48 results about "First language" patented technology

A computer-implemented method for transforming security advisories into targeted actionable mitigation strategies is provided. The method includes receiving a security advisory describing a vulnerability, processing the security advisory using a first language learning model (LLM) to extract vulnerability characteristics, generating an interaction model of sub-systems within a target system based on a topology of the target system, generating at least one actionable mitigation strategy for the vulnerability using a fine-tuned second LLM based on the extracted vulnerability characteristics and the interaction model, and outputting the actionable mitigation strategy as a security enhancement implementable on the target system. The method enables customized security enhancements for systems lacking official patches or manufacturer support.

Disclosed are a method and system for providing a speech conference service including an artificial intelligence-based speech interpretation function. According to one embodiment, the method for providing a video conference service may comprise the steps of: setting two or more interpretation bots participating as virtual participants in a video conference service; interpreting a speech of a first language input by participants of the video conference service into a speech of at least one other language different from the first language through processes of speech recognition, translation, and synthetic speech generation between the two or more interpretation bots and artificial intelligence; and providing the interpreted speech.

The application discloses a defect code generation method and related device, and the method comprises the steps of: obtaining at least one code segment pair from a code library; analyzing the modification reason between the first code segment before modification and the second code segment after modification in each code segment pair through a first language model, and identifying the defect type of the first code segment in each code segment pair indicating defect repair; obtaining at least one code segment pair corresponding to each defect type as a target code segment pair, and calling a second language model to learn each target code segment pair with the generation of defect code as a learning target to obtain a learned second language model; and generating a defect code segment corresponding to the target code segment through the learned second language model. The method can realize the automatic generation of defect code, improve the generation efficiency of defect code, improve the generation quality of defect code, and enhance the comprehensiveness and authenticity of the generated defect code.

This electronic device may comprise at least one processor. The at least one processor is configured to: while an application for providing an interpretation service for a call, which is performed by using a communication circuit, is executed, transmit uplink voice data of a first language generated on the basis of a user's utterance; determine a transmission time interval for transmitting uplink voice data of a second language on the basis of generating the uplink voice data of the second language from the utterance of the first language; determine transmission power for transmitting the uplink voice data of the second language on the basis of the transmission time interval for transmitting the uplink voice data of the second language; and transmit the uplink voice data of the second language on the basis of the transmission power.

A computer-implemented method: (A) receives product data identifying a product; (B) (B) receives patent data identifying a patent claim; (C) receives prior art data identifying a set of prior art, (D) executes an optimization process to minimize an objective function, the objective function including: a first sub-objective function and a second sub-objective function, the executing the optimization process comprising: (D)(1) generating a plurality of interpretations of the patent claim, (D)(2) for each particular interpretation in the plurality of interpretations of the patent claim: (D)(2)(a) using a first language model to evaluate the first sub-objective function with the product data and the particular interpretation as inputs to the first sub-objective function, (D)(2)(b) using a second language model to evaluate the second sub-objective function with the prior art data and the particular interpretation as inputs to the second sub-objective function.

Embodiments of the present disclosure disclose an audio synthesis method, device, equipment, computer readable medium and program product. A specific implementation of the method comprises: obtaining target audio corresponding to a first language and accent correction information corresponding to an audio synthesis scene, wherein the audio synthesis scene is a scene for synthesizing audio corresponding to a second language based on the target audio; extracting audio feature information corresponding to the target audio; and generating the synthesized audio corresponding to the second language by using a pre-trained speech synthesis large model according to the audio feature information and the accent correction information. The implementation is related to artificial intelligence, and by using the accent correction information, in the process of synthesizing the audio corresponding to the second language based on the target audio corresponding to the first language, the disturbance of the accent noise can be avoided, so that the synthesized audio without the accent noise can be accurately and efficiently generated.

We provide the system. [Solution] A means of supporting education using machine learning that enables two-way dialogue using a first language and a second language, A means for creating individual learning plans based on the user's native language and target language, A means of providing users with simulated dialogue using a virtual reality environment, A means of collecting and analyzing user learning progress information and providing real-time feedback, A means of displaying subtitles through the user interface to make the dialogue easier to understand, A means of using a robotic device that supports language learning through dialogue in daily life within a home environment, A system that includes means for analyzing a user's question using speech recognition and natural language processing technologies and generating appropriate linguistic expressions.

