Predictive text

Predictive text is an input technology most commonly used on mobile phones, and for accessibility. The technology allows words to be entered by a single keypress for each letter, as opposed to the multiple keypress approach used in the older generation of mobile phones. The intent is to simplify the writing of text messages, e-mail, entries into an address book or calendar, and the like. The number of keystrokes per character, on average, is comparable to using a Qwerty keyboard.

Background

Short message service (SMS) permits a mobile phone user to send text messages, messages, SMSes, texts, and txts as a short message. The most common system of SMS text input is referred to as "multi-tap". Using multi-tap, a key is pressed multiple times to access the list of letters on that key. For instance, pressing the"2" key once displays an, "a", twice displays a "b" and three times displays a "c". To enter two successive letters that are on the same key, the user must either pause or hit a "next" button. A user can type by pressing an alphanumeric keypad without looking at the electronic equipment display. Thus, multi-tap is easy to understand, and can be used without any visual feedback. However, multi-tap is not very efficient and is considered a hindrance by many users of electronic equipment. Also, since all twenty-six letters of the English language are entered using only eight alphanumeric keys, it is difficult to use SMS.

Predictive text improves on multi-tap. Predictive text entry dictionaries software applications generally minimize the number of key strokes a user is required to enter to express a word, phrase and/or expression (e.g., a graphical image, a text image, a smiley face, frown, etc.). With predictive text dictionaries, users of electronic equipment do not need to press each keypad number several times in order to get the desired letter. The user simply presses the number corresponding to the letter and, as long as the word exists in the predictive text dictionary, the electronic equipment will generally recognize the word. For instance, pressing "4663" would normally translate to the word "home" on a particular electronic equipment having a conventional English language predictive text entry dictionary installed. The most widely used systems of predictive text dictionaries are T9 (predictive text), iTap, and eZiText. Each of these systems requires the manufacturer to install a local dictionary of words and/or phrases for every input language that the electronic equipment supports in the electronic equipment.

Dictionary vs. non-dictionary systems

Traditional disambiguation works by referencing a dictionary of commonly used words, though Eatoni offers a dictionary-less disambiguation system. In dictionary-based systems, as the user presses the number buttons, an algorithm searches the dictionary for a list of possible words that match the keypress combination, and offers up the most probable choice. The user can then confirm the selection and move on, or use a key to cycle through the possible combinations. To perform future predictions, disambiguation may be combined with a word completion facility.

Like a spelling dictionary, such as used in text-processing software a disambiguation or predictive system may include a user database for storing entered words or phrases which are not in the pre-supplied database. When words are entered into the user database without direct user intervention, such systems are sometimes referred to as "learning" systems. Some disambiguation systems attempt to correct spelling, format text or perform other automatic rewrites, with the effect of either enhancing or obliterating user efforts to enter text.

History

Predictive entry of text from a telephone keypad has been known at least since the 1970s (Smith and Goodwin, 1971). Aspects of predictive text have been patented for instance by Kondraske (1985), and as a method for communicating with deaf people via phone in 1988 (Roy Feinson #4,754,474). Predictive text was mainly used to look up names in directories over the phone, until mobile phone text messaging came into widespread use.

Example

Consider a typical phone keypad:

A standard ITU-T E.161 keypad used for text messaging.

Suppose a user wishes to type 'The'. In a traditional "multi-tap" keypad entry system, it would be necessary to do the following:

• Press 8 (tuv) once to select t.
• Press 4 (ghi) twice to select h.
• Press 3 (def) twice to select e.

Meanwhile, in a phone with predictive text, it is only necessary to:

• Press 8 once to select the (tuv) group for the first character.
• Press 4 once to select the (ghi) group for the second character.
• Press 3 once to select the (def) group for the third character.

The system updates the display as each keypress is entered to show the most probable entry. In this case, predictive text reduced the number of button presses from 5 to 3. The effect is even greater with longer, more complex words.

A dictionary-based predictive system is based on hope that the desired word is in the dictionary. That hope may be misplaced if the word differs in any way from common usage— in particular, if the word is not spelled correctly, or typed correctly, or is slang, or is a proper noun. In these cases, some other mechanism must be used to enter the word.

Furthermore, the simple dictionary approach fails with agglutinative languages, where a single word doesn't necessarily represent a single semantic entity. A morphological synthesizer is needed.

Companies and products

Predictive text is developed and marketed in a variety of competing products. Nuance Communications's T9 is the market leader. Other services include Motorola's iTap, ZiCorp's eZiText, Eatoni Ergonomic's LetterWise, Prevalent Devices's Phraze-It (character, rather than word-based prediction), WordWise (word-based prediction without a dictionary), EQ3 (a Qwerty-like layout compatible with regular telephone keypads); Xrgomics' TenGO (a six-key reduced QWERTY keyboard system); and Adaptxt (considers language, context, grammar and semantics).

Textonyms

Words produced by the same combination of keypresses are technically paragrams,^[1] but colloquially they're often referred to as "textonyms" (or "txtonyms",) "adaptonyms", "cellodromes", or "T9onyms" (pronounced "tynonyms").[2]

One quoted example of textonyms shows that the keypresses required to produce the message "Ask the cool barmaid for nine pints of beer" could result in "Ask tie book carnage for mind shots me adds". Such examples illustrate the importance of proof-reading text messages after typing them, or developing disambiguation systems with lower ambiguity.

Some "textonyms" include

• 63 = me, of
• 5477 = kiss, lips, lisp

According to the ispell dictionaries, other examples of textonyms are:

• 22737 = acres bards barer bares barfs baser bases bbses caper capes cards carer cares cases (English; 14 words)
• 7254 = σάκη σακί ράλι πάλη ρακί σάμι ρακή ραμί ράκη σάλι σάμη σαλή πάλι (Greek; 13 words)

Such textonyms may even be adopted in regular speech, particularly by teenagers; for example, the use of "book" to mean "cool",[3], "idiom" to mean "Heino" (an abbreviation for "Heineken", used in Dublin) and "Zonino!" used to mean "Woohoo!".

As well as textonyms, there are a large number of gibberish words such as Blairf, which appears with the input 252473. The other default suggestion for this combination of key presses is Blaire (a reasonably common surname). Phones that contain the word blairf, such as the Sony Ericsson K610i, do not by default contain the name Claire.

See also

• Assistive technology
• Autocomplete
• Input method editor
• iPhone
• ITap
• LG VX9400
• List of BlackBerry Products
• Multi-tap
• Nokia 5510
• Q9 input method — method for inputting Chinese characters on a standard mobile phone keyboard
• SMS language
• Speech-to-Text Reporter
• T9 (predictive text)
• Texas Instruments' Avigo 10
• Text entry interface
• Text messaging
• Thumbcast
• Word completion

Notes

1. ^ Paragram - a word formed by altering a letter or group of letters in another word.

External links

Companies

• T9 (Nuance Communications)
• Eatoni Ergonomics
• ZiCorp
• SureType (RIM)
• iTap (Motorola)
• Adaptxt
• TenGO (Xrgomics)
• (WordLogic)

Additional reference

• "Alphabetic Data Entry Via the Touch-Tone Pad: A Comment", Sidney L. Smith and Nancy C. Goodwin, The Mitre Corporation, HUMAN FACTORS, 1971, 13(2) Page 189-190
• T9 training
• GSM Helpdesk Netherlands - T9 Wordinput
• New Scientist article on textonyms
• An Australian newspaper article on textonyms
• Technical notes on iTap (including lists of textonyms)