User Equipment (UE) Bimodal User Interface (UI)

This publication describes a user equipment (UE), such as a smartphone, that offers a user a bimodal user interface (UI) having an input mode and an output mode. The user may use various techniques to instruct the UE whether the UI needs to be in input mode or in output mode. As described herein, input mode refers to a user experience in which the user instructs the UE what to do, such as perform a computation, write an email, make a call, draw a figure, take notes, and other user-initiated activities. The UI in input mode silences and hides some or all calls, texts, and notifications from an operating system (OS) and various application software, unless the user specifically requests them, such as by tapping on a specific UI element. In addition, the UI in input mode creates shortcuts to certain OS and application software elements. On the other hand, as described herein, output mode refers to a user experience in which the UE instructs or notifies the user on what to do or what happened and fundamentally involves the user receiving information from other users, the operating system (OS), or various application software. The UI in output mode may offer the user the option to read email, read news, read posts from various social networking sites, browse the internet, read a list of bank transactions, receive calls, messages, and notifications, and other activities that involves the user receiving and consuming information. The bimodal UI in input mode or in output mode can help the user regain control of their user experience with the UE and can help the user better-manage their amount of time in front of the UE’s screen display

Automatic information protection when device camera is operated by secondary user

The techniques of this disclosure ensure user privacy when a user device with a camera is operated by a secondary user. Face detection and recognition are used, with user permission and consent, when a camera application of the device is in use. When it is detected that the device is being operated by a user other than the primary user, e.g., the device’s owner, enhanced security and/or privacy features are automatically enabled on the device. Using the techniques disclosed herein, faces within the viewfinder of a camera application are detected. If a face is recognized as that of the device owner while operating a rear camera of the device is in use, enhanced security and/or privacy features are enabled. Such features include filtering incoming system notifications, suppressing or obscuring other device or application alerts, limiting device usage to only the mobile camera application, etc

Providing link suggestions based on recent user activity

Web browsers typically include a navigation bar to enable users to enter URLs or search phrases. The browser often supplies suggestions to complete a URL or search-phrase when the user types a first few characters into the navigation bar. This disclosure provides techniques to provide link or URL suggestions based on text that was recently copied or highlighted by a consenting user. The text is classified into one or more types, e.g., geographical addresses, product categories, foreign language, etc., using a machine learning model. A map is established between text types and URLs associated with such types. When the user activates a navigation bar, e.g., by clicking on it or starting to enter characters, URL suggestions are offered that are based on the map. In this manner, recent context of the user is utilized to improve quality of suggestions or recommendations

Automatic context-based alerts for content sharing

This disclosure describes techniques for automatic detection of unintentional sharing of content. A user attempt to share content, e.g., from a clipboard via a paste operation, is detected. With user permission, the clipboard contents and the context in which the content is being shared are analyzed to determine suitability of the content to the context. An alert is provided to the user upon detection that sharing the content is likely unintentional

Adapting Ad Creative Text To Match A User\u27s Communication Style

A system and method for adapting the content of an ad-based on a user\u27s communication style is disclosed. The content adaptation may be performed on the user\u27s device or on a central server. On-device personalization can work best for mobile devices which are used as a primary means of communication. The method includes the steps of A) building a representation of the user’s communication style, B) when an advertisement is to be shown to the user, customizing the ad by rewriting it according to the user’s communication style and C) serving the optimized advertisement to the user. Building a representation of a user’s writing style may involve modelling using either statistics or a classifier e.g. a neural network. Prior to rendering, the user\u27s device would rewrite each of the ads, either by replacing words with synonyms or completely paraphrasing the ad to better match the user\u27s communication style

AUTOMATIC PLAYLIST CREATION FOR GROUP EVENTS

A playlist creation engine for automating the creation of a playlist which intelligently incorporates the interests, tastes, and preferences of every attendee of a group event which has indicated a preference to include their personalized consumption profiles based upon their consumption of media content through the content sharing platform is described. The playlist creation engine identifies a type of event and a group of users attending an event to provide the attending users with a request to build each user’s personalized consumption profile for use in generating a requested playlist. Playlist entries are determined from the personalized consumption profiles and combined into the playlist. The creation of the playlist optimizes the viewing appeal of the playlist for all users which agreed to share their personalized consumption profiles while making it transparent to the users which aspects of the users’ profiles are being shared

Automatic problem detection during audio or video call

Participants in an audio or video call over a network often face problems such as being unable to hear or see each other. With user permission, speech data from the call is automatically analyzed by a classifier to identify whether call participants are facing a problem. If a problem is identified, a message indicating a possible solution is provided, or if the call participant permits, automatic action is taken to fix the source of the problem. Users are provided with options to turn off the techniques

Automatic creation of photo albums from group conversations

Online photo sharing is a popular activity. However, users may share images via a photo sharing application or website, or via different messaging applications. When different users share photos with the same group via different mechanisms, the photos are not available to users in a single, convenient location. This disclosure describes a chat bot that can be invited to join a chat conversation conducted via different messaging applications. With user permission, the chat bot automatically retrieves images (photos and videos) shared in a messaging conversation and adds the images to a shared album or folder in a photo sharing application. Members of the conversation group are provided access to the shared album

Automatic annotations in communication applications

This disclosure describes techniques to insert hyperlinks into user communications (e.g., email, chat, etc.) that can provide a ready reference to other communications relevant to the context. With user permission, contents of email and chat messages are analyzed and classified according to the topics of the messages, e.g., with the use of a trained machine learning model. When a new message is received, it is analyzed and hyperlinks are automatically inserted that enable the user to navigate to other relevant messages