An electronic device and method are disclosed. The electronic device includes communication circuitry, a display, memory and a processor. The processor implements the method, including: establishing, by control of the processor, a communicative connection to an external device via the communication circuitry; receiving via the communicative connection, auto-complete text input information from the external device; storing, in the memory, the received auto-complete text input information, for usage with a keyboard process of the electronic device; and displaying, via a display, a recommended word, based on the stored auto-complete text input information, wherein the auto-complete text input information includes at least one of user data including complete words for recommendation as predictive text, generated from collecting and applying artificial-intelligence (AI) self-learning on words frequently utilized by a user, and user-defined text shortcuts configured by the user which associate an incomplete input with a completed word for usage as the predictive text.

Implementations set forth herein relate to providing selectable autofill suggestions, which correspond to application actions that are at least partially fulfilled using server command data—prior to a user selecting a particular selectable autofill suggestion. Proactively fulfilling command data in this way mitigates latency between user selection of a suggestion and fulfillment of a particular action. Initially, a partial input can be processed to generate autofill suggestions, which can be communicated to a server device for further processing. The autofill suggestions can also be rendered for selection at a touch display interface, thereby allowing a user to select one of the autofill suggestions. As command fulfillment data is provided by the server, the command fulfillment data can be available to a corresponding application(s) in order that any corresponding actions can be at least partially fulfilled prior to user selection.

A game controller includes a touchpad that a user, viewing a virtual keyboard on a screen, can soft-touch to move a cursor on the screen and then hard-touch to move the cursor and also send location data to a processor for inputting a letter from the virtual keyboard. Machine learning is used to predict a next letter or next word.

Methods and systems for predicting keystrokes using a neural network analyzing cumulative effects of a plurality of factors impacting the typing behavior of a user. The factors may include typing pattern, previous keystrokes, specifics of keyboard used for typing, and contextual parameters pertaining to a device displaying the keyboard and the user. A plurality of features may be extracted and fused to obtain a plurality of feature vectors. The plurality of feature vectors can be optimized and processed by the neural network to identify known features and learn unknown features that are impacting the typing behavior. Thereby, the neural network predicts keystrokes using the known and unknown features.

The present invention relates to an improved artificial neural network for predicting one or more next items in a sequence of items based on an input sequence item. The artificial neural network is implemented on an electronic device comprising a processor, and at least one input interface configured to receive one or more input sequence items, wherein the processor is configured to implement the artificial neural network and generate one or more predicted next items in a sequence of items using the artificial neural network by providing an input sequence item received at the at least one input interface and a side input as inputs to the artificial neural network, wherein the side input is configured to maintain a record of input sequence items received at the input interface.

A method and apparatus for a search function are provided in a touch-sensitive device that supports a search for contents in a list view by using a dedicated keypad displayed in the list view. In the method, the apparatus displays the dedicated keyboard for a content search in the list view, and performs the content search in the list view in response to an interaction inputted on the dedicated keyboard. The apparatus then displays at least one execution item associated with at least one found content, and executes the content associated with a selected one among the at least one execution item.

An electronic communications method includes receiving, by a device, electronic information. The electronic communications method further includes receiving, by the device, additional electronic information. A time period between receiving the electronic information and the additional electronic information is less than another time period between receiving the electronic information and the additional electronic information by using a standard keyboard.

A powered communication system comprises an improved layout of keys configured to treat, mitigate, or delay the onset and reduce the severity of symptoms of carpal tunnel syndrome (CTS) and other pathologies by reducing movement of a user's fingers during typing. A layout of the powered communication system comprises the most-used letters on a home or center row while retaining a plurality of keys in the same placement as the QWERTY keyboard. The powered communication system further comprises customizable function keys to further reduce finger movement and at least one sensor to monitor a user's health while typing.

An electronic device includes: a display; a memory storing an input pattern comprising a plurality of emojis; and a processor operatively connected to the display and the memory. The processor is configured to: display, in the display, a user interface comprising (i) an input field and (ii) a recommendation field comprising a plurality of recommendation areas; detect a first input that selects a first emoji from the plurality of emojis, the first emoji being displayed in a first recommendation area of the plurality of recommendation areas; output the first emoji to the input field based on the detected first input; and replace an item displayed in the first recommendation area with a second emoji subsequent to the first emoji in the input pattern.

Disclosed are techniques for extracting, identifying, and consuming imprecise temporal elements (“ITEs”). A user input may be received from a client device. A prediction may be generated of one or more time intervals to which the user input refers based upon an ITE model. The user input may be associated with the prediction, and provided to the client device.