20results about How to "Improve translation" patented technology

According to the method for constructing the efficient sign language translation system based on deep learning, the accuracy and efficiency of sign language translation are remarkably improved through improvement in the aspects of data enhancement and preprocessing, model architecture optimization, real-time translation and interaction, system robustness and adaptability and the like. Through the application of the multi-modal deep learning model and in combination with the computer vision and natural language processing technology, the sign language can be better understood and translated, and diversified communication requirements of users are met. In addition, due to the self-adaptive learning ability and the multi-language support function of the system, the system can be continuously optimized and adapt to the requirements of different users, and the system has wide application prospects and social value.

The invention discloses a context translation processing method and device based on a large model, and intelligent equipment, and the method comprises the steps: obtaining voice information needing to be translated, and obtaining scene information corresponding to the voice information; inputting the processed voice information and the corresponding scene information into a pre-trained scene-based translation model, and outputting translation content corresponding to the scene; wherein the pre-trained training step based on the scene translation model comprises the following steps: collecting and acquiring different videos as training data; analyzing a frame-by-frame page, obtaining a subtitle file, and understanding a plot scene of each video according to video plot description and comment content; and based on the plot scene of each video, in combination with the frame-by-frame page of the video and the corresponding subtitle file, analyzing the corresponding translation content, and training the scene translation model to obtain a pre-trained scene-based translation model. The translation of the method is not only simple character translation, but also can be performed according to the scene in combination with the corresponding context, so that the translation is more accurate, and the translation effect is better.

The embodiment of the invention discloses a model training method and device, electronic equipment, a medium and a program product, which can be applied to various scenes such as cloud technology, artificial intelligence, intelligent traffic, auxiliary driving and the like. According to the embodiment of the invention, a training sample set is obtained, wherein the training sample set comprises an initial sample text corresponding to an initial scene and a newly-added sample text corresponding to a newly-added scene; translating the initial sample text through a teacher model to obtain a teacher translation result; translating the initial sample text and the newly added sample text through an initial student model to obtain a student translation result; calculating a loss value by combining the teacher translation result and the student translation result; and on the basis of the loss value, updating model parameters of the initial student model to obtain a trained student model, so that the trained student model is used for translating the to-be-translated text corresponding to the initial scene and the newly-added scene. Therefore, according to the scheme, the multi-scene adaptive capacity of the model can be enhanced while the model training efficiency is improved.

The invention relates to the technical field of language neural machine translation, and discloses a method for performing multi-language neural machine translation in a resource-constrained environment, which comprises the following steps of: firstly, reducing the model size and the operation complexity by adopting a model compression technology and technologies such as quantification, pruning and knowledge distillation; the system can run on low-power-consumption equipment; then, a network structure shared by multiple languages is designed, and by designing a neural network structure capable of processing multiple languages at the same time and by sharing an encoder and a decoder, the parameter quantity of the model is reduced, and the translation efficiency is improved. Neural machine translation becomes a preferred technology due to translation quality and efficiency, traditional NMT models usually need a large number of computing resources, application of the traditional NMT models in resource limited environments (such as mobile equipment and Internet of Things equipment) is limited, and certain limitation exists when the traditional NMT models are used.

The present invention relates to a polynucleotide, containing a translated region from a start codon to a stop codon, a 5' untranslated region, and a poly A chain, in which 65% or more of nucleotides contained in the poly A chain are sugar modified nucleotides.

The present disclosure relates to the field of biotechnology, and in particular to a 5'UTR sequence for promoting mRNA translation and its use. The present disclosure provides a 5'UTR sequence, which comprises a nucleotide sequence shown in any one of SEQ ID NO:1-6 or its complementary sequence, or a nucleotide sequence having at least 80% homology with a nucleotide sequence shown in any one of SEQ ID NO:1-6 or its complementary sequence. The present disclosure provides a new RNA molecule design scheme, which achieves the advantage of optimized translation by rationally optimizing the nucleic acid sequence of the functional region, so that the RNA molecule has a wide range of application prospects in the fields of gene therapy, vaccine development, etc.

The invention provides a preparation method and application of circular RNA, the ring opening rate of the circular RNA is reduced through preparation of the circular RNA, the loss of the circular RNA is reduced, meanwhile, the purity of a product is improved, and RNA molecules after in-vitro cyclization can be effectively transfected into cells. The invention also provides a preparation method and application of the circular RNA. In some embodiments, compared with existing RNA cyclization methods, the method provided by the invention has the advantages that the product purity is improved, and the ring opening efficiency is reduced.

