Future directions for the Dasher project

The Dasher project is being taken forward by the Inference group in the Cavendish laboratory; other researchers who share our aim of seeing Dasher widely used in the real world are also encouraged to work on Dasher.

The initial focus is the development of Dasher for disabled users; additional goals are the development of the palmtop version; the development of Japanese and Chinese versions; and the creation of specialized versions for particular computers. In order to take all these goals forward, we have released the Dasher source code as an Open Source project. Our Current core activities are listed on the development page.

Other ideas include:

Controlling Dasher by Breath

Now done! Works with version 3

Controlling Dasher by Buttons

Now done! Should be released in version 4

Controlling Dasher by Tilt sensors

Should be very easy to do with version 3

Linking Dasher to the Owl, a very low-cost eyetracker

`Peano Dasher' and other Fully Two-dimensional Dashers

capable of using both dimensions as information sources.
David MacKay and Piotr Zielinski

basher

a mouse-driven command-line interface; a one-handed, keyboardless alternative to tcsh, csh, bash, etc.
Unfortunately the name dash has recently been adopted for another shell in Debian, The Debian Almquist Shell, so we are using the name basher for this concept.

Xybernaut

The Xybernaut company have kindly provided a wearable computer for us to test Dasher on.

Linux eyetracker

Piotr Zielinski

Self-tuning eyetracker

Phil Cowans and Piotr Zielinski

Improved language models

Phil Cowans

Dreams for the future

Hybrid voice-dasher system

Speak into an imperfect speech-recognizer, and watch as its inferences are displayed as predictions; wherever it is not sure what you said, use dasher to steer into the correct sentence. Much easier than having to correct errors by saying further speech-commands!
This system, Speech-Dasher, is now working, thanks to Keith Vertanen.

Hybrid automatic translation-dasher system

Assume we have a poor translation system that translates badly from French to English. An expert has to zip through the translation and clean up errors. This cleaning-up could be done within Dasher, using the output of the translator to define a language model.