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1. Programming gate-based hardware quantum computers for music

Author

Kirke Alexis

Subjects
quantum computer music, algorithms, D-Wave, Musical instruction and study, MT1-960
Abstract

There have been significant attempts previously to use the equations of quantum mechanics for generating sound, and to sonify simulated quantum processes. For new forms of computation to be utilized in computer music, eventually hardware must be utilized. This has rarely happened with quantum computer music. One reason for this is that it is currently not easy to get access to such hardware. A second is that the hardware available requires some understanding of quantum computing theory. This paper moves forward the process by utilizing two hardware quantum computation systems: IBMQASM v1.1 and a D-Wave 2X. It also introduces the ideas behind the gate-based IBM system, in a way hopefully more accessible to computerliterate readers. This is a presentation of the first hybrid quantum computer algorithm, involving two hardware machines. Although neither of these algorithms explicitly utilize the promised quantum speed-ups, they are a vital first step in introducing QC to the musical field. The article also introduces some key quantum computer algorithms and discusses their possible future contribution to computer music.

Published
2018
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3. Artificially Synthesising Data for Audio Classification and Segmentation to Improve Speech and Music Detection in Radio Broadcast

Author

Venkatesh, Satvik, Moffat, David, Kirke, Alexis, Shakeri, Gözel, Brewster, Stephen, Fachner, Jörg, Odell-Miller, Helen, Street, Alex, Farina, Nicolas, Banerjee, Sube, and Miranda, Eduardo Reck

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Machine Learning, Computer Science - Sound, I.5.4, I.2.m
Abstract

Segmenting audio into homogeneous sections such as music and speech helps us understand the content of audio. It is useful as a pre-processing step to index, store, and modify audio recordings, radio broadcasts and TV programmes. Deep learning models for segmentation are generally trained on copyrighted material, which cannot be shared. Annotating these datasets is time-consuming and expensive and therefore, it significantly slows down research progress. In this study, we present a novel procedure that artificially synthesises data that resembles radio signals. We replicate the workflow of a radio DJ in mixing audio and investigate parameters like fade curves and audio ducking. We trained a Convolutional Recurrent Neural Network (CRNN) on this synthesised data and outperformed state-of-the-art algorithms for music-speech detection. This paper demonstrates the data synthesis procedure as a highly effective technique to generate large datasets to train deep neural networks for audio segmentation., Comment: 5 pages, 3 figures, Accepted to ICASSP 2021

Published
2021

4. RadioMe: Adaptive Radio to Support People with Mild Dementia in Their Own Home

Author

Di Campli San Vito, Patrizia, primary, Yang, Xiaochen, additional, Brewster, Stephen, additional, Street, Alex, additional, Fachner, Jörg, additional, Fernie, Paul, additional, Muller-Rodriguez, Leonardo, additional, Hung Hsu, Ming, additional, Odell-Miller, Helen, additional, Shaji, Hari, additional, Itaborai, Paulo, additional, Evison, Beth, additional, Farina, Nicolas, additional, Banerjee, Sube, additional, Kirke, Alexis, additional, and Miranda, Eduardo, additional

Published
2023
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5. Application of Optimization and Simulation to Musical Composition that Emerges Dynamically during Ensemble Singing Performance

Author

Kirke, Alexis, Davies, Greg B., and Eaton, Joel

Subjects
Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing, 00A65, J.5
Abstract

This paper presents and tests a new approach to composing for ensemble singing performance: reality opera. In the performance of such a composition, emotions of the singers are real and emerge as a consequence of their interactions and reaction and to a dynamic narrative. This paper gives background and motivation for the form, based on three key concepts, incorporating the use of technology. Then proposed techniques for creating reality opera are instantiated in an example, which is performed and a behavioral analysis done of performer reactions, leading to support for the feasibility of the reality opera concept., Comment: 31 pages, 11 Figures

Published
2020

6. Applying Quantum Hardware to non-Scientific Problems: Grover's Algorithm and Rule-based Algorithmic Music Composition

Author

Kirke, Alexis

Subjects
Computer Science - Artificial Intelligence
Abstract

Of all novel computing methods, quantum computation (QC) is currently the most likely to move from the realm of the unconventional into the conventional. As a result some initial work has been done on applications of QC outside of science: for example music. The small amount of arts research done in hardware or with actual physical systems has not utilized any of the advantages of quantum computation (QC): the main advantage being the potential speed increase of quantum algorithms. This paper introduces a way of utilizing Grover's algorithm - which has been shown to provide a quadratic speed-up over its classical equivalent - in algorithmic rule-based music composition. The system introduced - qgMuse - is simple but scalable. Example melodies are composed using qgMuse using the ibmqx4 quantum hardware. The paper concludes with discussion on how such an approach can grow with the improvement of quantum computer hardware and software., Comment: Accepted by 'International Journal of Unconventional Computing' 18 July 2019

Published
2019

14. Application of intermediate multi-agent systems to integrated algorithmic composition and expressive performance of music

Author

Kirke, Alexis and Miranda, Eduardo

Subjects
780, Computer Music, Algorithmic Composition, Expressive Performance, Multi-Agent Systems
Abstract

