Predictive text is an input technology used where one key or button represents many letters, such as on the 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.
Predictive text programs have been around for a long time, and many are still available. The first one I used was Brown Bag Software’s MindReader, which arrived on a 5.25in floppy disk in the. Find and compare top Predictive Analytics software on Capterra, with our free and interactive tool. Quickly browse through hundreds of Predictive Analytics tools and systems and narrow down your top choices. Filter by popular features, pricing options, number of users, and read reviews from real users and find a tool that fits your needs.
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[edit]
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[edit]
How to unlock my iphone 5s for free. 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[edit]
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.[2] 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), while a fully functional keypad to text system for communicating with deaf people via phone was patented in 1988 by Roy Feinson (#4,754,474) that included most of the features of modern predictive text systems including disambiguation and local dictionary storage. Predictive text was mainly used to look up names in directories over the phone, until mobile phone text messaging came into widespread use.
Example[edit]
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[edit]
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).
Textonyms[edit]
Words produced by the same combination of keypresses have been called 'textonyms';[3] also 'txtonyms';[4] or 'T9onyms' (pronounced 'tynonyms'[3]), 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 row that led to manslaughter was sparked by a textonym error.[5] 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 have been used as Generation Y slang; for example, the use of the word book to mean cool, since book is the default in those predictive text systems that assume it is more frequent than cool.[6] This is related to cacography.
Disambiguation failure and misspelling[edit]
Textonyms in which a disambiguation system gives more than one dictionary word for a single sequence of keystrokes are not the only issue, or even the most important issue, limiting the effectiveness of predictive text implementations. More important, according to the above references,[which?] 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.
See also[edit]
Concepts[edit]
Products[edit]
Devices[edit]
References[edit]
- ^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
- ^Fisher, Jamie. 'The Left-Handed Kid'. London Review of Books. Retrieved 16 March 2018.
- ^ ab'Slang early-warning alert: `Book' is the new `cat's pajamas' | Change of Subject'. Blogs.chicagotribune.com. 2007-01-19. Retrieved 2009-07-08.
- ^Dartmelk, Jewis. 'Txtonyms'(PDF). University College London: Centre for Mathematics and Physics in the Life Sciences and Experimental Biology. Retrieved 5 April 2013.
- ^'Indefinite sentence for killing his friend'. This Is Lancashire. 2 April 2011. Retrieved 5 April 2013.
- ^Alleyne, Richard (5 Feb 2008). 'Predictive text creating secret teen language'. The Daily Telegraph. Retrieved 5 April 2013.
Further reading[edit]
- 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.
External links[edit]
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Predictive_text&oldid=929446861'
Predictive text is not a new technology. Most mobile devices have a built-in predictive text feature, regardless of the model and manufacturer. If you’re using a smartphone, then it most probably has a predictive typing feature.
Game resident evil 4. Predictive typing is an input technology that makes typing faster and more efficient by suggesting keywords based on the letters being typed. The suggested words are based on the context of the other words you are typing and the first letters you typed.
What Is Windows 10 Predictive Typing?
Windows users had a taste of predictive typing when Redstone 5 test build brought SwiftKey touch keyboard support to Windows 10. But with the latest 20H1 build, Microsoft is bringing predictive typing to all Windows 10 apps. This new feature, which was hidden in the latest build, offers suggestions of words that the operating system predicts you will write. You can quickly select the word you want to use from the suggestions by clicking on it.
The current AI-enabled hardware text suggestions on Windows 10 are displayed above the word being typed. With the new predictive typing feature of Windows 10, the suggested words appear in-line instead. This means that the predictive typing feature will suggest words as you type the letters. The suggested words may differ the more letters you type in.
If you’re familiar with Gmail’s intelligent predictive typing feature, then you’ll have a clear understanding of how the Window 10 version works. The in-line text suggestions for the words you type works in Windows 10 applications, such as OneNote, Notepad, and Microsoft To-Do. The feature also work s in some third-party apps.
