Abstract: At an electronic device with a touch-sensitive display, display a message transcript, where the message transcript includes at least one message from at least a first user. Determine, based at least in-part on the at least one message, a plurality of suggested one or more characters. Display, on the touch-sensitive display, the plurality of suggested one or more characters. Detect an input on the touch-sensitive display. Determine whether the input represents user selection of one of the plurality of suggested one or more characters. Display the selected one of the plurality of suggested one or more characters in the message transcript. Send the selected one or more characters to the first user.

Abstract: At an electronic device with a touch-sensitive display, display a message transcript, where the message transcript includes at least one message from at least a first user. Determine, based at least in-part on the at least one message, a plurality of suggested one or more characters. Display, on the touch-sensitive display, the plurality of suggested one or more characters. Detect an input on the touch-sensitive display. Determine whether the input represents user selection of one of the plurality of suggested one or more characters. Display the selected one of the plurality of suggested one or more characters in the message transcript. Send the selected one or more characters to the first user.

Abstract: At an electronic device with a touch-sensitive display, display a message transcript, where the message transcript includes at least one message from at least a first user. Determine, based at least in-part on the at least one message, a plurality of suggested one or more characters. Display, on the touch-sensitive display, the plurality of suggested one or more characters. Detect an input on the touch-sensitive display. Determine whether the input represents user selection of one of the plurality of suggested one or more characters. Display the selected one of the plurality of suggested one or more characters in the message transcript. Send the selected one or more characters to the first user.

Abstract: Embodiments described herein enable data associated with a large plurality of users to be analyzed without compromising the privacy of the user data. In one embodiment, a user can opt-in to allow analysis of clear text of the user's emails. An analysis process can then be performed in which an analysis service receives clear text of an email of a client device; processes the clear text of the email into one or more tokens having one or more tags; enriches one or more tokens in the processed email using data associated with a user of the client device and the one or more tags; and processes the clear text and one or more enriched tokens to generate a data set of one or more feature vectors.

Abstract: Systems and methods for updating a language model are provided. One example method includes, at an electronic device with one or more processors and memory, training a first language model using a training data set comprising user-generated and user-relevant data, and storing a reference version of the first language model including a first overall probability distribution. Based on the reference version of the first language model, a second language model including a second overall probability distribution is updated (i.e., adapted) using the first overall probability distribution as a constraint on the second overall probability distribution.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In one example process, one or more input words can be received. The process can extract, based on the one or more input words, seed data for unsupervised training of a first learning network. Training data that includes a collection of words having typographical errors for the first learning network can be obtained. The process can determine, using the first learning network and based on the seed data and the training data, one or more output words having a probability distribution corresponding to a probability distribution of the training data. The one or more output words can include typographical errors. The process can generate, based on the determined one or more output words, a data set for supervised training of a second learning network. The second learning network can provide one or more typographical error suggestions.

Abstract: At an electronic device with a touch-sensitive display, display a message transcript, where the message transcript includes at least one message from at least a first user. Determine, based at least in-part on the at least one message, a plurality of suggested one or more characters. Display, on the touch-sensitive display, the plurality of suggested one or more characters. Detect an input on the touch-sensitive display. Determine whether the input represents user selection of one of the plurality of suggested one or more characters. Display the selected one of the plurality of suggested one or more characters in the message transcript. Send the selected one or more characters to the first user.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In one example process, one or more input words can be received. The process can extract, based on the one or more input words, seed data for unsupervised training of a first learning network. Training data that includes a collection of words having typographical errors for the first learning network can be obtained. The process can determine, using the first learning network and based on the seed data and the training data, one or more output words having a probability distribution corresponding to a probability distribution of the training data. The one or more output words can include typographical errors. The process can generate, based on the determined one or more output words, a data set for supervised training of a second learning network. The second learning network can provide one or more typographical error suggestions.

Abstract: Systems and processes for multilingual word prediction are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, identifying context information of the electronic device and generating, with the one or more processors, a plurality of candidate words based on the context information, wherein a first candidate word of the plurality of candidate words corresponds to a first language of a plurality of languages and a second candidate word of the plurality of candidate words corresponds to a second language of the plurality of languages different than the first language.

Abstract: Embodiments described herein enable data associated with a large plurality of users to be analyzed without compromising the privacy of the user data. In one embodiment, a user can opt-in to allow analysis of clear text of the user's emails. An analysis process can then be performed in which an analysis service receives clear text of an email of a client device; processes the clear text of the email into one or more tokens having one or more tags; enriches one or more tokens in the processed email using data associated with a user of the client device and the one or more tags; and processes the clear text and one or more enriched tokens to generate a data set of one or more feature vectors.

Abstract: Systems and processes for multilingual word prediction are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, identifying context information of the electronic device and generating, with the one or more processors, a plurality of candidate words based on the context information, wherein a first candidate word of the plurality of candidate words corresponds to a first language of a plurality of languages and a second candidate word of the plurality of candidate words corresponds to a second language of the plurality of languages different than the first language.

Abstract: At an electronic device with a touch-sensitive display, display a message transcript, where the message transcript includes at least one message from at least a first user. Determine, based at least in-part on the at least one message, a plurality of suggested one or more characters. Display, on the touch-sensitive display, the plurality of suggested one or more characters. Detect an input on the touch-sensitive display. Determine whether the input represents user selection of one of the plurality of suggested one or more characters. Display the selected one of the plurality of suggested one or more characters in the message transcript. Send the selected one or more characters to the first user.