We investigate the properties of a new Multi-Agent Systems (MAS) for computer-aided composition called IPCS (pronounced “ipp-siss”) the Intermediate Performance Composition System which generates expressive performance as part of its compositional process, and produces emergent melodic structures by a novel multi-agent process. IPCS consists of a small-medium size (2 to 16) collection of agents in which each agent can perform monophonic tunes and learn monophonic tunes from other agents. Each agent has an affective state (an “artificial emotional state”) which affects how it performs the music to other agents; e.g. a “happy” agent will perform “happier” music. The agent performance not only involves compositional changes to the music, but also adds smaller changes based on expressive music performance algorithms for humanization. Every agent is initialized with a tune containing the same single note, and over the interaction period longer tunes are built through agent interaction. Agents will only learn tunes performed to them by other agents if the affective content of the tune is similar to their current affective state; learned tunes are concatenated to the end of their current tune. Each agent in the society learns its own growing tune during the interaction process. Agents develop “opinions” of other agents that perform to them, depending on how much the performing agent can help their tunes grow. These opinions affect who they interact with in the future. IPCS is not a mapping from multi-agent interaction onto musical features, but actually utilizes music for the agents to communicate emotions. In spite of the lack of explicit melodic intelligence in IPCS, the system is shown to generate non-trivial melody pitch sequences as a result of emotional communication between agents. The melodies also have a hierarchical structure based on the emergent social structure of the multi-agent system and the hierarchical structure is a result of the emerging agent social interaction structure. The interactive humanizations produce micro-timing and loudness deviations in the melody which are shown to express its hierarchical generative structure without the need for structural analysis software frequently used in computer music humanization.

Published
2011

17. Music and Dementia: Two Case-Studies

Author

Kirke, Alexis, Dixon, Belinda, Miranda, Eduardo R., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Kronland-Martinet, Richard, editor, Aramaki, Mitsuko, editor, and Ystad, Sølvi, editor

Published
2016
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20. Learning and co-operation in mobile multi-robot systems

Author

Kirke, Alexis John

Subjects
629.892, Robotics
Abstract

This thesis addresses the problem of setting the balance between exploration and exploitation in teams of learning robots who exchange information. Specifically it looks at groups of robots whose tasks include moving between salient points in the environment. To deal with unknown and dynamic environments,such robots need to be able to discover and learn the routes between these points themselves. A natural extension of this scenario is to allow the robots to exchange learned routes so that only one robot needs to learn a route for the whole team to use that route. One contribution of this thesis is to identify a dilemma created by this extension: that once one robot has learned a route between two points, all other robots will follow that route without looking for shorter versions. This trade-off will be labeled the Distributed Exploration vs. Exploitation Dilemma, since increasing distributed exploitation (allowing robots to exchange more routes) means decreasing distributed exploration (reducing robots ability to learn new versions of routes), and vice-versa. At different times, teams may be required with different balances of exploitation and exploration. The main contribution of this thesis is to present a system for setting the balance between exploration and exploitation in a group of robots. This system is demonstrated through experiments involving simulated robot teams. The experiments show that increasing and decreasing the value of a parameter of the novel system will lead to a significant increase and decrease respectively in average exploitation (and an equivalent decrease and increase in average exploration) over a series of team missions. A further set of experiments show that this holds true for a range of team sizes and numbers of goals.

Published
1997

27. Learning to Make Feelings: Expressive Performance as a Part of a Machine Learning Tool for Sound-Based Emotion Control

Author

Kirke, Alexis, Miranda, Eduardo R., Nasuto, Slawomir J., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Aramaki, Mitsuko, editor, Barthet, Mathieu, editor, Kronland-Martinet, Richard, editor, and Ystad, Sølvi, editor

Published
2013
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33. Artificially Synthesising Data for Audio Classification and Segmentation to Improve Speech and Music Detection in Radio Broadcast

Author

Venkatesh, Satvik, primary, Moffat, David, additional, Kirke, Alexis, additional, Shakeri, Gozel, additional, Brewster, Stephen, additional, Fachner, Jorg, additional, Odell-Miller, Helen, additional, Street, Alex, additional, Farina, Nicolas, additional, Banerjee, Sube, additional, and Miranda, Eduardo Reck, additional

Published
2021
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34. A survey of computer systems for expressive music performance

Author

Kirke, Alexis and Miranda, Eduardo Reck

Subjects
Algorithm, Algorithms -- Surveys, Computers -- Surveys
Abstract

We present a survey of research into automated and semiautomated computer systems for expressive performance of music. We will examine the motivation for such systems and then examine the majority of the systems developed over the last 25 years. To highlight some of the possible future directions for new research, the review uses primary terms of reference based on four elements: testing status, expressive representation, polyphonic ability, and performance creativity. Categories and Subject Descriptors: J.5 [Arts and Humanities]: Performing arts (e.g. dance, music) General Terms: Algorithms, Experimentation, Human Factors Additional Key Words and Phrases: Music performance, generative performance, computer music, machine learning DOI = 10.1145/1592451.1592454

