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There is no musical input to the autoencoder, the user simply defines a latent vector, either on a GUI or using a MIDI controller, and the decoder network creates a sound. Synthesizer: This is like the example described above.We envision three potential uses for MusicAE: The network will decode the latent vector as if it had been encoded from sound, and will output a short audio sample, unique from any of the sounds it was trained on. Where this neural network becomes creative is when you bypass the encoder and simply introduce a vector of numbers into the latent space.

#BLOB OPERA MACHINE LEARNING HOW TO#

Over several epochs of training, the autoencoder learns how to efficiently compress sounds into a lower dimensional latent space, and then decode it back into a nearly identical sound. We train our autoencoder using a corpus containing tones generated by a variety of synthesizers, organs, and other keyboard instruments. Graphical representation of an autoencoder neural network architecture | by Steven Flores If the machine learning methods can be implemented as a plug-in in a standard format like virtual studio technology (VST), musicians will be able to integrate it seamlessly into their normal workflow. The best way to guarantee this last point is to build the tool on top of platforms that musicians are already familiar with, and in this digital age, the gold standard is the digital audio workstation. Additionally, the tool must be accessible, intuitive to use, and fit into a musician’s workflow. We think ML techniques can be most successful when they are used to enhance the artist’s creative experience.

In some cases, it tries to imitate a composer, in other cases a performer, but it tends to fall short. So what would constitute an ideal tool for musicians to gain access to machine learning? In many of the examples we’ve shown above, the AI is replacing, or attempting to replace, the musician.

#BLOB OPERA MACHINE LEARNING SOFTWARE#

The problem with NSynth is that, even if you can assemble it, it only works as a stand alone instrument, and can’t be implemented as software for the synthesizers or MIDI controllers that most musicians already own.Īn example of an assembled NSynth built on top of a Raspberry Pi with MIDI interface | by NSynth Super NSynth on the other hand present extensive open-source documentation on how to build the physical instrument, with standard interfaces like Musical Instrument Digital Interface (MIDI) or USB.

#BLOB OPERA MACHINE LEARNING DOWNLOAD#

The tool is only available online as a web app, and it clunkily requires artists to upload and download their short samples one at a time, with no easy connection to common programs such as digital audio workstations (DAWs). It captures the pitch and inflections of the original piece surprisingly well, but where it fails is in the interface. Tone Transfer allows musicians to upload short samples played on any instrument (or non-instrument), and it outputs a reinterpretation of the sample performed on one of four instruments: flute, saxophone, trumpet, or violin. Two of the most popular such tools are Tone Transfer and NSynth. However, another breed of music ML is rising alongside this one, one that expands the tools available to an artist, rather than replacing them entirely.īlob opera singers are astonished by their soprano's coloratura performance | by Google Arts and Culture While such programs can be extraordinarily complex, and are fun to use, their use cases are more-or-less relegated to novelty no serious artist would produce music through a singing blob or imitative piano program. On a sillier note, Blob Opera lets you control a group of blob shaped opera singers, inputting the pitch and vowel in real time. Celebrating Johann Sebastian Bach was a Google Doodle (apps and animations that replace the Google title on the search page) which allows you to compose a single melody, and it generates a four-part counterpoint in the style of Bach, while admittedly breaking some of Bach’s fundamental rules of which he wrote extensively. Most notably, Google has published dozens of fun apps and prototypes using Magenta, “an open source research project exploring the role of machine learning as a tool in the creative process.” Of the myriad of ML tools available, some work to enhance artists’ work, but many seek instead to replace the artist entirely.Īi-Duet lets you play a virtual piano, and automatically performs a duet along with you. Over the last few years, a number of tools have been published to introduce machine learning (ML) to the world of music.

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