Albacore, a software expert, discovered the new feature and posted in on Twitter, along with a GIF that shows how the feature works with Notepad. As seen in the video, the new predictive feature works a lot faster and smarter than its predecessor.
How to Enable Predictive Typing on Windows 10?
Tests done by various tech experts show that the new predictive text feature still needs some work when it comes to accuracy and performance. However, it still proves to be a huge upgrade to the existing hardware text suggestions you see on Windows 10.
For example, the inline predictive text feature does not work in web browsers or webpages. If you try to compose a message or a post on Facebook, the text suggestions do not appear. The same goes for browsers.
There has been no announcement yet from Microsoft whether it will provide inline predictive typing support to all third-party apps, or it will be limited only to native Windows 10 apps. If Microsoft does roll out the feature for all apps, this new typing experience can immensely boost productivity and efficiency when using said apps.
The Windows 10 20H1 update will be rolled out around April next year and is currently being tested with the Windows Insider program. That means Microsoft still has almost a year to perfect this feature and hopefully make it more efficient.
The Windows 10 predictive typing feature is disabled by default. You need to use a special tool called Mach2 to enable it . The Mach2 utility manages the Windows Feature Store where features can be toggled on or off. This tool contains thousands of Feature switches to turn on and off new functionality.
To turn on predictive typing on Windows 10, you need to download Mach2 from Github, and input the following Feature IDs:
Predictive Text On Computer
- HardwareKeyboardTextlntelligence 18624723
- HardwareKeyboardInlinePrediction 20367435
- HardwareKeyboardInlinePredictionForXAML 20371093
- HardwareKeyboardInlinePredictionForWin32 20805657
- HardwareKeyboardInlinePredictionOneKeyReversion 20805978
You can then use the following commands to turn each of these features on:
- mach2 enable 18624723
- mach2 enable 20367435
- mach2 enable 20371093
- mach2 enable 20805657
- mach2 enable 20805978
Once done, close the utility, restart your computer, and open Notepad or OneNote to see if the feature works.
Here’s a tip: When enabling features on Windows 10, it is recommended that you optimize your processes using Outbyte PC Repair to avoid snags and other issues. This tool also deletes junk files that might get in the way of your system’s smooth operation.
What Are the Benefits of Predictive Typing?
Predictive text features have been around for a long time and they come in different forms. Here are some of the advantages of using predictive typing on Windows 10:
1. Spelling and grammar errors will be minimized.
Some words are just difficult or confusing to spell out, such as courageous and instantaneous. With predictive typing, you don’t have to worry about whether the letter o comes before letter e. You’ll just need to type the first few letters and predictive typing will fill out the rest of the letters for you.
Predictive Text Pc
2. It is a form of assistive typing.
Some users may argue that this feature might contribute to the dumbing down of the next generation, but you can’t argue the benefits it brings to those who have problems spelling out words. For example, users who have dyslexia, visual impairment, or other conditions that impair the ability to type with the keyboard, will definitely find this feature a huge help.
3. This feature will improve productivity and efficiency.
Users will be able to type faster and better with the new inline text suggestions because they don’t have to watch out for mistakes all the time. Plus, they don’t have to type in the complete word, saving them from a lot of keystrokes. Predictive typing can save you a lot of time, especially if your work involves a lot of typing.
Summary
Free Predictive Software
The predictive typing on Windows 10 20H1 build is going to be a useful feature, not only for those who have trouble with spelling, but also for those who want to improve their typing speed and efficiency. The feature is set to be released with Windows 10 20H1 build next year, so Microsoft has a lot of time to work on the improvements of the feature.
Predictive Text Online
If you’re running into errors and your system is suspiciously slow, your computer needs some maintenance work. Download Outbyte PC Repair for Windows, Outbyte Antivirus for Windows, or Outbyte MacRepair for macOS to resolve common computer performance issues. Fix computer troubles by downloading the compatible tool for your device. See more information about Outbyte and uninstall instructions. Please review EULA and Privacy Policy Outbyte.