104 results about "Character (computing)" patented technology

Systems and methods for generating custom art fonts with consistent style include receiving user input that identifies a base font style for a custom font and includes descriptive text that defies one or more text effects to use for the custom font. Depth maps are selected for characters to be included in the custom font. The depth maps are preprocessed to add noise to the depth maps. A generative model generates custom font images conditioned with the text prompt and the depth maps. The custom font images are then used to render text on a display screen of a computing device.

Techniques and apparatuses for enhanced text suggestions are described. An example method includes detecting a user gesture performed by a user of the computing system based on data from one or more neuromuscular sensors and identifying a set of text characters corresponding to the user gesture. The method further includes causing display of the set of text terms in a user interface and determining whether a cognitive load of the user meets one or more criteria. The method also includes providing a text suggestion to the user based on the set of text characters in accordance with a determination that the cognitive load of the user meets the one or more criteria, and forgoing providing the text suggestion to the user based on the set of text characters, in accordance with a determination that the cognitive load of the user does not meet the one or more criteria.

Techniques and apparatuses for enhanced text suggestions are described. An example method includes detecting a user gesture performed by a user of the computing system based on data from one or more neuromuscular sensors and identifying a set of text characters corresponding to the user gesture. The method further includes causing display of the set of text terms in a user interface and determining whether a cognitive load of the user meets one or more criteria. The method also includes providing a text suggestion to the user based on the set of text characters in accordance with a determination that the cognitive load of the user meets the one or more criteria, and forgoing providing the text suggestion to the user based on the set of text characters, in accordance with a determination that the cognitive load of the user does not meet the one or more criteria.

Examples of the present disclosure describe systems and methods for automating the identification of events in a text file. In examples, a computing system identifies a subset of a text file that comprises an unknown event using a set of rules. Each rule of the set of rules specifying a first pattern of characters is compared to the subset of the first text file. When the set of rules does not identify the unknown event, the subset of the text file is provided to a language model to generate a new rule with a second pattern of characters and an identifier of the new rule. The system then generates an updated set of rules by adding the new rule to the set of rules.

The embodiment of the invention provides a character rendering size calculation method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining to-be-rendered text content; the text content comprises a plurality of to-be-rendered characters; each character to be rendered is configured with a rendering aspect ratio; the rendering aspect ratio of each to-be-rendered character represents the ratio between the character width and the character height of each to-be-rendered character after rendering; rendering a reference character in the current page environment; determining the rendering size of each to-be-rendered character in the current page environment according to the rendering aspect ratio corresponding to the reference character, the rendering size of the reference character in the current page environment and the rendering aspect ratio corresponding to each to-be-rendered character; the sum of the rendering sizes of all the to-be-rendered characters in the current page environment is determined as the actual rendering size of the text content, and through the method and device, the problems that in the related technology, due to the fact that a browser executes backflow and redrawing, computing resource consumption is large, and the page is stuck are solved.

Described herein is a system for providing access to a virtual assistant using a hidden element in source code of a document. The system can receive a request from a computing device to access a document, which has source code that includes a first set of characters embedded at its beginning. The first set of characters may only be accessible by an accessibility engine design to render data describing a document for individuals with visual impairments. When the accessibility engine parses the first set of characters, the computing device outputs content indicating that the individual can access the virtual assistant by performing an interaction. When the computing device detects the interaction, the computing device invokes the virtual assistant to guide the individual through the document.

The invention discloses a speech recognition error correction model training method, an electronic device, a medium and a program product, and relates to the technical field of speech recognition, and the speech recognition error correction model training method comprises the steps: obtaining a first training text, respectively inserting marks into character positions of a preset type of text in the first training text and the corresponding first real text through a preset large language model to obtain a second training text and a second real text; inputting the second training text into the initial speech recognition error correction model to obtain a prediction error correction text; a loss function value is calculated according to the prediction error correction text and the second real text, and the marked text is ignored in the calculation process of the loss function value; and performing iterative training on the initial speech recognition error correction model based on the second training text and the loss function value to obtain a target speech recognition error correction model. According to the technical scheme, the situation that the speech recognition error correction model wastes computing resources and time on errors which cannot be corrected is avoided, and the training efficiency is improved.

