Wekinator in Pathum Thani: how Rebecca Fiebrink's free machine learning tool lets musicians build new instruments, and why Kanom reads the tempo in her AI piano lessons

Kanom is fifteen and belongs to a maker club at a secondary school in Pathum Thani. The club builds robots, games and gadgets from cheap parts. This term the members decided to build a musical instrument that responds to hand movements in the air. Their teacher suggested a free program called Wekinator, and Kanom volunteered to research it.

Wekinator was created by Rebecca Fiebrink, a computer scientist and musician, during her doctoral research at Princeton University around 2009. She later worked at Goldsmiths, University of London, and at the Creative Computing Institute of the University of the Arts London. The software is open source and free to download, which made it perfect for a school club with a tiny budget.

The key idea is interactive machine learning. Instead of writing complex code, a user teaches the computer by giving examples. Kanom might hold her hand high and tell the program that this position should produce a high note, then hold it low for a low note. After a few examples, the model learns the relationship and can respond to new positions in between.

Wekinator connects inputs and outputs using a standard music messaging format called Open Sound Control. Inputs can come from a webcam, a microphone, a game controller, a motion sensor or a smartphone. Outputs can control synthesisers, music software, lights or animations. This flexibility lets artists invent instruments that never existed before.

Fiebrink designed the tool with musicians and artists in mind, not only programmers. She has argued that people should be able to shape AI through demonstration and experimentation, adjusting the model until it feels right. That approach matched the maker club's spirit: try something, listen, change it, try again.

Wekinator has also been used in teaching. Fiebrink created an online course titled Machine Learning for Musicians and Artists, which introduced students around the world to building interactive systems. Kanom watched several of its introductory videos and found the explanations friendly, even though some of the mathematics went over her head.

Kanom's interest in music comes from her piano lessons, which she takes through TiGA AI, an online piano learning app she started using at twelve. The app's AI piano teacher listens to each attempt and tells her where notes or rhythm drifted. She explained to the club that the app uses AI to understand her playing, while Wekinator would let them design how AI responds to movement.

The club built a simple instrument using a webcam. Raising a hand made the pitch rise, moving it sideways changed the sound's brightness, and closing the fist stopped the note. Training took about twenty minutes of giving examples. The first version sounded chaotic, so they added more examples until the response felt smooth and predictable.

The structured piano course in the app had taught Kanom about scales, so she suggested limiting the instrument to the notes of a pentatonic scale. With that change, any movement produced pleasant melodies. Her clubmates were delighted, and the teacher pointed out that musical knowledge had improved the engineering, not just the other way round.

For their school open day, the club planned a short performance. Kanom would play a slow melody on the keyboard while a clubmate added floating notes with the gesture instrument. They rehearsed several times, listening carefully to keep the two parts together, and visitors gathered around to try the air instrument afterwards.

For any student who wants to learn piano, tools like Wekinator show how music, technology and creativity can meet. Understanding scales, rhythm and harmony makes it easier to design new instruments that sound good. And learning to play music on a traditional keyboard gives a strong foundation for experimenting with entirely new ways to perform.

Her school's music lessons include a project on instruments from around the world, and the teacher asked the club to present their invention as an instrument of the future. Kanom described how Wekinator learns from examples and played a short duet with her clubmate. Younger students lined up to wave their hands in front of the webcam.

Training a model by showing examples

Before every rehearsal, Kanom reads the tempo marking at the head of the first bar out loud, Moderato or Allegro, to settle how quickly her hands should begin. Her clubmate then sets the gesture instrument to follow the same pace. She keeps up her AI piano lessons each evening, hoping one day to play piano alongside an instrument she has trained entirely herself.

Frequently asked questions

Q: What is Wekinator? A: Wekinator is free, open-source software created by Rebecca Fiebrink. It lets people train machine learning models in real time by giving examples, connecting inputs such as webcams or game controllers to sound and other outputs.

Q: Who uses Wekinator? A: Musicians, artists, students and researchers use it to build new instruments and interactive performances. It has also been used in teaching, including an online course on machine learning for musicians and artists.

Q: How is Wekinator different from AI piano lessons? A: Wekinator helps people design their own interactive systems. AI piano lessons in an online piano learning app use AI to listen to a learner on a keyboard and offer feedback on notes and rhythm.

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