Abstract: The present invention provides a search capability to allow a user to easily locate a menu command or other user interface element associated with a search result. In one embodiment, a user enters a search term (or a portion thereof) in a search field. A list of results is displayed, for example in a results menu. The user can select or highlight any of the listed results; in response, the corresponding command is brought into view in context within the user interface, and is highlighted. The user can activate the selected command directly from the search results menu.

Abstract: An apparatus for recognizing shapes characterized by a stroke grouper receptive to a plurality of strokes formed on a screen of a pen-based computer system; a shape recognition engine receptive to a stroke group produced by the stroke grouper; and a knowledge base coupled to the shape recognition engine, where the knowledge base includes, at a minimum, knowledge concerning closed polygons and closed curves. Preferably, the closed curves of the knowledge base include both circles and ellipses. A method for recognizing digitized shapes in a computer system includes the steps of receiving at least one user-initiated stroke; grouping the user-initiated stroke with related strokes to form a stroke group; and analyzing the stroke group to make a best-guess shape represented by the stroke group. Preferably, the method also looks for other shapes which are related to the best-guess shape and modifying at least one of the location, size, or shape of the best-guess shape to conform with the other shapes.

Abstract: A method for processing equations in a graphical computer system characterized by the steps of: receiving at least one unit comprising an equation which was derived from a graphical user input device; parsing the units into a parsed tree utilizing a constrained attribute grammar; and deriving a result of the equation utilizing the parsed tree. Preferably, the graphical user input device is a table or the screen of a pen-based computer system, where stroke units derived from strokes made by a stylus on the screen are passed to at least one recognition domain. The process preferably also includes the steps of: receiving at least one stroke unit comprising an edit to an equation on the screen; determining whether the edit changes the structure of the parsed tree of the equation; and editing the parsed tree if the edit does not change the structure of the parsed tree.

Abstract: An apparatus for recognizing shapes characterized by a stroke grouper receptive to a plurality of strokes formed on a screen of a pen-based computer system; a shape recognition engine receptive to a stroke group produced by the stroke grouper; and a knowledge base coupled to the shape recognition engine, where the knowledge base includes, at a minimum, knowledge concerning closed polygons and closed curves. Preferably, the closed curves of the knowledge base include both circles and ellipses. A method for recognizing digitized shapes in a computer system includes the steps of receiving at least one user-initiated stroke; grouping the user-initiated stroke with related strokes to form a stroke group; and analyzing the stroke group to make a best-guess shape represented by the stroke group. Preferably, the method also looks for other shapes which are related to the best-guess shape and modifying at least one of the location, size, or shape of the best-guess shape to conform with the other shapes.

Abstract: A pen-based system for reflowing handwritten ink objects is disclosed. The system divides the ink objects into paragraphs by identifying groups of ink objects separated from other groups by predefined distances. Each such paragraph is classified as either a graphics paragraph or a text paragraph; graphics paragraphs are formatted according to a graphics formatting protocol and text paragraphs are formatted according to a text formatting protocol. In addition, the system writes formatted paragraphs to destinations where they are displayed. The destination may be a screen on which the ink objects were originally written by a user and/or a printed page, a computer monitor, etc.

Abstract: A recognition system for a pen-based computer system characterized by: a tablet for inputting strokes from a stylus; a low-level recognizer responsive to the strokes and operative to perform low-level recognition on the strokes; a high-level recognizer responsive to at least some of the strokes and operative to perform high-level recognition on those strokes; and a recognition interface permitting communication between the recognizers and an application program. The high-level recognizer includes a controller capable of receiving units to be recognized; a number of recognition domains coupled to the controller, where each of the recognition domains can receive one or more units from the controller and is capable of providing an interpretation of the meaning of the one or more units to the controller; and an arbiter coupled to the controller which is capable of resolving conflicts between multiple interpretations developed by the recognition domains.

Abstract: A method for processing equations in a graphical computer system characterized by the steps of: receiving at least one unit comprising an equation which was derived from a graphical user input device; parsing the units into a parsed tree utilizing a constrained attribute grammar; and deriving a result of the equation utilizing the parsed tree. Preferably, the graphical user input device is a table or the screen of a pen-based computer system, where stroke units derived from strokes made by a stylus on the screen are passed to at least one recognition domain. The process preferably also includes the steps of: receiving at least one stroke unit comprising an edit to an equation on the screen; determining whether the edit changes the structure of the parsed tree of the equation; and editing the parsed tree if the edit does not change the structure of the parsed tree.

Abstract: An apparatus for recognizing shapes characterized by a stroke grouper receptive to a plurality of strokes formed on a screen of a pen-based computer system; a shape recognition engine receptive to a stroke group produced by the stroke grouper; and a knowledge base coupled to the shape recognition engine, where the knowledge base includes, at a minimum, knowledge concerning closed polygons and closed curves. Preferably, the closed curves of the knowledge base include both circles and ellipses. A method for recognizing digitized shapes in a computer system includes the steps of receiving at least one user-initiated stroke; grouping the user initiated stroke with related strokes to form a stroke group; and analyzing the stroke group to make a best-guess shape represented by the stroke group. Preferably, the method also looks for other shapes which are related to the best-guess shape and modifying at least one of the location, size, or shape of the best-guess shape to conform with the other shapes.