This article is about word completion on limited physical keyboards, such as early mobile phone keyboards. For a similar article for general keyboards, smartphones and tablets, see Autocomplete.
Predictive text is an input technology used where one key or button represents many letters, such as on the physical numeric keypads of mobile phones and in accessibility technologies. Each key press results in a prediction rather than repeatedly sequencing through the same group of "letters" it represents, in the same, invariable order. Predictive text could allow for an entire word to be input by single keypress. Predictive text makes efficient use of fewer device keys to input writing into a text message, an e-mail, an address book, a calendar, and the like.
The most widely used, general, predictive text systems are T9, iTap, eZiText, and LetterWise/WordWise. There are many ways to build a device that predicts text, but all predictive text systems have initial linguistic settings that offer predictions that are re-prioritized to adapt to each user. This learning adapts, by way of the device memory, to a user's disambiguating feedback that results in corrective key presses, such as pressing a "next" key to get to the intention. Most predictive text systems have a user database to facilitate this process.
Theoretically the number of keystrokes required per desired character in the finished writing is, on average, comparable to using a keyboard. This is approximately true providing that all words used are in its database, punctuation is ignored, and no input mistakes are made typing or spelling.[1] The theoretical keystrokes per character, KSPC, of a keyboard is KSPC=1.00, and of multi-tap is KSPC=2.03. Eatoni's LetterWise is a predictive multi-tap hybrid, which when operating on a standard telephone keypad achieves KSPC=1.15 for English.
The choice of which predictive text system is the best to use involves matching the user's preferred interface style, the user's level of learned ability to operate predictive text software, and the user's efficiency goal. There are various levels of risk in predictive text systems, versus multi-tap systems, because the predicted text that is automatically written that provide the speed and mechanical efficiency benefit, could, if the user is not careful to review, result in transmitting misinformation. Predictive text systems take time to learn to use well, and so generally, a device's system has user options to set up the choice of multi-tap or of any one of several schools of predictive text methods.
Background
Short message service (SMS) permits a mobile phone user to send text messages (also called 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, requiring potentially many keystrokes to enter a single letter.
In ideal predictive text entry, all words used are in the dictionary, punctuation is ignored, no spelling mistakes are made, and no typing mistakes are made. The ideal dictionary would include all slang, proper nouns, abbreviations, URLs, foreign-language words and other user-unique words. This ideal circumstance gives predictive text software the reduction in the number of key strokes a user is required to enter a word. The user presses the number corresponding to each letter and, as long as the word exists in the predictive text dictionary, or is correctly disambiguated by non-dictionary systems, it will appear. For instance, pressing "4663" will typically be interpreted as the word good, provided that a linguistic database in English is currently in use, though alternatives such as home, hood and hoof are also valid interpretations of the sequence of key strokes.
The most widely used systems of predictive text are Tegic's T9, Motorola's iTap, and the Eatoni Ergonomics' LetterWise and WordWise. T9 and iTap use dictionaries, but Eatoni Ergonomics' products uses a disambiguation process, a set of statistical rules to recreate words from keystroke sequences. All predictive text systems require a linguistic database for every supported input language.
Dictionary vs. non-dictionary systems
Traditional disambiguation works by referencing a dictionary of commonly used words, though Eatoni offers a dictionaryless 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.
A non-dictionary system constructs words and other sequences of letters from the statistics of word parts. To attempt predictions of the intended result of keystrokes not yet entered, disambiguation may be combined with a word completion facility.
Either system (disambiguation or predictive) may include a user database, which can be further classified as a "learning" system when words or phrases are entered into the user database without direct user intervention. The user database is for storing words or phrases which are not well disambiguated by the pre-supplied database. Some disambiguation systems further attempt to correct spelling, format text or perform other automatic rewrites, with the risky effect of either enhancing or frustrating user efforts to enter text.
History
The predictive text and autocomplete technology was invented out of necessities by Chinese scientists and linguists in the 1950s to solve the input inefficiency of the Chinese typewriter,[2] as the typing process involved finding and selecting thousands of logographic characters on a tray,[3] drastically slowing down the word processing speed.[4][5]
The actuating keys of the Chinese typewriter created by Lin Yutang in the 1940s included suggestions for the characters following the one selected. In 1951, the Chinese typesetter Zhang Jiying arranged Chinese characters in associative clusters, a precursor of modern predictive text entry, and broke speed records by doing so.[6] Predictive entry of text from a telephone keypad has been known at least since the 1970s (Smith and Goodwin, 1971). Predictive text was mainly used to look up names in directories over the phone, until mobile phone text messaging came into widespread use.
Example
A standard ITU-TE.161 keypad used for text messaging
On a typical phone keypad, if users wished to type the in a "multi-tap" keypad entry system, they would need to:
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, they need only:
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 example, prediction reduced the number of button presses from five to three. The effect is even greater with longer words and those composed of letters later in each key's sequence.
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 or typed correctly, 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 does not necessarily represent a single semantic entity.