The embodiment of the invention discloses a multi-language text transcription method and system, and is applied to an AR device end, the method comprises the following steps: collecting first to-be-transcribed data of a user through the AR device end, and preprocessing the first to-be-transcribed data to obtain preprocessed to-be-transcribed data, the first to-be-transcribed data comprising voice data, visual data and action data; performing feature extraction on the first to-be-transcribed data to obtain first to-be-transcribed feature data, the first to-be-transcribed feature data including first voice feature data, first visual feature data and first action feature data; inputting the first voice feature data into a preset language recognition model, outputting preliminary target language data, and sending the first to-be-transcribed feature data and the preliminary target language data to an edge device end; and receiving the text transcription result, and displaying the text transcription result on the AR equipment end, so that the problem of insufficient computing resources of the AR equipment end can be effectively solved, and the transcription accuracy and reaction speed of the AR equipment end are improved.

The embodiment of the invention relates to a method for generating blessing texts, computing equipment and a storage medium. The method comprises the following steps: respectively generating a blessing label embedding vector and a blessing prompt embedding vector based on a blessing label and a blessing prompt input by a user; splicing the blessing label embedding vector and the blessing prompt word embedding vector to obtain a first embedding vector for generating a blessing text; through a constructed language model, extracting a relationship between segmented words in the first embedded vector so as to calculate an attention weight about the first embedded vector, the language model being constructed based on a multi-head attention mechanism; and calculating and outputting the text content of the next character in the to-be-generated blessing text based on the weight matrix, the blessing label embedding vector and the attention weight until the generation of the blessing text is completed. Therefore, the infectivity of the blessing text can be effectively improved, and the blessing text is more personalized.

The invention discloses a grammar error processing method and device, a cluster, a storage medium and a program product, and relates to the technical field of computers. By adding the processing flow after detecting that the grammar error exists in the database statement, the robustness and compatibility when the computing device analyzes the database statement are improved, a user does not need to modify a service code or completely shield a keyword in advance, so that the use threshold is reduced while the function of the database is ensured to be fully reserved. The method comprises the steps that after a first database statement is received, a target grammar unit in the first database statement is determined, when the target grammar unit is used as a keyword for grammar analysis, the target grammar unit does not conform to a first grammar rule, and the target grammar unit comprises one or more characters; and processing the target grammar unit, wherein the processed target grammar unit conforms to at least one grammar rule including the first grammar rule during subsequent grammar analysis.

The invention discloses a multi-modal document data processing method and system for large language model training, and the method comprises the steps: receiving a plurality of original documents in various formats, extracting the structure information of each original document, and recognizing a text region and an image region of each original document based on the structure information; performing optical character recognition on the text region and the image region by adopting a parallel OCR (Optical Character Recognition) engine based on GPU (Graphics Processing Unit) acceleration and heterogeneous calculation to generate recognition text data of the corresponding original document; performing multi-dimensional quality evaluation and cleaning on the recognition text data of each original document, and outputting normalized text data; and storing the standardized text data into a distributed knowledge base according to a predefined structure, and performing copyright and compliance test on the standardized text data. By adopting a parallel OCR recognition engine based on GPU acceleration and heterogeneous calculation, efficient and high-precision batch processing of multi-modal documents is realized, and the processing speed, the recognition accuracy and the data quality are improved.

A computing system may receive natural language audio input data. The computing system may automatically generate structured text data based on the natural language audio input data. The computing system may receive text input from an automatic speech recognizer or an input device providing for entry of typed characters. A machine learning model executing on the computing system may identify, based on the structured text data, one or more changes to be made to the text input. The machine learning model may include one or more of a statistical language model and a large language model. The machine learning model may generate, based on the one or more changes to be made to the text input, one or more proposed changes to the text input. The computing system may output the one or more proposed changes to the text input.