The application discloses a data processing method and device and a storage medium, wherein the data processing method comprises the following steps: obtaining first language structure data parsed based on a Proto description file, the first language structure data comprising a field in the Proto description file expressed in a first language and conversion limitation information between languages corresponding to a field type of the field in the Proto description file; calling a preset conversion function parsed based on the Proto description file; the preset conversion function representing a mapping relationship between languages determined based on the field type of the field in the Proto description file and the conversion limitation information between languages corresponding to the field type; converting the first language structure data into second language structure data according to the preset conversion function; and serializing the second language structure data to obtain Protobuf serialized data. The application can use Protobuf as a data exchange format of a protocol, can use shared memory in a service, and improves data transmission efficiency.

Embodiments are disclosed for preserving a vocal identity of an input audio sequence when translating speech audio. The method may include receiving an input audio sequence that includes speech audio having a source vocal identity in a first language. The method may further comprise translating a first transcription of the speech audio to a second transcription in a second language. Using the second transcription, initial translated speech audio having a default vocal identity is generated. The method may further comprise processing the initial translated speech audio to generate a translated content embedding and translated intonation data and processing the input audio sequence to generate a source speaker embedding representing the source vocal identity of the speech audio. The method may further comprise generating final translated speech audio with the source vocal identity in the second language, using the source speaker embedding, the translated content embedding, and the translated intonation data.

A prompt text including a list of a plurality of first language models each specialized for intention understanding in a plurality of predetermined domains and a content of the utterance is generated, the prompt text is input to a second language model, the first language model having a domain corresponding to the content of the utterance is identified based on the content of the response obtained from the second language model, and the content of the utterance is transferred to the identified first language model.

A method and system perform operations comprising: setting a first instruction tuning dataset comprising tasks in a first language; setting a second instruction tuning dataset comprising tasks in a second language; generating a first instruction, written in a same language as the first language, for the first instruction tuning dataset, and storing the first instruction for the first instruction tuning dataset; generating a second instruction, written in a same language as the second language, for the second instruction tuning dataset, and storing the first instruction for the first instruction tuning dataset; generating a cross-language instruction based on the first instruction tuning dataset, the first instruction for the first instruction tuning dataset, the second instruction tuning dataset, and the second instruction for the second instruction tuning dataset; and performing instruction tuning for an artificial intelligence model using the cross-language instruction.

This application provides an image forming apparatus, a document processing method, and an image forming system. The image forming apparatus includes: an acquisition module for acquiring a target document; a language detection module for detecting whether the language of the target document is a first language; an output module for outputting a prompt message when the language of the target document is not the first language, the prompt message indicating to the user whether to translate the target document; and an execution module for translating the language of the target document into the first language when the user selects to translate the target document. This application can automatically identify whether a user has a translation need and provide translation services to the user.

A table-type data analysis system, method, and program using a language model are disclosed. The method comprises the steps of: receiving a query and at least one table-type data, and converting the table-type data into at least one text-type data; inputting the query and the text-type data into a first language model to identify the text-type data corresponding to an analysis request included in the query and extracting the identified text-type data as analysis data; inputting the query and the analysis data into a second language model to generate an execution command for performing the analysis request; inputting the execution command into a third language model to convert the execution command into a code configured to perform the analysis request; and executing the code to output a data analysis result.

The application relates to the technical field of computers, in particular to a page construction method and device, electronic equipment and a storage medium, to improve the page construction efficiency. The method comprises the following steps: obtaining an original text set in a to-be-constructed page; in response to a language setting operation on the original text set, a language setting interface is presented, and each candidate language control is displayed in the language setting interface; in response to a selection operation on a target language control in each candidate language control, a target text set obtained by translating the original text set is acquired; and an application page corresponding to the target language is constructed based on the target text set and each target function component. In the application, after a target object selects a target language control, the original text set is translated into a target text set, and then an application page corresponding to a language other than the first language is obtained, so that the efficiency of constructing application pages in different languages can be effectively improved.

Various implementations include initiating, at a client device, a translation application for translation of a dialog session between a first user speaking in a first language and a second user speaking in a second language. In many implementations, the first language, spoken by the first user, can be determined based on one or more features of the client device. Additional or alternative implementations include determining a subset of candidate second languages from a plurality of languages available to the translation application. In a variety of implementations, the system can render output based on the subset of candidate second languages, and can process received input from the second user indicative of one or more of the candidate second languages in the subset of candidate second languages.

