Tegic Communications, Inc.

Nuance Communications, Inc.

America Online, Inc.

Ethan Robert Bradford

David Jon Kay

Pim Van Meurs

Michael R Longe

James Stephanick

Michael R Longé

Christina James

Keith Charles Hullfish

Simon H Corston

Keith Trnka

Donni McCray

Clifford A Kushler

Edward Paul Flinchem

Richard Eyraud

Gaurav Tandon

Daiju Matsuo

Mark Evans Brighton

Erland Unruh

David Field

Wendy Bannister

Claes-Fredrik Mannby

Christopher Breske

Peter C Peddie

Lisa Nathan

Alex Robinson

Technology for improving the predictive accuracy of input word recognition on a device by dynamically updating the lexicon of recognized words based on the word choices made by similar users. The technology collects users' vocabulary choices (e.g., words that each user uses, or adds to or removes from a word recognition dictionary), associates users who make similar choices, aggregates related vocabulary choices, filters the words, and sends words identified as likely choices for that user to the user's device. Clusters may include, for example, users in a particular location (e.g., sets of people who use words such as 'Puyallup,' 'Gloucester,' or &#x201c;Waiheke&#x201d;), users with a particular professional or hobby vocabulary, or application-specific vocabulary (e.g., word choices in map searches or email messages).

Updating population language models based on changes made by user clusters

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.

Updating language databases using crowd-sourced input

The disclosed system provides an efficient method of using a later word or words entered after a previous word along with one or more language models that show which words are likely to occur together to identify a better disambiguated choice for the previous word. To identify the better disambiguated choice for the previous word, the system can evaluate the conditional probability for the later word of various candidate previous words, and select the candidate previous word that has the highest conditional probability. If the conditional probability of the selected candidate previous word exceeds that of the previous word that was entered by at least a factor, then the system can include the selected candidate previous word in a selection list for user selection. The disclosed system also provides an efficient method for using one or more language models and a later word to correct errors in segmenting the word.

Correction of previous words and other user text input errors

An operating sequence for a handheld computing device manages the device to automatically detect cues describing the device's environmental and user actions performed with the device, learn which cues and cue combinations are relevant to predict user actions, and then in response to occurrence of the relevant cues, predictively implementing the appropriate user action or configuring the device in anticipation of user action.

Contextual prediction of user words and user actions

The present invention relates to a method and apparatus for explicit filtering in ambiguous text entry. The invention provides embodiments including various explicit text entry methodologies, such as 2-key and long pressing. The invention also provides means for matching words in a database using build around methodology, stem locking methodology, word completion methodology, and n-gram searches.

Explicit character filtering of ambiguous text entry

An apparatus and method for providing visual indication of character ambiguity and ensuing reduction of such ambiguity during text entry are described. An application text entry field is presented in a display screen, into which the user enters text by means of a reduced keyboard and a disambiguating system. The default or most likely word construct for the current key sequence may be presented at the insertion point of the text entry field. An indication of ambiguity is presented in the display screen to communicate to the user the possible ambiguous characters associated with each key. A word choice list field may also be present to display at least one word construct matching the current key sequence.

Apparatus and method for providing visual indication of character ambiguity during text entry

In one general sense, information may be presented to a user by receiving one or more ambiguous characters that may be resolved to one of at least two disambiguated characters, exchanging at least one of the ambiguous characters with a host, receiving, from the host, results that reflect disambiguated terms related to the ambiguous characters exchanged with the host, rendering the results in a manner enabling the user to perceive which of the disambiguated terms will be used upon user selection of an aspect of the results, and enabling the user to select an aspect of the results to effect use of a corresponding one of the disambiguated terms.

Disambiguating ambiguous characters

A selective input system and method are provided which track the motion of a pointing device over a region or area. The pointing device can be a touchpad, a mouse, a pen, or any device capable of providing two or three-dimensional location. The region or area is preferably augmented with a printed or actual keyboard/pad. Alternatively, a representation of the location of the pointing device over a virtual keyboard/pad can be dynamically shown on an associated display. The system identifies selections of items or characters by detecting parameters of motion of the pointing device, such as length of motion, a change in direction, a change in velocity, and or a lack of motion at locations that correspond to features on the keyboard/pad. The input system is preferably coupled to a text disambiguation system such as a T9&#xae; or Sloppytype&#x2122; system, to improve the accuracy and usability of the input system.

System and apparatus for selectable input with a touch screen

A selective input system and associated method is provided which tracks the motion of a pointing device over a region or area. The pointing device can be a touchpad, a mouse, a pen, or any device capable of providing two or three-dimensional location. The region or area is preferably augmented with a printed or actual keyboard/pad. Alternatively, a representation of the location of the pointing device over a virtual keyboard/pad can be dynamically shown on an associated display. The system identifies selections of items or characters by detecting parameters of motion of the pointing device, such as length of motion, a change in direction, a change in velocity, and or a lack of motion at locations that correspond to features on the keyboard/pad. The input system is preferably coupled to a text disambiguation system such as a T9&#xae; or Sloppytype&#x2122; system, to improve the accuracy and usability of the input system.

Selective input system and process based on tracking of motion parameters of an input object

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Seattle, WA, United States of America

Ethan Robert Bradford