Companies and products
Predictive text is developed and marketed in a variety of competing products, such as Nuance Communications's T9. Other products include Motorola's iTap; Eatoni Ergonomic's LetterWise (character, rather than word-based prediction); WordWise (word-based prediction without a dictionary); EQ3 (a QWERTY-like layout compatible with regular telephone keypads); Prevalent Devices's Phraze-It; Xrgomics' TenGO (a six-key reduced QWERTY keyboard system); Adaptxt (considers language, context, grammar and semantics); Lightkey (a predictive typing software for Windows); Clevertexting (statistical nature of the language, dictionaryless, dynamic key allocation); and Oizea Type (temporal ambiguity); Intelab's Tauto; WordLogic's Intelligent Input Platform™ (patented, layer-based advanced text prediction, includes multi-language dictionary, spell-check, built-in Web search); Google's Gboard.
Textonyms
Words produced by the same combination of keypresses have been called "textonyms";[7] also "txtonyms";[8] or "T9onyms" (pronounced "tynonyms" /ˈtaɪnənɪmz/[7]), though they are not specific to T9. Selecting the wrong textonym can occur with no misspelling or typo, if the wrong textonym is selected by default or user error. As mentioned above, the key sequence 4663 on a telephone keypad, provided with a linguistic database in English, will generally be disambiguated as the word good. However, the same key sequence also corresponds to other words, such as home, gone, hoof, hood and so on. For example, "Are you home?" could be rendered as "Are you good?" if the user neglects to alter the default 4663 word. This can lead to misunderstandings; for example sequence 735328 might correspond to either select or its antonymreject. A 2010 brawl that led to manslaughter was sparked by a textonym error.[9] Predictive text choosing a default different from that which the user expects has similarities with the Cupertino effect, by which spell-check software changes a spelling to that of an unintended word.
Textonyms were used as Millennial slang; for example, the use of the word book to mean cool, since book was the default in predictive text systems that assumed it was more frequent than cool.[10] This is related to cacography.
Disambiguation failure and misspelling
Textonyms are not the only issue limiting the effectiveness of predictive text implementations. Another significant problem are words for which the disambiguation produces a single, incorrect response. The system may, for example, respond with Blairf upon input of 252473, when the intended word was Blaise or Claire, both of which correspond to the keystroke sequence, but are not, in this example, found by the predictive text system. When typos or misspellings occur, they are very unlikely to be recognized correctly by a disambiguation system, though error correction mechanisms may mitigate that effect.
Keystroke logging, often referred to as keylogging or keyboard capturing, is the action of recording (logging) the keys struck on a keyboard, typically covertly, so that a person using the keyboard is unaware that their actions are being monitored. Data can then be retrieved by the person operating the logging program. A keystroke recorder or keylogger can be either software or hardware.
A telephone keypad is a keypad installed on a push-button telephone or similar telecommunication device for dialing a telephone number. It was standardized when the dual-tone multi-frequency signaling (DTMF) system was developed in the Bell System in the United States in the 1960s – this replaced rotary dialing, that had been developed for electromechanical telephone switching systems. Because of the abundance of rotary dial equipment still on use well into the 1990s, many telephone keypads were also designed to be backwards-compatible: as well as producing DTMF pulses, they could optionally be switched to produce loop-disconnect pulses electronically.
An input method is an operating system component or program that enables users to generate characters not natively available on their input devices by using sequences of characters that are available to them. Using an input method is usually necessary for languages that have more graphemes than there are keys on the keyboard.
In computing, a keyboard shortcut is a software-based assignment of an action to one or more keys on a computer keyboard. Most operating systems and applications come with a default set of keyboard shortcuts, some of which may be modified by the user in the settings.
Typing is the process of writing or inputting text by pressing keys on a typewriter, computer keyboard, mobile phone, or calculator. It can be distinguished from other means of text input, such as handwriting and speech recognition. Text can be in the form of letters, numbers and other symbols. The world's first typist was Lillian Sholes from Wisconsin in the United States, the daughter of Christopher Sholes, who invented the first practical typewriter.
Autocomplete, or word completion, is a feature in which an application predicts the rest of a word a user is typing. In Android and iOS smartphones, this is called predictive text. In graphical user interfaces, users can typically press the tab key to accept a suggestion or the down arrow key to accept one of several.
GOMS is a specialized human information processor model for human-computer interaction observation that describes a user's cognitive structure on four components. In the book The Psychology of Human Computer Interaction. written in 1983 by Stuart K. Card, Thomas P. Moran and Allen Newell, the authors introduce: "a set of Goals, a set of Operators, a set of Methods for achieving the goals, and a set of Selections rules for choosing among competing methods for goals." GOMS is a widely used method by usability specialists for computer system designers because it produces quantitative and qualitative predictions of how people will use a proposed system.
A compose key is a key on a computer keyboard that indicates that the following keystrokes trigger the insertion of an alternate character, typically a precomposed character or a symbol.