The application provides a logic scene generation method, device and equipment based on a large language model, relates to the technical field of automatic driving, and comprises the following steps: analyzing a target natural language corresponding to an automatic driving logic scene to be created to obtain a target label corresponding to the target natural language; finding a target use case matched with the target natural language from a scene use case library by using the target label; constructing a target prompt word according to the target use case and the target natural language; and inputting the target prompt word into a first language model to obtain the automatic driving logic scene. By using the logic scene generation method, device and equipment based on the large language model, the problem of low scene creation efficiency and long scene creation time during the creation of the automatic driving logic scene is solved.

The application discloses a speech processing method and a terminal device, and relates to the technical field of artificial intelligence. The terminal device acquires a speech segment in a speech stream. When a first speech segment in the acquired speech segment has first language expression content and corresponds to a first semantic, if the first semantic matches a target semantic, the terminal device performs speech enhancement processing on the first speech segment. When a second speech segment in the acquired speech segment has second language expression content and corresponds to a second semantic, if the second semantic matches the target semantic, the terminal device performs speech enhancement processing on the second speech segment. The first language expression content and the second language expression content are not completely identical.

Various embodiments of the present disclosure are directed to an inflight entertainment computer server. The IFE computer server includes at least one network interface, at least one processor connected to communicate through the at least one network interface with video display units and / or personal electronic devices, and at least one memory. The at least one memory including a language conversion module operative to translate an announcement including digitized speech and / or text from a first language to an available set of translated languages; a passenger preferred language module operative to identify a set of passenger preferred languages based on information obtained for passengers onboard the aircraft; and an announcement distribution module operative to receive the announcement in the first language generated by a crew member or by a controller, and process the announcement in the first language through the language conversion module to output a set of translated announcements.

An information processing apparatus includes a speech section extraction unit that extracts a speech section from each of speech data of a first language and speech data of a second language that is dubbed after video data; a correspondence relation detection unit that detects a correspondence relation between the speech section of the first language and the speech section of the second language; and a position adjustment unit that adjusts a position of the speech section of the second language for which the correspondence relation has been detected, based on the speech section of the first language.

A speech translation method using a multilingual text-to-speech synthesis model includes receiving input speech data of the first language and an articulatory feature of a speaker regarding the first language, converting the input speech data of the first language into a text of the first language, converting the text of the first language into a text of the second language, and generating output speech data for the text of the second language that simulates the speaker's speech by inputting the text of the second language and the articulatory feature of the speaker to a single artificial neural network text-to-speech synthesis model.

This generates a video that translates the speaker's utterance from the first language to the second language. [Solution] The conversion program enables the processor to implement: a speech voice acquisition function that acquires speech voice containing the speaker's utterances in their first language; a first language utterance text acquisition function that acquires first language utterance text, which is a text representation of the speaker's utterances in their first language, based on the speech voice; a second language utterance text translation function that translates the first language utterance text into second language utterance text; and a second language utterance voice output function that outputs speech voice containing the translated utterances based on the second language utterance text.

Provided are a mobile electronic device and a real-time call translation method thereof. The method is adapted to the mobile electronic device including a microphone, and the method includes the following steps. Environmental sound level is detected when initiating a voice call. A speech recognition parameter is determined based on the environmental sound level. Speech recognition processing is performed on a call voice signal received by the microphone according to the speech recognition parameter to obtain a dialogue text. The dialogue text corresponding to a first language is translated to generate a translated dialogue text corresponding to a second language. During the voice call, a function is executed based on the translated dialogue text.

An information processing apparatus, an information processing system, and an information processing method are provided. The cost of the device for providing voice guidance is reduced. The information processing apparatus performs: processing to provide voice guidance to a user using first voice data corresponding to a first language; determining if the user is using a language different from the first language; and, based on the result of the determination, obtaining second voice data corresponding to the language used by the user.

The invention relates to a method comprising: receiving a user input in a first language format; segmenting the user input into a plurality of input segments; retrieving, based on the user input, at least one specification among a set of specifications, wherein the specification is in a second language format and specifies a property of a technical entity; and mapping each input segment to at least one specification segment in the at least one specification.

A computer-implemented method for transforming security advisories into targeted actionable mitigation strategies is provided. The method includes receiving a security advisory describing a vulnerability, processing the security advisory using a first language learning model (LLM) to extract vulnerability characteristics, generating an interaction model of sub-systems within a target system based on a topology of the target system, generating at least one actionable mitigation strategy for the vulnerability using a fine-tuned second LLM based on the extracted vulnerability characteristics and the interaction model, and outputting the actionable mitigation strategy as a security enhancement implementable on the target system. The method enables customized security enhancements for systems lacking official patches or manufacturer support.