Real world neural networks for interactive music composition in real time
A new model designed for musicians to use as a tool for practicing and improvisation is developed based on a corpus of Jazz lead sheets. It is lightweight enough to work within the CPU and memory constraints of consumer equipment and operate in real time with input from a standard midi device. The m...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/48526/ |
| _version_ | 1848797784426151936 |
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| author | Bickerstaffe, Colin |
| author_facet | Bickerstaffe, Colin |
| author_sort | Bickerstaffe, Colin |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | A new model designed for musicians to use as a tool for practicing and improvisation is developed based on a corpus of Jazz lead sheets. It is lightweight enough to work within the CPU and memory constraints of consumer equipment and operate in real time with input from a standard midi device. The model is also compatible for use on a Raspberry Pi for ultimate portability (at the cost of a significantly longer training time). |
| first_indexed | 2025-11-14T20:09:23Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-48526 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:09:23Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-485262018-01-12T00:04:32Z https://eprints.nottingham.ac.uk/48526/ Real world neural networks for interactive music composition in real time Bickerstaffe, Colin A new model designed for musicians to use as a tool for practicing and improvisation is developed based on a corpus of Jazz lead sheets. It is lightweight enough to work within the CPU and memory constraints of consumer equipment and operate in real time with input from a standard midi device. The model is also compatible for use on a Raspberry Pi for ultimate portability (at the cost of a significantly longer training time). 2017-12-14 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/48526/1/Colin%20Bickerstaffe_MScDissertation.pdf Bickerstaffe, Colin (2017) Real world neural networks for interactive music composition in real time. [Dissertation (University of Nottingham only)] Artificial Neural Networks Recurrent Neural Networks Long Short Term Memory Musical Instrument Digital Interface. |
| spellingShingle | Artificial Neural Networks Recurrent Neural Networks Long Short Term Memory Musical Instrument Digital Interface. Bickerstaffe, Colin Real world neural networks for interactive music composition in real time |
| title | Real world neural networks for interactive music composition in real time |
| title_full | Real world neural networks for interactive music composition in real time |
| title_fullStr | Real world neural networks for interactive music composition in real time |
| title_full_unstemmed | Real world neural networks for interactive music composition in real time |
| title_short | Real world neural networks for interactive music composition in real time |
| title_sort | real world neural networks for interactive music composition in real time |
| topic | Artificial Neural Networks Recurrent Neural Networks Long Short Term Memory Musical Instrument Digital Interface. |
| url | https://eprints.nottingham.ac.uk/48526/ |