*, 1-19, MIT press, 2024.

[11] Bell, J. "Maps As Scores : “Timbre Space” Representations in Corpus-Based Concatenative Synthesis", *Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR*, 2023

[12] Bilbao, S. D. *Numerical sound synthesis : finite difference schemes and simulation in musical acoustics*, Wiley Publishing, 2009

[13] Biles, J. "GenJam : A genetic algorithm for generating jazz solos" *Proceedings of the international computer music conference*, 1994

[14] Bonnasse-Gahot, L. "Donner à OMax le sens du rythme : vers une improvisation plus riche avec la machine", *École des Hautes Études en sciences sociales, Internal Report*, 2010

[15] Borg, J. "The Somax 2 Theoretical Model", *STMS-IRCAM, Technical Report*, 2021

[16] Borg, J. "The Somax 2 Software Architecture Rev. 0.2.0", *STMS-IRCAM, Technical Report*, 2021

[17] Bresson, J. and Chadabe, J. "Interactive Composition : New Steps in Computer Music Research", *Journal of New Music Research*, 46-1, MIT press, 2017

[18] Canonne, C., and Garnier, N. B. "Cognition and segmentation in collective free improvisation : An exploratory study" *International Conference on Music Perception and Cognition*, 2012

[19] Carnovalini, F., and Rodà, A. "Computational Creativity and Music Generation Systems : An Introduction to the State of the Art", *Frontiers in Artificial Intelligence*, 14-3, 2020

[20] Collins, D. "A synthesis process model of creative thinking in music composition", *Psychology of Music*, 33-2, SAGE, 2005

[21] Collins, N. "LL : Listening and learning in an interactive improvisation system" *Technical Report*, University of Sussex, 2011

[22] Cook, N. *Beyond the Score : Music as Performance*, Oxford University Press, 2019

[23] Cont, A. "ANTESCOFO : Anticipatory Synchronization and Control of Interactive Parameters in Computer Music", *International Computer Music Conference (ICMC)*, 2008

[24] Davies, M. E. P., and Plumbley, M. D. "Context-dependent beat tracking of musical audio", *IEEE Transactions on Audio, Speech and Language Processing*, 15-3, 2007

[25] De Cheveigné, A., and Kawahara, H. "YIN, a fundamental frequency estimator for speech and music", *The Journal of the Acoustical Society of America*, 111-4, 2002

[26] Di Scipio, A. "Compositional Models in Xenakis’s Electroacoustic Music" *Perspective of New Music*, 36-2, 1998
[27] Ellis, D. P. W. "Beat tracking by dynamic programming", *Journal of New Music Research*, 36-1, Taylor & Francis, 2007

[28] Exarchos, D. "Iannis Xenakis and Sieve Theory - An Analysis of the Late Music (1984-1993)", *PhD Thesis*, Goldsmiths College, University of London, 2007

[29] Fiorini, M. "Somax2 User's Guide" *IRCAM Technical Report*, 2023

[30] Galante, F., and Sani, N. *Musica Espansa* Ricordi, 2000

[31] Ghisi, D., and Agon, C. "dada : Non-Standard User Interfaces for Computer-Aided Composition in Max", *Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR*, 2018

[32] Goto, M. "An audio-based real-time beat tracking system for music with or without drum-sounds", *International Journal of Phyto remediation*, 21-1, 2001

[33] Griffiths, P. *La musica del Novecento* Einaudi, 2014

[34] Harley, J. *Iannis Xenakis Komboï, for percussion & harpsichord*, Rovi Corporation, 2014

[35] Hernandez-Olivan, C., and Beltran, J. R. *Music Composition with Deep Learning : A Review*, 2021

[36] Herremans, D., Chuan, C., and Chew, E. "A Functional Taxonomy of Music Generation Systems", *ACM Comput. Surv.*, 50-5, Association for Computing Machinery, 2017

[37] Huang, Cheng-Zhi A., Vaswani, A., Uszkoreit, J., Shazeer, N., Hawthorne, C., Dai, A. M., Hoffman, M. D., and Eck, D. "Music Transformer : Generating Music with Long-Term Structure" *arXiv preprint arXiv:1809.04281*, 2018

