Abstract: Technology is described for refining a language model for a language recognition system based on aggregating and analyzing word tag metadata from multiple users of the language. The technology allows a user to mark a word or phrase in a selected language (e.g., as offensive or misspelled, or as a part of speech or other category), combines information collected from multiple users of the selected language, and updates the user's language model based on the combined information from multiple users of the selected language.

Abstract: System and methods are provided for detecting numerical text strings within a text string and converting those numerical text strings into digit strings. The digit strings may be reflected in real-time, such as when the user is typing a text message. If more than one possible format of the digit string is determined, the system may then provide a selection of the various formats for selection. Once the proper format for the digit string is determined, that digit string may replace the numerical string previously detected in the text string. The text to digit conversion and associated formatting expedites user text entry such that the user is not required to switch keyboard views, (e.g., virtual keyboards). Additionally, converting to digit strings compresses message length, as well as provide other benefits.

Abstract: System and methods are provided for detecting numerical text strings within a text string and converting those numerical text strings into digit strings. The digit strings may be reflected in real-time, such as when the user is typing a text message. If more than one possible format of the digit string is determined, the system may then provide a selection of the various formats for selection. Once the proper format for the digit string is determined, that digit string may replace the numerical string previously detected in the text string. The text to digit conversion and associated formatting expedites user text entry such that the user is not required to switch keyboard views, (e.g., virtual keyboards). Additionally, converting to digit strings compresses message length, as well as provide other benefits.

Abstract: Technology is described for refining a language model for a language recognition system based on aggregating and analyzing word tag metadata from multiple users of the language. The technology allows a user to mark a word or phrase in a selected language (e.g., as offensive or misspelled, or as a part of speech or other category), combines information collected from multiple users of the selected language, and updates the user's language model based on the combined information from multiple users of the selected language.

Abstract: System and methods are provided for detecting numerical text strings within a text string and converting those numerical text strings into digit strings. The digit strings may be reflected in real-time, such as when the user is typing a text message. If more than one possible format of the digit string is determined, the system may then provide a selection of the various formats for selection. Once the proper format for the digit string is determined, that digit string may replace the numerical string previously detected in the text string. The text to digit conversion and associated formatting expedites user text entry such that the user is not required to switch keyboard views, (e.g., virtual keyboards). Additionally, converting to digit strings compresses message length, as well as provide other benefits.

Abstract: The present technology describes context based text input, which uses linguistic models based on conditional probabilities to provide meaningful word completion and modification suggestions, such as auto-capitalization, based on previously entered words. The technology may use previously entered left context words to modify a list of candidate words matching a current user input. The left context may include one or more previously input words followed by a space, hyphen, or another word. The technology may then modify the list of candidate words based on one or more conditional probabilities, where the conditional probabilities show a probability of a candidate list modification given a particular left context. The modifying may comprise reordering the list or modifying properties of words on the list such as capitalization. The technology may then display the modified list of candidate words to the user.