Relating to the field of artificial intelligence, and specifically relating to the field of natural language processing, a data processing method includes and an apparatus performs: determining original text samples, where masking processing is not performed on the original text samples; and performing mask processing on the original text samples to obtain mask training samples, where the mask processing makes mask proportions of the mask training samples unfixed, and the mask training samples each are used to train a pretrained language model PLM. Training the PLM by using the mask training samples whose mask proportions are unfixed can enhance mode diversity of the training samples of the PLM. Therefore, features learned by the PLM are also diversified, a generalization capability of the PLM can be improved, and a natural language understanding capability of the PLM obtained through training can be improved.

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.

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.

Systems, devices, media, and methods are presented for composing and sharing a message based on the motion of a handheld electronic device such as a ring. The methods in some implementations include presenting a keyboard on a display, collecting course data associated with a course traveled by the ring, and overlying a trace onto the keyboard, such that the trace is correlated in near real-time with the course traveled by the ring. In some implementations the display element is part of a portable device, such as the lens of an electronic eyewear device. Based on the course data relative to the key locations on the keyboard, the system identifies and presents candidate words to be included in a message.

Systems, devices, media, and methods are presented for composing and sharing a message based on the motion of a handheld electronic device such as a ring. The methods in some implementations include presenting a keyboard on a display, collecting course data associated with a course traveled by the ring, and overlying a trace onto the keyboard, such that the trace is correlated in near real-time with the course traveled by the ring. In some implementations the display element is part of a portable device, such as the lens of an electronic eyewear device. Based on the course data relative to the key locations on the keyboard, the system identifies and presents candidate words to be included in a message.

Methods, apparatuses, and computer program products are described herein that are configured to express a time in an output text. In some example embodiments, a method is provided that comprises identifying a time period to be described linguistically in an output text. The method of this embodiment may also include identifying a communicative context for the output text. The method of this embodiment may also include determining one or more temporal reference frames that are applicable to the time period and a domain defined by the communicative context. The method of this embodiment may also include generating a phrase specification that linguistically describes the time period based on the descriptor that is defined by a temporal reference frame of the one or more temporal reference frames. In some examples, the descriptor specifies a time window that is inclusive of at least a portion of the time period to be described linguistically.

Methods, apparatuses, and computer program products are described herein that are configured to express a time in an output text. In some example embodiments, a method is provided that comprises identifying a time period to be described linguistically in an output text. The method of this embodiment may also include identifying a communicative context for the output text. The method of this embodiment may also include determining one or more temporal reference frames that are applicable to the time period and a domain defined by the communicative context. The method of this embodiment may also include generating a phrase specification that linguistically describes the time period based on the descriptor that is defined by a temporal reference frame of the one or more temporal reference frames. In some examples, the descriptor specifies a time window that is inclusive of at least a portion of the time period to be described linguistically.

A document translation method includes: displaying a source text display region, a translated text region, and an editing region, wherein textual content in a document to be translated is displayed in the source text display region, and reference translated text for the textual content is displayed in the translated text region; and providing a translated text recommendation from the reference translated text according to input from a user within the editing region. The method further includes: displaying the translation recommendation in the editing area as a translation result, if a confirmation operation for the translation recommendation is detected; and receiving a translation inputted by the user that is different from the translation recommendation and displaying the translation inputted by the user in the editing area as the translation result, if a non-confirmation operation for the translation recommendation is detected.

In some embodiments, a method includes determining a position for a search query and a position for each audience record from multiple audience records in an embedding space. The method further includes receiving multiple device records, each associated with an audience record. The method further includes determining multiple keywords, each associated with an audience record and determining a position for each keyword in the embedding space. The method further includes calculating a first distance between the position of the search query in the embedding space and the position of each audience record in the embedding space. The method further includes calculating a second distance between the position of the search query in the embedding space and the position of each keyword in the embedding space. The method further includes ranking each audience record based on the first distance and the second distance.

In some embodiments, a method includes determining a position for a search query and a position for each audience record from multiple audience records in an embedding space. The method further includes receiving multiple device records, each associated with an audience record. The method further includes determining multiple keywords, each associated with an audience record and determining a position for each keyword in the embedding space. The method further includes calculating a first distance between the position of the search query in the embedding space and the position of each audience record in the embedding space. The method further includes calculating a second distance between the position of the search query in the embedding space and the position of each keyword in the embedding space. The method further includes ranking each audience record based on the first distance and the second distance.