[38] Karplus, K., and Strong, A. "Digital Synthesis of Plucked String and Drum Timbres", *Computer Music Journal*, 7-2, MIT Press, 1983

[39] Karplus, K., Strong, A., and Smith, J. O. "Extensions of the Karplus-Strong Plucked String Algorithm", *Computer Music Journal*, 7-2, MIT Press, 1983

[40] Large, E., and Kolen, J. F. "Resonance and the perception of musical meter", *Connection Science*, 6, 1994

[41] Lewis, G. E. "Too many notes : Computers, Complexity and Culture in Voyager" *Leonardo Music Journal*, 10, 2000

[42] Malt, M., and Sluchin, B. "Game Theory and formal structure in Xenakis's Duel (1959)" *Meta – Xenakis Global Symposium*, 2022

[43] Miranda, E. *Composing Music with Computers*. Routledge, 2001

[44] Moreira, J., Roy, P., and Patchet, F. "Virtualband : Interacting with stylistically consistent agents" *Proceedings of the 14th international society for music information retrieval conference*, 2013

[45] Mosqueira-Rey, E., Hernández-Pereira, E., Alonso-Ríos, D. et al. "Human-in-the-loop machine learning : a state of the art" *Artificial Intelligence Review*, 56, 2023

[46] Nika, J., Chemillier, M., and Assayag, G. "ImproteK : introducing scenarios into human-computer music improvisation" *ACM Computers in Entertainment*, 2017

[47] Nika, J., Déguernel, K., Chemla-Romeu-Santos, A., Vincent, E., and Assayag, G. "DYCI2 agents : merging the "free", "reactive", and "scenario-based" music generation paradigms" *International Computer Music Conference*, 2017

[48] Pachet, F. "The continuator : Musical interaction with style" *Journal of New Music Research*, 32-3, 2003

[49] Puckette, M. "A divide between ‘compositional’ and ‘performative’ aspects of pd", *First International Pd Convention*, 2004

[50] Puckette, M. S., Apel, T., and Zicarelli, D. D. "Real-time audio analysis tools for Pd and MSP", *Proceedings, ICMC 98*, Citeseer, 2006

[51] Roberts, A., Engel, J., Raffel, C., Hawthorne, C., Eck, D. "A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music" *arXiv* 1803.05428, 2019

[52] Ross, A. *The Rest Is Noise : Listening to the Twentieth Century*. Farrar, Straus and Giroux, Picador, 2007

[53] Rowe, R. "Machine listening and composing with cypher" *Computer Music Journal*, 16-1, 43, MIT press, 1992

[54] Rowe, R. *Machine Musicianship*, MIT Press, 2004

[55] Schnell, N., Roebel, A., Schwarz, D., Peeters, G., and Borghesi, R. "Mubu and friends - assembling tools for content based real-time interactive audio processing in max/msp" *Proceedings of the International Computer Music Conference (ICMC)*, 2009

[56] Schwarz, D., Beller, G., Verbrugghe, B., and Britton, S. "Real-Time Corpus-Based Concatenative Synthesis with CataRT", *9th International Conference on Digital Audio Effects (DAFx)*, 2006

[57] Schwarz, D., and Cannone, C. "Notation, Transmission and Comprovisation : A Case Study of The Onceim Improvisation Orchestra", *Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR*, 2022

[58] Smith, J. O. "Physical Modeling Using Digital Waveguides", *Computer Music Journal*, 24-4, MIT Press, 1992

[59] Stark, A. M., Davies, M. E. P., and Plumbley, M. D. "Real-Time Beat-Synchronous Analysis Of Musical Audio" *Proc. of the 12th Int. Conference on Digital Audio Effects (DAFx-09)*, 2009
[27] Ellis, D. P. W. "Beat tracking by dynamic programming", *Journal of New Music Research*, 36-1, Taylor & Francis, 2007

[28] Exarchos, D. "Iannis Xenakis and Sieve Theory - An Analysis of the Late Music (1984-1993)", *PhD Thesis*, Goldsmiths College, University of London, 2007

