Description of impact
Dr Ryan Stables and colleagues’ research into how computers can be trained to understand the human vocabulary of sound has led to a level of intelligent automation that is unprecedented in commercial music production. Since 2014, the BCU team has introduced a suite of adaptive software plugins (SAFE) which have been used by well-known music studios to create commercial recordings, as well as downloaded by 15,000 music-creators in 20 countries. The software makes the technical and creative process easier for professionals to perform complex and tedious mixing tasks, and for amateurs and early careerists to bypass many years’ costly learning of how to process sound. The team have developed a next-generation Digital Audio Workstation (DAW), facilitating real-time collaborative music production and embedding machine learning capabilities into the production workflow; this is being commercialised by a university spin-out, Semantic Audio Labs (SAL), which raised an initial GBP500,000 of seed-funding, employs 6 full-time staff, and has a number of pending patents.Impact date | 2016 → 2020 |
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Category of impact | Other impacts |
Related content
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Outputs
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SAFE: A System for the Extraction and Retrieval of Semantic Audio Descriptors: The 15th International Society for Music Information Retrieval Conference
Research output: Contribution to conference › Paper
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JS-Xtract: A Realtime Audio Feature Extraction Library for the Web
Research output: Chapter in Book/Report/Conference proceeding › Chapter
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JSAP: Intelligent Audio Plugin format for the Web Audio API: The 2nd AES Workshop on Intelligent Music Production
Research output: Contribution to conference › Paper
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Semantic description of timbral transformations in music production
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Automatic drum transcription using bi-directional recurrent neural networks
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Semantically controlled adaptive equalisation in reduced dimensionality parameter space
Research output: Contribution to journal › Article › peer-review