A collection of AI and Chrome experiments inspired by Morse code on Android Gboard.
Developer Tania Finlayson found her voice through Morse code. Now she’s partnering with Google to bring Morse code to Gboard, so others can try it for accessible communication.
Morse code for Gboard includes settings that allow users to customize the keyboard to their unique usage needs. It works in tandem with Android Accessibility features like Switch Access and Point Scan.
This provides access to Gboard's AI driven predictions and suggestions, as well as an entry point to AI-powered products, like the Google Assistant.
I’m very excited that Gboard now has a Morse keyboard that allows for switch-access, with various settings to accommodate more people’s unique needs.
I’m even more excited about what people will build. From small, fun games and new teaching tools, to fully fledged communication apps based on the ML-driven WaveNet starter code. I’d also love to see your hardware hacks for switches. I’ve already asked my husband Ken to post one of his own as well! Whatever you build — big or small — we’d love for you to submit it here. You never know — even small hacks you come up with could open the world for newcomers to Morse code.
By Tania and Ken Finlayson, Use All Five, with friends at Google Creative Lab
Tania and team created this trainer to make learning Morse code more fun and to encourage people to keep at it. Give it a try if you’ve set up Morse code for Gboard and are ready to learn Morse.
By Selman Design and friends at Google Creative Lab
This is a printable and open source version of the pictographs used in the Morse trainer. Use or modify the images however you want to.
This artwork is made available by Google, LLC. under the Creative Commons Attribution 4.0 International license.
By Jane Friedhoff and Use All Five
This is a text-to-speech (TTS) app that converts written text into spoken word. What makes this example Morse-compatible is that it allows folks to activate the voice with a unique Morse sequence.
This experiment uses Google’s ML-powered Cloud Text-to-Speech API which enables developers to synthesize natural-sounding speech with many voice options. It uses WaveNet which incorporates DeepMind’s Machine Learning research.
By Ken Finlayson
This experiment is a DIY hardware adapter that enables assistive tech developers to connect existing switch based input systems to their Android device. Once connected, 2 switch assistive systems (with an additional switch for mode switching) can control both the standard Android accessibility functions as well as text entry through Morse on Gboard.
This experiment is built using Arduino and is compatible with most standard assistive 2 switch systems with ⅛” mono outputs.
Contribute your own experiment to this collection.