[29] Fiorini, M. "Somax2 User's Guide" *IRCAM Technical Report*, 2023

[30] Galante, F., and Sani, N. *Musica Espansa* Ricordi, 2000

[31] Ghisi, D., and Agon, C. "dada : Non-Standard User Interfaces for Computer-Aided Composition in Max", *Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR*, 2018

[32] Goto, M. "An audio-based real-time beat tracking system for music with or without drum-sounds", *International Journal of Phyto remediation*, 21-1, 2001

[33] Griffiths, P. *La musica del Novecento* Einaudi, 2014

[34] Harley, J. *Iannis Xenakis Komboï, for percussion & harpsichord*, Rovi Corporation, 2014

[35] Hernandez-Olivan, C., and Beltran, J. R. *Music Composition with Deep Learning : A Review*, 2021

[36] Herremans, D., Chuan, C., and Chew, E. "A Functional Taxonomy of Music Generation Systems", *ACM Comput. Surv.*, 50-5, Association for Computing Machinery, 2017

[37] Huang, Cheng-Zhi A., Vaswani, A., Uszkoreit, J., Shazeer, N., Hawthorne, C., Dai, A. M., Hoffman, M. D., and Eck, D. "Music Transformer : Generating Music with Long-Term Structure" *arXiv preprint arXiv:1809.04281*, 2018

[38] Karplus, K., and Strong, A. "Digital Synthesis of Plucked String and Drum Timbres", *Computer Music Journal*, 7-2, MIT Press, 1983

[39] Karplus, K., Strong, A., and Smith, J. O. "Extensions of the Karplus-Strong Plucked String Algorithm", *Computer Music Journal*, 7-2, MIT Press, 1983

[40] Large, E., and Kolen, J. F. "Resonance and the perception of musical meter", *Connection Science*, 6, 1994

[41] Lewis, G. E. "Too many notes : Computers, Complexity and Culture in Voyager" *Leonardo Music Journal*, 10, 2000

[42] Malt, M., and Sluchin, B. "Game Theory and formal structure in Xenakis's Duel (1959)" *Meta – Xenakis Global Symposium*, 2022

[43] Miranda, E. *Composing Music with Computers*. Routledge, 2001

[44] Moreira, J., Roy, P., and Patchet, F. "Virtualband : Interacting with stylistically consistent agents" *Proceedings of the 14th international society for music information retrieval conference*, 2013

[45] Mosqueira-Rey, E., Hernández-Pereira, E., Alonso-Ríos, D. et al. "Human-in-the-loop machine learning : a state of the art" *Artificial Intelligence Review*, 56, 2023

[46] Nika, J., Chemillier, M., and Assayag, G. "ImproteK : introducing scenarios into human-computer music improvisation" *ACM Computers in Entertainment*, 2017

[47] Nika, J., Déguernel, K., Chemla-Romeu-Santos, A., Vincent, E., and Assayag, G. "DYCI2 agents : merging the "free", "reactive", and "scenario-based" music generation paradigms" *International Computer Music Conference*, 2017

[48] Pachet, F. "The continuator : Musical interaction with style" *Journal of New Music Research*, 32-3, 2003

[49] Puckette, M. "A divide between ‘compositional’ and ‘performative’ aspects of pd", *First International Pd Convention*, 2004

[50] Puckette, M. S., Apel, T., and Zicarelli, D. D. "Real-time audio analysis tools for Pd and MSP", *Proceedings, ICMC 98*, Citeseer, 2006

[51] Roberts, A., Engel, J., Raffel, C., Hawthorne, C., Eck, D. "A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music" *arXiv* 1803.05428, 2019

[52] Ross, A. *The Rest Is Noise : Listening to the Twentieth Century*. Farrar, Straus and Giroux, Picador, 2007

[53] Rowe, R. "Machine listening and composing with cypher" *Computer Music Journal*, 16-1, 43, MIT press, 1992

