Two UC Berkeley researchers have released a paper describing a method for figuring out what someone is typing by analyzing the sounds the keyboard makes.
The algorithm works in three basic stages. First, it isolates the sound of each individual keystroke. Second, it takes all of the recorded keystrokes and puts them into about fifty categories, where the keystrokes within each category sound very similar. Third, it uses fancy machine learning methods to recover the sequence of characters typed, under the assumption that the sequence has the statistical characteristics of English text.
The third stage is the hardest one. You start out with the keystrokes put into categories, so that the sequence of keystrokes has been reduced a sequence of category-identifiers
