

A new technique to enter text using a mobile phone keypad is described. For text input, the traditional touchtone phone keypad is ambiguous because each key encodes three or four letters. Instead of using a stored dictionary to guess the intended word, our technique uses probabilities of letter sequences --- "prefixes" --- to guess the intended letter. Compared to dictionary-based methods, this technique, called LetterWise, takes significantly less memory and allows entry of non-dictionary words without switching to a special input mode. We conducted a longitudinal study to compare LetterWise to Multitap, the conventional text entry method for mobile phones. The experiment included 20 participants (10 LetterWise, 10 Multitap), and each entered phrases of text for 20 sessions of about 30 minutes each. Error rates were similar between the techniques; however, by the end of the experiment the mean entry speed was 36% faster with LetterWise than with Multitap.

TiltType is a novel text entry technique for mobile devices. To enter a character, the user tilts the device and presses one or more buttons. The character chosen depends on the button pressed, the direction of tilt, and the angle of tilt. TiltType consumes minimal power and requires little board space, making it appropriate for wristwatch-sized devices. But because controlled tilting of one's forearm is fatiguing, a wristwatch using this technique must be easily removable from its wriststrap. Applications include two-way paging, text entry for watch computers, web browsing, numeric entry for calculator watches, and existing applications for PDAs.

EdgeWrite is a new unistroke text entry method for handheld devices designed to provide high accuracy and stability of motion for people with motor impairments. It is also effective for able-bodied people. An EdgeWrite user enters text by traversing the edges and diagonals of a square hole imposed over the usual text input area. Gesture recognition is accomplished not through pattern recognition but through the sequence of corners that are hit. This means that the full stroke path is unimportant and recognition is highly deterministic, enabling better accuracy than other gestural alphabets such as Graffiti. A study of able-bodied users showed subjects with no prior experience were 18% more accurate during text entry with Edge Write than with Graffiti (p>.05), with no significant difference in speed. A study of 4 subjects with motor impairments revealed that some of them were unable to do Graffiti, but all of them could do Edge Write. Those who could do both methods had dramatically better accuracy with Edge Write.

TiltText, a new technique for entering text into a mobile phone is described. The standard 12-button text entry keypad of a mobile phone forces ambiguity when the 26- letter Roman alphabet is mapped in the traditional manner onto keys 2-9. The TiltText technique uses the orientation of the phone to resolve this ambiguity, by tilting the phone in one of four directions to choose which character on a particular key to enter. We first discuss implementation strategies, and then present the results of a controlled experiment comparing TiltText to MultiTap, the most common text entry technique. The experiment included 10 participants who each entered a total of 640 phrases of text chosen from a standard corpus, over a period of about five hours. The results show that text entry speed including correction for errors using TiltText was 23% faster than MultiTap by the end of the experiment, despite a higher error rate for TiltText. TiltText is thus amongst the fastest known language-independent techniques for entering text into mobile phones.

We present the design and implementation of a word-level stroking system called Fisch, which is intended to improve the speed of character-level unistrokes. Importantly, Fisch does not alter the way in which character-level unistrokes are made, but allows users to gradually ramp up to word-level unistrokes by extending their letters in minimal ways. Fisch relies on in-stroke word completion, a flexible design for fluidly turning unistroke letters into whole words. Fisch can be memorized at the motor level since word completions always appear at the same positions relative to the strokes being made. Our design for Fisch is suitable for use with any unistroke alphabet. We have implemented Fisch for multiple versions of EdgeWrite, and results show that Fisch reduces the number of strokes during entry by 43.9% while increasing the rate of entry. An informal test of "record speed" with the stylus version resulted in 50-60 wpm with no uncorrected errors.