[54] Rowe, R. *Machine Musicianship*, MIT Press, 2004

[55] Schnell, N., Roebel, A., Schwarz, D., Peeters, G., and Borghesi, R. "Mubu and friends - assembling tools for content based real-time interactive audio processing in max/msp" *Proceedings of the International Computer Music Conference (ICMC)*, 2009

[56] Schwarz, D., Beller, G., Verbrugghe, B., and Britton, S. "Real-Time Corpus-Based Concatenative Synthesis with CataRT", *9th International Conference on Digital Audio Effects (DAFx)*, 2006

[57] Schwarz, D., and Cannone, C. "Notation, Transmission and Comprovisation : A Case Study of The Onceim Improvisation Orchestra", *Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR*, 2022

[58] Smith, J. O. "Physical Modeling Using Digital Waveguides", *Computer Music Journal*, 24-4, MIT Press, 1992

[59] Stark, A. M., Davies, M. E. P., and Plumbley, M. D. "Real-Time Beat-Synchronous Analysis Of Musical Audio" *Proc. of the 12th Int. Conference on Digital Audio Effects (DAFx-09)*, 2009
[60] Stark, A. M. "Musicians and Machines : Bridging the Semantic Gap In Live Performance", *PhD Thesis*, Centre for Digital Music, Department of Electronic Engineering and Computer Science, Queen Mary, University of London, 2011

[61] Stockhausen, K. *On Music*. M. Boyars, 2000

[62] Stockhausen, K. *Comment passe le temps : Essais sur la musique 1952-1961*. Éditions Contrechamps, 2019

[63] Tatar, K., and Pasquier, P. "Musical agents : A typology and state of the art towards Musical Metacreation" *Journal of New Music Research*, 48-1, Routledge, 2019

[64] Toiviainen, P. "An interactive midi accompanist", *Computer Music Journal*, 22, MIT Press, 1998

[65] Tremblay, P. A., Green, O., Rowa, G., Bradbury, J., Moore, T., Hart, J., and Harker, A. "Fluid Corpus Manipulation Toolbox", 2022

[66] Wang, C.-I., Hsu, J., and Dubnov, S. "Machine Improvisation with Variable Markov Oracle : Toward Guided and Structured Improvisation" *Computers in Entertainment*, 14-3, (2016)

[67] Xenakis, I. "La voie de la recherche et de la question", *Preuves*, 177, 1965

[68] Xenakis, I. "Vers un métamusique", *La Nef*, 29, 1967

[69] Xenakis, I. "Sieves", *Perspectives of New Music*, 28-1, 1990

[70] Xenakis, I. *Formalized Music : Thought and Mathematics in Composition*, Pendragon Press, 1992
[60] Stark, A. M. "Musicians and Machines : Bridging the Semantic Gap In Live Performance", *PhD Thesis*, Centre for Digital Music, Department of Electronic Engineering and Computer Science, Queen Mary, University of London, 2011

[61] Stockhausen, K. *On Music*. M. Boyars, 2000

[62] Stockhausen, K. *Comment passe le temps : Essais sur la musique 1952-1961*. Éditions Contrechamps, 2019

[63] Tatar, K., and Pasquier, P. "Musical agents : A typology and state of the art towards Musical Metacreation" *Journal of New Music Research*, 48-1, Routledge, 2019

[64] Toiviainen, P. "An interactive midi accompanist", *Computer Music Journal*, 22, MIT Press, 1998

[65] Tremblay, P. A., Green, O., Rowa, G., Bradbury, J., Moore, T., Hart, J., and Harker, A. "Fluid Corpus Manipulation Toolbox", 2022

[66] Wang, C.-I., Hsu, J., and Dubnov, S. "Machine Improvisation with Variable Markov Oracle : Toward Guided and Structured Improvisation" *Computers in Entertainment*, 14-3, (2016)

[67] Xenakis, I. "La voie de la recherche et de la question", *Preuves*, 177, 1965

[68] Xenakis, I. "Vers un métamusique", *La Nef*, 29, 1967

[69] Xenakis, I. "Sieves", *Perspectives of New Music*, 28-1, 1990

[70] Xenakis, I. *Formalized Music : Thought and Mathematics in Composition*, Pendragon Press, 1992