Al-terity: Non-Rigid Musical Instrument with Artificial Intelligence Applied to Real-Time Audio Synthesis

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorTahiroğlu, Korayen_US
dc.contributor.authorKastemaa, Mirandaen_US
dc.contributor.authorKoli, Oskaren_US
dc.contributor.departmentDepartment of Mediaen_US
dc.date.accessioned2020-12-31T08:36:16Z
dc.date.available2020-12-31T08:36:16Z
dc.date.issued2020-07-25en_US
dc.description.abstractA deformable musical instrument can take numerous dis- tinct shapes with its non-rigid features. Building audio syn- thesis module for such an interface behaviour can be chal- lenging. In this paper, we present the Al-terity, a non-rigid musical instrument that comprises a deep learning model with generative adversarial network architecture and use it for generating audio samples for real-time audio synthesis. The particular deep learning model we use for this instru- ment was trained with existing data set as input for pur- poses of further experimentation. The main benefits of the model used are the ability to produce the realistic range of timbre of the trained data set and the ability to generate new audio samples in real-time, in the moment of playing, with the characteristics of sounds that the performer ever heard before. We argue that these advanced intelligence features on the audio synthesis level could allow us to ex- plore performing music with particular response features that define the instrument’s digital idiomaticity and allow us reinvent the instrument in the act of music performance.en
dc.description.versionPeer revieweden
dc.format.extent6
dc.format.extent337-342
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationTahiroğlu , K , Kastemaa , M & Koli , O 2020 , Al-terity: Non-Rigid Musical Instrument with Artificial Intelligence Applied to Real-Time Audio Synthesis . in Proceedings of the International Conference on New Interfaces for Musical Expression . Proceedings of the International Conference on New Interfaces for Musical Expression , International Conference on New Interfaces for Musical Expression (NIME) , Birmingham , pp. 337-342 , INTERNATIONAL CONFERENCE ON NEW INTERFACES FOR MUSICAL EXPRESSION , 01/01/1900 . < https://www.nime.org/proceedings/2020/nime2020_paper65.pdf >en
dc.identifier.issn2220-4806
dc.identifier.otherPURE UUID: 02152a45-1ac3-400c-b70e-7fd2fcd1a154en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/02152a45-1ac3-400c-b70e-7fd2fcd1a154en_US
dc.identifier.otherPURE LINK: https://www.nime.org/proceedings/2020/nime2020_paper65.pdfen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/54131063/nime2020_paper65.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/101388
dc.identifier.urnURN:NBN:fi:aalto-2020123160209
dc.language.isoenen
dc.relation.ispartofINTERNATIONAL CONFERENCE ON NEW INTERFACES FOR MUSICAL EXPRESSIONen
dc.relation.ispartofseriesProceedings of the International Conference on New Interfaces for Musical Expressionen
dc.rightsopenAccessen
dc.subject.keywordNIMEen_US
dc.subject.keywordArtificial Intelligence (AI)en_US
dc.subject.keywordGANen_US
dc.subject.keyworddeep learningen_US
dc.subject.keywordSOPIen_US
dc.titleAl-terity: Non-Rigid Musical Instrument with Artificial Intelligence Applied to Real-Time Audio Synthesisen
dc.typeConference article in proceedingsfi
dc.type.versionpublishedVersion
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