The invention relates to the technical field of computers, and discloses a database character string comparison method and device, electronic equipment and a storage medium. The method comprises the following steps: analyzing a received character string comparison request to obtain a first character string to be compared; acquiring a corresponding second character string from a target database according to the character string comparison request; converting the first character string into a first numerical value corresponding to a preset data system, and converting the second character string into a second numerical value corresponding to the preset data system; and comparing whether the first numerical value and the second numerical value are the same or not, and setting a comparison result as a return result of the character string comparison request, so that consumption and occupation of system computing resources are reduced, and the efficiency of database character string comparison is improved.

A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing characters of a font present in an electronic communication. The data includes an integer code for each character of the font. Operations also include applying an operator to the integer code of each character of the font to produce an encrypted integer code. The respective character of the font is assigned to the encrypted integer code. Operations also include sending an encrypted font file comprising data representing each character of the font and the respective encrypted integer code, the encrypted font file being sent to one or more recipient computing devices for rendering the electronic communication using the encrypted font file.

Provided in the embodiments of the present disclosure are a data compression method, a data decompression method, a computing device, a computer storage medium and a computer program product. The data compression method comprises: determining data to be compressed that has been subjected to character coding according to a unicode coding format; according to a byte order, reading character data from the data to be compressed, and determining a first dictionary or a second dictionary hit by the character data; searching for a coding sub-space corresponding to the first dictionary or the second dictionary, and determining coded values, in corresponding coding sub-spaces, of dictionary data hit by the character data, so as to obtain a coded-value set corresponding to the data to be compressed; and on the basis of the coded-value set and the first dictionary, obtaining compressed data.

A method for constructing a fault knowledge graph. The method comprises: after a sentence to be processed is acquired according to fault discrimination text, determining protocol signaling and an atomic flow of said sentence from an atomic flow chart according to a signaling character string of said sentence; after an atomic flow clause is generated according to the atomic flow and said sentence, determining a logic expression corresponding to the atomic flow clause; generating a logic expression of said sentence according to the logic expression of the atomic flow clause; then generating a logic expression of the fault discrimination text according to the logic expression of said sentence; and adding the logic expression of the fault discrimination text to a fault knowledge graph. By means of the method, corresponding protocol signaling and a corresponding atomic flow can be searched for in an atomic flow chart according to a signaling character string of fault discrimination text, such that the accuracy of identifying the signaling can be improved, and the success rate of converting the fault discrimination text into a logic expression is improved. Further provided in the present application is a computing apparatus capable of implementing the method.

The embodiment of the invention provides a data compression method, a data decompression method, computing equipment, a computer storage medium and a computer program product. The data compression method comprises the following steps: determining to-be-compressed data subjected to character coding according to a unified code coding format; reading character data from the to-be-compressed data according to a byte sequence, and determining a first dictionary or a second dictionary hit by the character data; searching coding subspaces respectively corresponding to the first dictionary or the second dictionary, and determining coding numerical values of dictionary data hit by the character data in the corresponding coding subspaces to obtain a coding numerical value group corresponding to the data to be compressed; and obtaining compressed data based on the coding numerical value group and the first dictionary. According to the technical scheme provided by the embodiment of the invention, the compression rate and the compression speed of data compression are ensured, and the compression performance is improved.

The present disclosure offers an improved user interface for selecting and entering special characters in digital text, among other capabilities. When a character key is press and held, a related special character is displayed at a text cursor or input insertion point, replacing the previously displayed keyboard character. When the key remains held down, other related special characters are automatically cycled in a continuous loop until the key is released. Display of special characters are prioritized based on various criteria, including usage history and contextual factors. This enhances typing efficiency by reducing the number of keystrokes and / or mouse movements conventionally required, thus simplifying the input of special characters. It is particularly useful for multilingual users and those requiring access to special characters. The system is adaptive, learning from user behavior to improve accuracy and relevance over time.

