very interesting research...
uc berkeley press release
uc berkeley press release
The researchers were able to take several 10-minute sound recordings of users typing at a keyboard, feed the audio into a computer, and use an algorithm to recover up to 96 percent of the characters entered.
What makes the technique feasible is that each keystroke makes a relatively distinct sound, however subtle, when hit. Typical users type about 300 characters per minute, leaving enough time for a computer to isolate the sounds of individual keystrokes and categorize the letters based upon the statistical characteristics of English text. For example, the letters "th" will occur together more frequently than "tj," and the word "yet" is far more common than "yrg."
"Using statistical learning theory, the computer can categorize the sounds of each key as it's struck and develop a good first guess with an accuracy of 60 percent for characters, and 20 percent for words," said Li Zhuang, a UC Berkeley Ph.D. student in computer science and lead author of the study. "We then use spelling and grammar checks to refine the results, which increased the character accuracy to 70 percent and the word accuracy to 50 percent. The text is somewhat readable at this point."
