Learning tools for musical instruments-1


Learning tool for a musical instrument

Article: 04

This article is based on a Meta-instrument for interactive, on-the-fly machine learning project done at the Princeton University. They had been proposed a method for harnessing machine learning algorithms within a radically interactive paradigm, in which the designer may repeatedly generate examples, train a learner, evaluate outcomes, and modify parameters in real-time within a single software environment. They had been described their meta-instrument, Wekinator, which allows a user to engage in on-the-fly learning using arbitrary control modalities and sound synthesis environments. They provide details regarding the system implementation and discuss their experiences using the Wekinator for experimentation and performance. 

They had been introduced a Wekinator, which allows musicians, composers, and new instrument designers to interactively train and modify many standard machine learning algorithms in real-time. The Wekinator is a general tool that is not specialized for learning a concept, using a particular input controller, or using learning outputs in a particular way. Users are free to choose among a suite of built-in feature extractors for audio, video, and gestural inputs, or they can supply their own feature extractors. They can thus train a learning algorithm to respond to inputs ranging from conducting gestures to vocalizations to custom sensor devices.

They had been presented their tool with GUI panes for training and running. Validations, error detections and all the instructions are provided by the GUI panes. They must be in a creative context.
This is one of the learning tools that I had found regarding to my objective.

 Reference

Author: Dilini Herath

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