An example method includes outputting a graphical user interface including: a graphical keyboard comprising a plurality of character keys, the plurality of character keys including two to eight character keys; a text-editing region; and a word-suggestion region. The method also includes detecting a first user input at a location of the presence-sensitive display associated with a particular character key from the plurality of character keys. The method further includes, responsive to detecting the first user input, determining a first character associated with the particular character key. The method additionally includes outputting the first character for display within the text-editing region and a set of suggested words for display within the word-suggestion region. The method also includes, responsive to receiving a transition input via an input device of the computing device, transitioning a focus region from a location of the text-editing region to a location of the word-suggestion region.

The embodiments of the present disclosure disclose a method and device for character positioning. A specific implementation of the method includes: acquiring a target image; performing text line detection on the target image to obtain text line position information of the text line in the target image; performing character recognition on the image area in the target image located at the position indicated by the text line position information to obtain a character sequence included in the text line; and generating character position information of the characters in the text line based on the character sequence. This implementation determines the position of characters through text line detection and character recognition, which can improve the speed of single character positioning, reduce the amount of calculation for single character positioning, and reduce the consumption of computing resources during the positioning process.

The invention provides a training method and device of a synonymous character generation model and computing equipment, and belongs to the technical field of artificial intelligence. According to the training method of the synonymous character generation model provided by the invention, the synonymous character generation model is pre-trained in an unsupervised training mode based on the sensitive word data set, so that the synonymous character generation model can learn the association rules of the characters in the sensitive words, and therefore, after doping, the sensitivity of the sensitive words can be improved. Whether the semantics of the sensitive words is changed or not is judged according to the association rules of the words in the sensitive words, and then a synonym generation model obtained through pre-training is trained in a supervised training mode on the basis of the labeled doped corpus, so that the synonym generation model can learn the rules of doping the characters into the sensitive words; according to the method, the model can obtain synonymous characters doped with other characters, and the synonymous characters and sensitive words have the same semantics, so that the obtained synonymous characters are more comprehensive, and the efficiency of obtaining the synonymous characters is improved.

This invention discloses a method, system, and device for text segmentation highlighting based on speech character position mapping, applied in the field of data processing technology. It achieves text segmentation highlighting through scrolling character position mapping. First, the text content, scrolling sequence, speed, and font layout are preprocessed and uniformly converted into character coordinates and progress percentage format. Character indices and highlight intervals are extracted through position mapping and segmentation detection to form display baseline information. Based on the scrolling-driven calculation module, text features are modulated and non-viewport content is filtered. A highlighting following effect is generated after pixel restoration and synchronization calibration. The highlighting module is directly connected to a fixed-logic prompting engine, and synchronization calibration of scrolling and chapter modes is only performed at the front-end mapping layer, achieving parameter optimization. Seamless adaptation of the rendering framework is achieved through dimensional alignment. Using the prompting engine as a timing discriminator, a complete technical solution for low-computing-power, high-precision, and pluggable scrolling text synchronization and segmentation highlighting is ultimately formed.

The invention discloses a file comparison method and device, electronic equipment and a storage medium, and belongs to the technical field of text processing, in the method, a computing node receives a first text block and a second text block sent by a control node, and the block division order of the first text block in a first file is the same as the block division order of the second text block in a second file; carrying out similarities and differences labeling on characters in the first text block and the second text block, and carrying out iterative calculation on resource consumption conditions of the first text block and the second text block under different character comparison paths according to similarities and differences labeling results and a resource consumption iteration rule during character comparison, according to an iterative calculation result and character comparison rules corresponding to different path backtracking modes, a block comparison result is determined, the block comparison result comprises character modification operation performed when the first text block is updated into the second text block, the block comparison result is sent to a control node, and the control node controls the second text block according to the block comparison result. And determining a file comparison result of the first file and the second file.

A method and a computing device for displaying patent text based on large language model output, wherein the method is performed by the computing device, and the method comprises receiving patent text output by a large language model, wherein the patent text comprises at least one placeholder, each placeholder comprises a general symbol and symbol information, and the symbol information corresponds to a special symbol, backfilling the special symbol having a mapping relationship with the placeholder at the position of the placeholder in the patent text, and displaying the backfilled patent text. The method can realize accurate display of formulas, chemical equations and other special characters.