The invention discloses a multi-scene adaptive sign language translator and a control method thereof. The multi-scene adaptive sign language translator comprises a base, a rotating mechanism is mounted at the top of the base, a lifting mechanism is mounted at the top of the rotating mechanism, and a translation mechanism capable of capturing in multiple directions is mounted at the top of the lifting mechanism. While the monitoring probe is used for shooting, the position of a sign language person can be monitored in real time through the infrared sensor, a monitored sensing signal is transmitted to the PLC of the control module, the servo motor is controlled to operate through the PLC, and therefore the rotating seat can be driven to rotate in the circumferential direction, the shooting angle of the monitoring probe can be adjusted, and the shooting accuracy of the sign language person is improved. Meanwhile, a first forward and reverse rotation motor can be controlled to operate through a PLC, the first forward and reverse rotation motor drives a threaded column to rotate, and a lifting cylinder can be driven to perform lifting adjustment under the action of threads of a threaded sleeve, so that the camera shooting height of the monitoring probe can be adjusted, and then the camera shooting device can be suitable for multi-scene camera shooting.

The invention discloses an error-correction improved translation big data integration method, which belongs to the field of translation technology. The method performs multiple sentence segmentation and numbering on the document, translates and integrates it, and finally performs modification and feedback. The above method performs error correction and feedback processing on the translation result, thereby ensuring the accuracy of the translation. At the same time, during the modification process, the results of the machine-converted translation content will be included in the cloud as a reference for the next translation, thereby improving the learning ability of the system and further improving the effect of machine translation.

The invention discloses a binary quantization translation model generation method, a machine translation method and related equipment, and the generation method comprises the steps: collecting sample data of multiple languages, and constructing a plurality of bilingual sentence pairs according to the sample data of the multiple languages, each bilingual sentence pair comprising two mutually translated sentence texts; the bilingual sentence pairs serve as training samples, a pre-trained original translation model and a pre-trained compression translation model are trained through knowledge distillation, and the compression translation model is obtained by conducting binary quantization processing on the original translation model; and taking the trained compression translation model as a binary quantization translation model capable of being deployed to edge equipment, wherein the binary quantization translation model is used for converting a given source language statement into a target language statement. The scale of the translation model is effectively reduced through binary quantization, the model is trained through knowledge distillation, and the binary quantization translation model which can adapt to edge equipment configuration and is good in translation performance is obtained, so that the translation model can be successfully deployed at an edge computing end, and the translation efficiency is improved.

The invention relates to a text translation method and system based on granular ball clustering. The method comprises the following steps: regularly acquiring a text data set by adopting a crawler technology and preprocessing the text data set; performing word segmentation processing on the obtained text data by utilizing a word segmentation tool, and updating a word bank by utilizing words obtained by the word segmentation processing; on the basis of a pre-trained large language model, coding words in the word bank to obtain word vector representation of the words; according to the word vector representation of the words in the word bank, adaptively generating a synonym set of the words in the word bank by using a granular ball clustering algorithm; using synonyms of words in the training text to replace the words to generate adversarial samples of the training text; constructing a training set according to the training text and the adversarial sample, and training a text translation model based on a large language model based on the constructed training set; and translating the to-be-translated text through the trained text translation model. According to the invention, the accuracy and reliability of translation can be improved.

This invention discloses the application of cotton uORF elements G1u2 and G1u3 in improving gene translation levels, belonging to the field of genetic engineering. This invention utilizes upland cotton... WNK Gene Ghir_D04G003230 Two uORF elements, G1u2 (SEQ ID No. 2) and G1u3 (SEQ ID No. 3), were isolated from cotton. A dual-luciferase reporter assay demonstrated that both G1u2 and G1u3 elements significantly improved the translation efficiency of downstream genes. This invention is the first to discover uORF elements in cotton with a clear positive translation regulatory function, filling a gap in the research and application of positive uORF regulatory elements in cotton. Furthermore, these uORF elements can be applied to molecular design breeding for high-yield, stress-resistant, and high-quality plants, as well as precise gene editing, demonstrating strong practicality.

The application provides a system and method for automatically translating sign language and language into text, and relates to the technical field of sign language translation. The system for automatically translating sign language and language into text comprises a voice capturing module, a text capturing module, a sign language capturing module, a voice recognition module, a text recognition module, a sign language recognition module, a data processing module, a sign language translation and text translation module, a deep learning and model training module, a user interface, and a real-time interaction module. In the application, computer technology, artificial intelligence and machine learning are used to automatically convert between sign language, voice and text, which helps the deaf and hearing-impaired people to communicate with others in daily life, breaks the communication barrier, and achieves better translation effect, so that the communication between the hearing-impaired people and the hearing people is more smooth, and the hearing-impaired people no longer need to rely on limited sign language interpreters, which greatly improves the communication efficiency and convenience.

The utility model provides a kind of plastic bag production line flattening folding mechanism, belong to plastic bag production technical field.This kind of plastic bag production line flattening folding mechanism includes frame and folding adjusting mechanism, the left side of the top of frame outside is equipped with plate body, the inside of plate body is equipped with roll body, folding frame is movably connected in the bottom of frame inside, the top of folding frame inside and the inside of plate body are movably connected with folding plate by shaft rod, screw is movably connected in the bottom of folding plate inside by shaft pin, screw surface is connected with screw seat by setting folding adjusting mechanism, can be folded in guiding to outside plastic bag simultaneously, for user provides the medium of adjusting folding guide angle according to outside plastic bag size, so that user carries out folding guide adjustment operation according to the actual size of outside plastic bag, thus improve the operation convenience and adaptability of frame flattening folding.

