Musical agents: A typology and state of the art towards Musical Metacreation

Tatar, Kıvanç; Pasquier, Philippe

doi:10.1080/09298215.2018.1511736

Cited by 47 publications

(29 citation statements)

References 68 publications

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“…Music can also regulate human emotions, enabling people to relax, soothe their bodies and minds, reduce anxiety, improve sleep, and even be used for complementary medicine. Music is widely recognized as a universal language, and the innovation of musical artworks and the diversity of their performance styles also help to inherit and promote the profound traditional culture [1]. e vast amount of digital music has given rise to music information retrieval (MIR) technology, which combines computers and music and has numerous applications.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Using a Solution Construction Algorithm for Cyclic Shift Network Coding under Multicast Network to the Transformation of Musical Performance Styles

Wang

Geng

2021

Complexity

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This paper presents a theoretical framework of the circular shift network coding system through the study of nonmultiple clustered interval music performance style conversion and the analysis of music conversion by using circular shift topology, and a series of basic research results of circular shift network coding is obtained under this framework. It reveals the essential connection between scalar network coding based on finite domain and cyclic shift network coding, designs a solution construction algorithm for cyclic shift network coding under multicast network, and portrays the multicast capacity of cyclic shift network coding. It overcomes the problem that the piano roll-curtain representation cannot distinguish between a single long note and multiple consecutive notes of the same pitch, describes musical information more comprehensively, extracts musical implicit style from the note matrix based on autoencoder, and better eliminates the potential influence of musical content on musical performance style. A two-way recurrent neural network based on the gated recurrent unit is used to extract a sequence of note feature vectors of different styles, and a one-dimensional convolutional neural network is used to predict the intensity of the extracted note feature vector sequence for a specific style, which better learns the intensity variation of different styles of MIDI music.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Using a Solution Construction Algorithm for Cyclic Shift Network Coding under Multicast Network to the Transformation of Musical Performance Styles

Wang

Geng

2021

Complexity

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“…Any software with such capabilities can be seen as an agent (including many of the systems described in the previous sections), but the definition becomes especially interesting when multiple agents cooperate within a single software, that can be referred to as a Multi Agent System. This is not a specific algorithm for music generation, but rather a meta-technique that has gained popularity among researchers, as testified by Tatar and Pasquier ( 2019 ).…”

Section: Music Generation Systemsmentioning

confidence: 99%

Computational Creativity and Music Generation Systems: An Introduction to the State of the Art

Carnovalini

Rodà

2020

Front. Artif. Intell.

100

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Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors from computers. One of its most prolific subfields is that of Music Generation (also called Algorithmic Composition or Musical Metacreation), that uses computational means to compose music. Due to the multidisciplinary nature of this research field, it is sometimes hard to define precise goals and to keep track of what problems can be considered solved by state-of-the-art systems and what instead needs further developments. With this survey, we try to give a complete introduction to those who wish to explore Computational Creativity and Music Generation. To do so, we first give a picture of the research on the definition and the evaluation of creativity, both human and computational, needed to understand how computational means can be used to obtain creative behaviors and its importance within Artificial Intelligence studies. We then review the state of the art of Music Generation Systems, by citing examples for all the main approaches to music generation, and by listing the open challenges that were identified by previous reviews on the subject. For each of these challenges, we cite works that have proposed solutions, describing what still needs to be done and some possible directions for further research.

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“…Tatar's [6] autonomy spectrum, we see the instrument as falling somewhere in the middle ground. The behaviour is complex enough as to not be purely reactive.…”

Section: Autonomous Nature and Functionalitymentioning

confidence: 94%

“…The agency has been discussed with a focus on the ways agency arises through the autonomous acts of the musical instrument that forms and supports the musical identity [4], building a basis for collaborative music actions between musician and the musical instrument [5]. Tatar et al [6] define autonomy in musical generative systems as being a spectrum, ranging from purely reactive ("rule based") to completely autonomous systems ("generic"). In the first, the system has a set of static rules defined by the system's creator which map input to output.…”

Section: Related Workmentioning

confidence: 99%

AI-terity 2.0: An Autonomous NIME Featuring GANSpaceSynth Deep Learning Model

Tahiroğlu¹,

Kastemaa²,

Koli³

Nime 2021

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In this paper we present the recent developments in the AI-terity instrument. AI-terity is a deformable, non-rigid musical instrument that comprises a particular artificial intelligence (AI) method for generating audio samples for real-time audio synthesis. As an improvement, we developed the control interface structure with additional sensor hardware. In addition, we implemented a new hybrid deep learning architecture, GANSpaceSynth, in which we applied the GANSpace method on the GANSynth model.Following the deep learning model improvement, we developed new autonomous features for the instrument that aim at keeping the musician in an active and uncertain state of exploration. Through these new features, the instrument enables more accurate control on GAN latent space. Further, we intend to investigate the current developments through a musical composition that idiomatically reflects the new autonomous features of the AI-terity instrument. We argue that the present technology of AI is suitable for enabling alternative autonomous features in audio domain for the creative practices of musicians.

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Musical agents: A typology and state of the art towards Musical Metacreation

Cited by 47 publications

References 68 publications

[Retracted] Using a Solution Construction Algorithm for Cyclic Shift Network Coding under Multicast Network to the Transformation of Musical Performance Styles

[Retracted] Using a Solution Construction Algorithm for Cyclic Shift Network Coding under Multicast Network to the Transformation of Musical Performance Styles

Computational Creativity and Music Generation Systems: An Introduction to the State of the Art

AI-terity 2.0: An Autonomous NIME Featuring GANSpaceSynth Deep Learning Model

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