T9 is a predictive text technology for mobile phones, originally developed by Tegic Communications, now part of Nuance Communications. T9 stands for Text on 9 keys.
iTap is a predictive text technology developed for mobile phones, developed by Motorola employees as a competitor to T9. It was designed as a replacement for the old letter mappings on phones to help with word entry. This makes some of the modern mobile phones features like text messaging and note-taking easier.
On personal computers with numeric keypads that use Microsoft operating systems, such as Windows, many characters that do not have a dedicated key combination on the keyboard may nevertheless be entered using the Alt code. This is done by pressing and holding the Alt key, then typing a number on the keyboard's numeric keypad that identifies the character and then releasing Alt.
A virtual keyboard is a software component that allows the input of characters without the need for physical keys. Interaction with a virtual keyboard happens mostly via a touchscreen interface, but can also take place in a different form when in virtual or augmented reality.
Multi-tap (multi-press) is a text entry system for mobile phones. The alphabet is printed under each key in a three-letter sequence as follows; ABC under 2 key, DEF under 3 key, etc. Exceptions are the "7" key, which adds a letter ("PQRS"), and the "9" key which includes "Z". Punctuation is typically accessed via the "1" key and various functions mapped to the "*" key and "#" key.
LetterWise and WordWise were predictive text entry systems developed by Eatoni Ergonomics (Eatoni) for handheld devices with ambiguous keyboards / keypads, typically non-smart traditional cellphones and portable devices with keypads. All patents covering those systems have expired. LetterWise used a prefix based predictive disambiguation method and can be demonstrated to have some advantages over the non-predictive Multi-tap technique that was in widespread use at the time that system was developed. WordWise was not a dictionary-based predictive system, but rather an extension of the LetterWise system to predict whole words from their linguistic components. It was designed to compete with dictionary-based predictive systems such as T9 and iTap which were commonly used with mobile phones with 12-key telephone keypads.
A text entry interface or text entry device is an interface that is used to enter text information in an electronic device. A commonly used device is a mechanical computer keyboard. Most laptop computers have an integrated mechanical keyboard, and desktop computers are usually operated primarily using a keyboard and mouse. Devices such as smartphones and tablets mean that interfaces such as virtual keyboards and voice recognition are becoming more popular as text entry systems.
Unicode input is method to add a specific Unicode character to a computer file; it is a common way to input characters not directly supported by a physical keyboard. Characters can be entered either by selecting them from a display, by typing a certain sequence of keys on a physical keyboard, or by drawing the symbol by hand on touch-sensitive screen. In contrast to ASCII's 96 element character set, Unicode encodes hundreds of thousands of graphemes (characters) from almost all of the world's written languages and many other signs and symbols besides.
A computer keyboard is a peripheral input device modeled after the typewriter keyboard which uses an arrangement of buttons or keys to act as mechanical levers or electronic switches. Replacing early punched cards and paper tape technology, interaction via teleprinter-style keyboards have been the main input method for computers since the 1970s, supplemented by the computer mouse since the 1980s.
SureType is a QWERTY-based character input method for cell phones which is used on the BlackBerry Pearl. SureType combines a traditional telephone keypad with a QWERTY-based keyboard to create a non-standard way to input text on a cell phone. In addition, SureType contains a list of 35,000 English words, so when a user types the beginning of a word, all the possible words which start with those letters show up on the screen. Additional words can also be added to the word list.
MessagEase is an input method and virtual keyboard for touchscreen devices. It relies on a new entry system designed by Saied B. Nesbat, formatted as a 3x3 matrix keypad where users may press or swipe up, down, left, right, or diagonally to access all keys and symbols. It is a keyboard that was designed for devices like cell phones, mimicking the early cell phones' limited number of 12 keys.
EDT is a character-based text editor from Digital Equipment Corporation (DEC) running on PDP-11, and later for its OpenVMS operating system. It can respond to single keystrokes, and uses function keys to implement commands to the editor. EDT was introduced originally as a line-mode editor. The screen mode was developed first as the Keyboard Editor (KED) on RT-11 as part of the FMS-11 project by Darrell Duffy; EDT on the other operating systems was then enhanced to be compatible with KED.
References
↑ I. Scott MacKenzie (2002). "KSPC (Keystrokes per Character) as a Characteristic of Text Entry Techniques". Proceedings of MobileHCI 2002. Values [of KSPC] for English range from about 10 for methods using only cursor keys and a SELECT key to about 0.5 for word prediction techniques. It is demonstrated that KSPC is useful for a priori analyses, thereby supporting the characterisation and comparison of text-entry methods before labour-intensive implementations and evaluations
↑ Dartmelk, Jewis. "Txtonyms"(PDF). University College London: Centre for Mathematics and Physics in the Life Sciences and Experimental Biology. Retrieved 5 April 2013.
Smith, Sidney L.; Goodwin, Nancy C. (1971). "Alphabetic Data Entry Via the Touch-Tone Pad: A Comment". Human Factors. 13 (2): 189–190. doi:10.1177/001872087101300212. S2CID61164630.
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