Published
2010

42. Програмирање квантних рачунара базираних на употреби логичких кола за потребе рада са музиком

Author

Kirke, Alexis and Medić, Ivana

Subjects
алгоритми, quantum computer music, квантна компјутерска музика, D-Wave, algorithms
Abstract

There have been significant attempts previously to use the equations of quantum mechanics for generating sound, and to sonify simulated quantum processes. For new forms of computation to be utilized in computer music, eventually hardware must be utilized. This has rarely happened with quantum computer music. One reason for this is that it is currently not easy to get access to such hardware. A second is that the hardware available requires some understanding of quantum computing theory. Tis paper moves forward the process by utilizing two hardware quantum computation systems: IBMQASM v1.1 and a D-Wave 2X. It also introduces the ideas behind the gate-based IBM system, in a way hopefully more accessible to computerliterate readers. Tis is a presentation of the frst hybrid quantum computer algorithm, involving two hardware machines. Although neither of these algorithms explicitly utilize the promised quantum speed-ups, they are a vitalfrst step in introducing QC to the musical feld. Te article also introduces some key quantum computer algorithms and discusses their possible future contribution to computer music. Досад су забележени значајни покушаји да се једначине квантне механике користе за генерисање звука и да се озвуче симулирани квантни процеси. Али, за нове облике рачунања који би се користили у компјутерској музици, мора се употребити одговарајући хардвер. Ово се досад ретко дешавало са квантном компјутерском музиком, најпре зато што такав хардвер није широко доступан. Други разлог јесте околност да овакав хардвер захтева извесно познавање теорије квантног рачунарства. Овим чланком померамо овај процес унапред помоћу два хардверска квантна рачунарска система: IBMQASM v1.1 и D-Wave 2X. Такође уводимо неке идеје из IBM-овог система заснованог на логичким колима, на начин доступан рачунарски писменим читаоцима. Ово је презентација првог хибридног квантног компјутерског алгоритма, који укључује две хардверске машине. Иако ниједан од ових алгоритама експлицитно не користи обећана квантна убрзања, они представљају виталан први корак у увођењу квантног рачунарства у поље музике. Чланак започињемо кратким прегледом квантног рачунарства и указујемо како се оно може применити на подручју уметности. Следи истраживање претходних пројеката у којима су коришћени стварни или симулирани квантни процеси у музичким делима или извођењима. У следећем одељку се говори о најпознатијој врсти квантних рачунара, заснованих на логичким колима, и описује се хардвер једног од мањих квантних рачунара компаније IBM. Следи кратак увод у теорију квантног рачунарства; ове идеје су потом пројектоване на језик који користе IBM рачунари: IBMQASM. Следећи одељак доноси кратак преглед друге врсте квантног рачунара који се користи: D-Wave. Детаљнији описи мог алгоритма доступни су у другим чланцима на које се позивам. На крају је описан qGen: IBM генерише мелодију, а D-Wave је хармонизује. Фокус је на мелодијском алгоритму, пошто је алгоритам D-Wave описан у поглављу из књиге на коју реферирам. Развијен је “најједноставнији могући“ мелодијски алгоритам, уз који је приложен и одговарајући пример.

Published
2018

43. A perceptual and affective evaluation of an affectively driven engine for video game soundtracking

Author

Williams, Duncan, Mears, Jamie, Kirke, Alexis, Miranda, Eduardo, Daly, Ian, Malik, Asad, Weaver, James, Hwang, Faustina, and Nasuto, Slawomir

Subjects
ComputingMilieux_PERSONALCOMPUTING
Abstract

We report on a player evaluation of a pilot system for dynamic video game soundtrack generation. The system being evaluated generates music using an AI-based algorithmic composition technique to create score in real-time, in response to a continuously varying emotional trajectory dictated by gameplay cues. After a section of gameplay, players rated the system on a Likert scale according to emotional congruence with the narrative, and also according to their perceived immersion with the gameplay. The generated system showed a statistically meaningful and consistent improvement in ratings for emotional congruence, yet with a decrease in perceived immersion, which might be attributed to the marked difference in instrumentation between the generated music, voiced by a solo piano timbre, and the original, fully orchestrated soundtrack. Finally, players rated selected stimuli from the generated soundtrack dataset on a two-dimensional model reflecting perceived valence and arousal. These ratings were compared to the intended emotional descriptor in the meta-data accompanying specific gameplay events. Participant responses suggested strong agreement with the affective correlates, but also a significant amount of inter-participant variability. Individual calibration of the musical feature set, or further adjustment of the musical feature set are therefore suggested as useful avenues for further work.

Published
2017

48. An Affective Brain-Computer Music Interface

Author

Hwang, Faustina, Miranda, Eduardo, Daly, Ian, Williams, Duncan, Kirke, Alexis, Weaver, James, Malik, Asad, Nasuto, Slawomir, and Wairagkar, Maitreyee

Abstract

Proceedings Of The 6Th International Bci Meeting: Bci Past, Present, And Future

Published
2016
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