Apple Inc.

Brent D Ramerth

Jerome Rene Bellegarda

Xin Ru Wang

Stephen Olivier Lemay

Patrick L Coffman

Christopher Patrick Foss

Lawrence Yuan Yang

Richard R Dellinger

Gaurav Kapoor

Cyrus Daniel Irani

Alexandre F Carlhian

Giulia Maria Pagallo

Daniel C Gross

Michael R Siracusa

Thomas Deniau

Alexandre R Moha

Sofiane Toudji

Jannes G A Dolfing

Mathieu Jean Martel

Colin C Morris

Jason J Gauci

Karl Christian Kohlschuetter

Jun Hatori

Aria D Haghighi

Hafid J Arras

Kevin D Clark

Bronwyn A Jones

Douglas R Davidson

Jesper S Andersen

Jennifer Lauren Moore

Jesper A Andersen

Joshua H Shaffer

Devang Kalidas Naik

Bronwyn Anne Jones

Jannes G Dolfing

Xin Wang

Jia Pu

Bishal Barman

Hafid Arras

Andreas Eminidis

Jannes Ga Dolfing

Jannes GA Dolfing

Alexandre Carlhian

Mathieu J Martel

Guilia M Pagallo

Systems and methods for analysis and validation of language models trained using data that is unavailable or inaccessible are provided. One example method includes, at an electronic device with one or more processors and memory, obtaining a first set of data corresponding to one or more tokens predicted based on one or more previous tokens. The method determines a probability that the first set of data corresponds to a prediction generated by a first language model trained using a user privacy preserving training process. In accordance with a determination that the probability is within a predetermined range, the method determines that the one or more tokens correspond to a prediction associated with the user privacy preserving training process and outputs a predicted token sequence including the one or more tokens and the one or more previous tokens.

Analysis and validation of language models

Systems and methods for proactively identifying and surfacing relevant content on an electronic device with a touch-sensitive display are disclosed herein. In one aspect, a method includes presenting content in a first application. At least a portion of the content is presented without requiring input from a user. The method further includes receiving a request to open a second application. In response to receiving the request, the second application is presented with an input-receiving field. Before receiving any user input at the input-receiving field, a selectable user interface object is displayed with an indication that the portion of the content was viewed in the first application, allowing the user to paste at least the portion of the content into the input-receiving field. In response to detecting a selection of the selectable user interface object, the portion of the content is pasted into the input-receiving field.

Systems and methods for proactively identifying and surfacing relevant content on an electronic device with a touch-sensitive display

Systems and methods for proactively identifying and surfacing relevant content on an electronic device with a touch-sensitive display are disclosed herein. In one aspect, a method includes obtaining information identifying a first physical location viewed by a user in a first application. The method further includes detecting a first input. In response to detecting the first input: a second application is identified that is capable of accepting geographic location information; and an affordance is presented that is distinct from the first application, with a suggestion to open the second application. The suggestion includes information about the first physical location. The method further includes detecting a second input at the affordance. In response to detecting the second input at the affordance, the second application is opened and populated to include information that is based at least in part on the information identifying the first physical location.

Techniques to automatically correct or complete text are disclosed. An entered text and a context data indicating a context in which the entered text is used are received. Examples of context data include additional words and/or a phrase or sentence in which the entered text occurs. A replacement candidate to replace the entered text is determined based on the entered text and the context data.

Using parts-of-speech tagging and named entity recognition for spelling correction

Systems and methods for proactively identifying and surfacing relevant content are disclosed herein. An example method includes: detecting, via the touch-sensitive display, a search activation gesture from a user of the electronic device. The method also includes: in response to detecting only the search activation gesture, displaying a search interface on substantially all of the touch-sensitive display, the search interface including: (i) a search entry portion; and (ii) a predictions portion with one or more user interface objects each associated with a respective locally-installed application. Each respective locally-installed application is selected from among a plurality of locally-installed applications for inclusion in the predictions portion based on an application usage history associated with the user of the electronic device.

System and method for proactively identifying and surfacing relevant content on an electronic device with a touch-sensitive display

Systems and methods for proactively identifying and surfacing relevant content on an electronic device with a touch-sensitive display are disclosed herein. In one aspect, a method includes executing, on the device, an application in response to an instruction from a user of the electronic device. While executing the application, the method further includes collecting usage data. The usage data at least includes one or more actions performed by the user within the application. The method also includes: automatically, without human intervention, obtaining at least one trigger condition based on the collected usage data and associating the at least one trigger condition with a particular action of the one or more actions performed by the user within the application. Upon determining that the at least one trigger condition has been satisfied, the method includes providing an indication to the user that the particular action associated with the trigger condition is available.

Using a statistical language model to make information related to a word or other content of interest available is disclosed. An indication that a word or phrase is of interest is received. A contextual meta-information associated with the word or phrase of interest as used in context is used to make information related to the word or phrase of interest available, for example, by forming a more precise query and/or filtering search results based on the contextual meta-information.

Using statistical language models for contextual lookup

Systems and methods for proactively assisting users with accurately locating a parked vehicle are disclosed herein. An example method includes: automatically, and without instructions from a user: determining that a user of the electronic device is in a vehicle that has come to rest at a geographic location. Upon determining that the user has left the vehicle at the geographic location, the method includes automatically, and without instructions from a user: determining whether positioning information, retrieved from the location sensor to identify the geographic location, satisfies accuracy criteria. Upon determining that the positioning information does not satisfy the accuracy criteria, the method includes: providing a prompt to the user to input information about the geographic location. In response to providing the prompt, the method includes receiving information from the user about the geographic location and storing the information as vehicle location information.

Systems and methods for proactively identifying and surfacing relevant content on a touch-sensitive device

Systems and methods for proactively populating an application with information that was previously viewed by a user in a different application are disclosed herein. An example method includes: while displaying a first application, obtaining information identifying a first physical location viewed by a user in the first application. The method also includes exiting the first application and, after exiting the first application, receiving a request from the user to open a second application that is distinct from the first application. In response to receiving the request and in accordance with a determination that the second application is capable of accepting geographic location information, the method includes presenting the second application so that the second application is populated with information that is based at least in part on the information identifying the first physical location.

Systems and processes for predictive conversion of language input are provided. In one example process, text composed by a user can be obtained. Input comprising a sequence of symbols of a first symbolic system can be received from the user. Candidate word strings corresponding to the sequence of symbols can be determined. Each candidate word string can comprise two or more words of a second symbolic system. The candidate word strings can be ranked based on a probability of occurrence of each candidate word string in the obtained text. Based on the ranking, a portion of the candidate word strings can be displayed for selection by the user.

Predictive conversion of language input

Systems and processes for predictive text input are provided. In one example process, a text input can be received. The text input can be associated with an input context. A frequency of occurrence of an m-gram with respect to a subset of a corpus can be determined using a language model. The subset can be associated with a context. A weighting factor can be determined based on a degree of similarity between the input context and the context. A weighted probability of a predicted text given the text input can be determined based on the frequency of occurrence of the m-gram and the weighting factor. The m-gram can include at least one word in the text input and at least one word in the predicted text.

Predictive text input

Disambiguating multiple readings in language conversion is disclosed, including: receiving an input data to be converted into a set of characters comprising a symbolic representation of the input data in a target symbolic system; and using a language model that distinguishes between a first reading and a second reading of a character of the target symbolic system to determine a probability that the heteronymous character should be used to represent a corresponding portion of the input data.

Method for disambiguating multiple readings in language conversion

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San Francisco, CA, United States of America

Brent D Ramerth