The present invention relates to the technical field of machine translation, and in particular to a machine translation model training method and system based on parameter pruning and tuning. Specifically, it includes: obtaining an incremental data set, an original machine translation model and a pseudo target language data set; obtaining a fine-tuning data set, and using the incremental data set to build an incremental model; building a pruned model, including evaluating the importance of each parameter in the FFN layer of the original machine translation model and the incremental model, replacing the parameters in the FFN layer of the incremental model that are not important for incremental language translation but important for original language translation with the corresponding parameters in the FFN layer of the original model; building a four-tuple fine-tuning data set; using the four-tuple fine-tuning data set to fine-tune the FFN layer of the pruned model using an optimized CPO algorithm to obtain a new model after parameter pruning and tuning. The training method of the present invention can not only have the ability to learn new translation directions, but also effectively retain the translation performance of the original translation direction, and has good continuous learning ability.

The invention discloses a simplified English checking method based on ASD-STE100 ISSUE 8, and belongs to the technical field of English checking, and the simplified English checking method based on ASD-STE100 ISSUE 8 comprises the following steps: S1, creating a project, S2, creating a detection text, S3, detecting the text, S4, providing a management function of a simplified English dictionary, and S5, managing a historical text. According to the simplified English checking method based on the ASD-STE100 ISSUE 8, rules of the ASD-STE100 ISSUE 8 are further deepened through an algorithm and artificial intelligence, systematic detection of part of the rules is achieved, the efficiency is improved for users and enterprises who write practical scientific and technological English and need to follow the simplified English rules of the ASD-STE100 ISSUE 8, the use manual of non-native English language persons is more comprehensive, and the user experience is improved. And better conditions are created for human and machine translation.

The utility model relates to the technical field of die design, and discloses a cylinder gasket steel ring cold extrusion die which comprises an upper die and a lower die, the lower die is located below the upper die, an upper top plate is arranged at the top of the upper die, a lower bottom plate is arranged at the bottom of the lower die, and a plurality of vertically-arranged guide columns are distributed on the top of the lower bottom plate in the circumferential direction of the outer ring of the lower die. Through holes allowing the guide columns to penetrate through are formed in the upper top plate in the vertical direction and correspond to the guide columns, a containing annular groove is formed in the lower die and corresponds to the steel ring, and a plurality of guide grooves are formed between the lower die and the lower bottom plate in a vertically communicating mode and distributed in the circumferential direction of the inner ring of the containing annular groove. A positioning block for positioning the steel ring is arranged in each placing ring groove in a sliding manner, and an elastic supporting piece for providing outward supporting force for each positioning block is arranged on the lower die and corresponds to each positioning block. The device has the effect of improving the working efficiency of steel ring preparation.

The invention discloses application of a TLE4 expression level detection reagent in preparation of a melanoma diagnostic kit. Researches find that TLE4 is abnormally low in expression in a malignant melanoma patient and is closely related to prognosis of the patient; rOC curve analysis shows that the area under the curve (AUC) is 0.861, and the 95% confidence interval is 0.833-0.887, which shows that the TLE4 gene has strong ability in distinguishing a tumor sample from a normal sample; therefore, the TLE4 gene can be used as a potential biomarker of the malignant melanoma, and a reference value is provided for clinical diagnosis of the malignant melanoma.

This disclosure relates to the field of biotechnology, specifically to a 5'UTR sequence for promoting mRNA translation and its uses. This disclosure provides a 5'UTR sequence comprising the nucleotide sequence shown in any one of SEQ ID NO: 1-6 or its complementary sequence, or a nucleotide sequence having at least 80% homology with the nucleotide sequence shown in any one of SEQ ID NO: 1-6 or its complementary sequence. This disclosure provides a novel RNA molecule design scheme that, through rational optimization of the nucleic acid sequence of functional regions, achieves the advantage of optimized translation, making this RNA molecule promising for broad applications in gene therapy, vaccine development, and other fields.

This invention discloses a machine translation method, system, device, and storage medium for Dong language under low-resource conditions, belonging to the fields of natural language processing and machine translation technology. It includes: a Dong language corpus acquisition and preprocessing module, a low-resource data augmentation module, a multilingual transfer training module, a sample balancing training module, and a translation generation and result output module. This invention improves the model's learning ability and translation performance under low-resource conditions, enabling the model to leverage knowledge from other languages ​​to enhance its ability to model the semantic and syntactic features of Dong language, increasing the effective weight of Dong language samples during training, thereby improving Dong language translation performance and enhancing the usability and promotional value of the Dong language translation system in practical application scenarios.