ExSampling: a system for the real-time ensemble performance of field-recorded environmental sounds
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2020
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| Subjects: | |
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| _version_ | 1866912955871789056 |
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| author | Kobayashi, Atsuya Anzai, Reo Tokui, Nao |
| author_facet | Kobayashi, Atsuya Anzai, Reo Tokui, Nao |
| contents | We propose ExSampling: an integrated system of recording application and Deep Learning environment for a real-time music performance of environmental sounds sampled by field recording. Automated sound mapping to Ableton Live tracks by Deep Learning enables field recording to be applied to real-time performance, and create interactions among sound recorders, composers and performers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2006_09645 |
| institution | arXiv |
| publishDate | 2020 |
| record_format | arxiv |
| spellingShingle | ExSampling: a system for the real-time ensemble performance of field-recorded environmental sounds Kobayashi, Atsuya Anzai, Reo Tokui, Nao Human-Computer Interaction Sound Audio and Speech Processing We propose ExSampling: an integrated system of recording application and Deep Learning environment for a real-time music performance of environmental sounds sampled by field recording. Automated sound mapping to Ableton Live tracks by Deep Learning enables field recording to be applied to real-time performance, and create interactions among sound recorders, composers and performers. |
| title | ExSampling: a system for the real-time ensemble performance of field-recorded environmental sounds |
| topic | Human-Computer Interaction Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2006.09645 |