One embodiment provides a computer-implemented method that includes comparing, by a computing device, an input character signal with one or more prestored character templates for determining an estimated difference measure. The computing device, based on the estimated difference measure, determines one or more mixing weights between a stored character patch buffer and a current input character patch for determining an output mixing patch. The computing device further updates the character patch buffer based on the output mixing patch. The computing device additionally substitutes a designated area using the output mixing patch to produce a final output.

The invention relates to a system (1) for recognizing online handwriting, comprising: - a handwriting instrument (2) comprising a main body (3) extending longitudinally between a first end (4) and a second end (5), the first end (4) having a writing tip (6) capable of writing on a support, the handwriting instrument (2) further comprising a module (17) comprising at least one movement sensor (7) configured to acquire movement data relating to the user's handwriting as the user is writing a sequence of characters using the handwriting instrument (2), - a computing unit (8) in communication with the at least one movement sensor (7) and configured to analyze the movement data by means of a machine learning model trained in a multitask manner so that it is capable of simultaneously performing at least two tasks, the machine learning model being configured to deliver as output the sequence of characters written by the user using the handwriting instrument.

In one disclosed method, a computing system determines, on a first occasion, that a first user typed a first sequence of characters including at least a first character followed by a second character, and determines first data that is based at least in part on a first time interval between first and second interactions by the first user with a keyboard while typing the first character and the second character within the first sequence of characters. On a second occasion, the computing system determines that a person typed a second, different sequence of characters including at least the first character followed by the second character, determines second data that is based at least in part on a second time interval between third and fourth interactions by the person with a keyboard while typing the first character and the second character within the second sequence of characters, and determines that the person is the first user based at least in part on the first data and the second data.

The present application provides a method and system for intelligent government affairs processing based on a large model and process robot technology. By obtaining the original government affairs text to be processed; loading the original government affairs text into a large natural language model, obtaining key information detection results, the key information detection results include the key information coverage window identified in the original government affairs text, the key information core characters, the information classification corresponding to the key information characters, and the classification confidence corresponding to the information classification. The debugging process of the large natural language model includes debugging each branch component separately, and then further multi-task learning; generating a target government affairs text based on the key information detection results and the original government affairs text. The present application can achieve the effect of key information detection using only one large natural language model, while ensuring the accuracy of detection, reducing the model's dependence on computing power.

A method for encryption and decryption of files or email messages text, is disclosed that involves loading a p-text file for encryption into a computing device, determining if total bit number of said file is divisible by six and adding any necessary bits to result in bit number divisible by six, combining the bit sequence with a matching number of pad bits using an XOR additive cipher resulting in a modified file, converting said modified file to C-text, six bits a time, using a conversion table, rearranging the c text sequence using Prime Set Permutation. inserting a PSP lock character into the sequence, inserting pad pointer sequence characters into said sequence and displaying the file name saved.

The invention belongs to the technical field of digital image processing and ancient text information processing, particularly relates to an automatic oracle annotation method, system and equipment for digital literatures, and aims to solve the problem of automatic identification and annotation of oracle and Chinese character mixed literatures. The method comprises the following steps: receiving a document image, and obtaining respective coordinate areas of a plurality of characters in the image; obtaining each character image according to the coordinate area, and classifying the character images into an oracle character type or a non-oracle character type; performing differentiation recognition based on a classification result, determining codes of the oracle characters by adopting an image matching model, and determining texts of the non-oracle characters by adopting a character recognition model; and finally, associating an identification result with the coordinate region to generate a structured annotation file. According to the method, the technical bottlenecks of failure of a general OCR (Optical Character Recognition) technology, poor adaptability of a complex format and high computing power dependence are solved, and high-precision and automatic labeling of the oracle in the mixed literature in a low computing power environment is realized.