The basic algorithm behind autocorrection software like T9 is pretty simple. The system is essentially the same as a word processor’s spell checker—as you type, the software checks each word against a built-in dictionary, and it suggests alternatives when it doesn’t find a match. Many phones will also try to predict what you’re going for and suggest a word before you’ve finished typing it.
There are two difficulties in this process, Taylor says. The first is building the correct dictionary. The phone’s list of words has to be both comprehensive and well-targeted for its audience, stuffed with colloquialisms that a modern mobile user might employ. The second problem is creating an accurate “language model,” the system that determines which words to suggest. If a user types in fecer, did he mean fever or feces? The right answer depends on the context and the user—if you were e-mailing your boss about your absence from work, you’d be going for the former, while if you were a film critic who’d just attended the The Last Airbender, you’d probably want the latter. The more sophisticated the autocorrection system, the more of these contextual factors get taken into account when suggesting alternatives.