cool hit counter Google develops NSynth super-instrument, based on neural synthesizer algorithm_Intefrankly

Google develops NSynth super-instrument, based on neural synthesizer algorithm

Tech giant Google has been working on a fusion of artificial intelligence and music projects for some time now, and the project has finally created a meticulously useful tool for musicians in the form of NSynth Super. NSynth Super is a synthesizer board that uses machine learning and Magenta's extensive sound database to allow musicians to create new soundboards and sounds for synthesizers, drum machines, and more. The kicker can be done on the fly using the NSynth Super's front touch panel and dial, which means musicians inclined to do so can make brand new songs or add new tunes to an old collection mid-concert.

NSynth Super is based on a neural synthesizer algorithm called NSynth, which basically uses machine learning not to mix two sound profiles, but to "learn" what makes them unique and combine them to create an intermediate sound. The NSynth performs acoustic analysis through waveforms, so a wa electric electric electric guitar combined with the sound of a babbling brook is like blending the voices of two different singers. The team behind Google Brain and Magenta produced NSynth from the open source Magenta project, and Google Creative Labs used this work to implement it as NSynth Super.

Any DIY musicians who want their own NSynth Super will be happy to know that Google won't charge them for it, but they'll have to download the open source project files and templates, gather the materials and build the instruments themselves. Google has only produced a prototype of the NSynth Super and does not intend to sell it. Like the NSynth and NSynth Super documentation, Project Magenta's entire project is open source and available on GitHub, which means creative programmers and musicians can create and discover brand new things within the project framework. Magenta is based on machine learning, but once you have powerful enough AI technology and powerful enough machines to handle the project in its raw form, the only real limitation is that the processing of the audio and music is your own imagination.

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