55results about How to "The translation is accurate" patented technology

The invention discloses a machine translation method and device. The method comprises the steps that a sentence to be translated is received; at least one phrase fragment in the sentence to be translated is replaced by a preset character string, and a template which is matched with the sentence after replacing is searched from a template library after replacing operation every time; for the sentence matched with the template, a constant translation result of the part, corresponding to the constant of the template, of the matched sentence is acquired according to the template, a variable translation result of the part, corresponding to the variable of the template, of the matched sentence is acquired by decoding, and the constant translation result and the variable translation result are spliced; for the sentence which is not matched with the template in the template library, the translation result is acquired by decoding. According to the machine translation method and device, calculation can be reduced, and translation quality is improved.

The invention provides a word input method and an input method system having a translation function. The word input method comprises the following steps of: receiving a coded string input by a user; dissolving the coded string and obtaining a syllable unit sequence of a source language corresponding to the coded string; converting the syllable unit sequence of the source language and obtaining a syllable unit sequence of a target language; converting the syllable unit sequence of the target language and obtaining a transliteration result, and displaying the transliteration result; and outputting the appointed transliteration result according to an instruction of the user. In the word input method, a mapping relation between pronunciations of the two languages is constructed, so an effect that the user can obtain a correct spelling result through pronunciation can be achieved; under the help of the input method system, the user who forgets spelling can input a correctly spelled word or sentence; furthermore, some words which cannot be paraphrased or the paraphrase is not correct enough can be translated more accurately.

The invention relates to a method, device, a readable storage medium and a computer device for text translation, including steps: obtaining an initial source text and reconstructing that source text,wherein the reconstructed source text is the source text obtained by supplementing the initial source text with missing word position information; carrying out semantic coding on the initial source text to obtain a source end vector sequence corresponding to the initial source text; a target end vector being obtained by sequentially decoding that source end vector sequence, and the target end vector being decoded according to the word vector of the candidate target word determined before each decoding, and the candidate target word of the current time being determined according to the target end vector of the current time; forming a target end vector sequence by sequentially decoding the target end vectors; performing reconstruction evaluation processing on the source vector sequence and the target vector sequence according to the reconstruction source text to obtain a reconstruction score corresponding to each candidate target word; a target text being generated according to that reconstruction score and the candidate target word. The scheme provided by the present application can improve the quality of translation.

Disclosed are a translation system and a translation method. The translation system comprises a communication network, a user side, a server and a human translation side. The server comprises a server database including a standard database and a temporary database, wherein the standard database is used for storing original texts of all manually-inputted thinkable accurate characters, words and sentences and corresponding translated text materials, and the temporary database comprises original texts not exactly the same with those stored in the standard database and translating texts that the user side requests the human translation side to translate, wherein the translating texts in the temporary database and the translated texts in the standard database can be displayed in a distinguished manner when being outputted by the user side. The translation system has the advantages that the original texts requested to be translated by the user side and the translated texts can be completely stored into the databases, and when sentences are translated, if the database does not include the translated texts corresponding to the original texts, a user is informed that the translated texts come from the standard database or the temporary database and whether human translation is selected or not.

The invention discloses a machine translation method and device based on statistics, and electronic equipment, and a method and device for building a translation quality prediction model, wherein the machine translation method based on statistics comprises the steps of by aiming at each candidate translation of a text to be translated, obtaining the translation features in the language aspect according to the text to be translated and the candidate translations; obtaining the translation features in the service aspect according to service information; calculating the translation quality score of each candidate translation by the pre-generated translation quality prediction model according to the obtained translation features in the language aspect and the obtained translation features in the service aspect; and then, selecting the preset quantity of candidate translations with high translation quality scores as the translations of the text to be translated. After the methods provided by the invention are used, translation results with accurate languages can be generated; and meanwhile, the practical service target can also be met, so that the effect of improving the translation quality is achieved.

The invention discloses a continuous sign language video translation method based on the fusion of a time domain convolution network and a circulating neural network, which comprises the following steps: feature extraction of the sign language video and construction of a word list; processing of a time domain convolution network TCN; the processing of a bi-directional circulating neural network BGRU; word mapping process of feature; processing of a fusion network FL; optimization of network model parameters based on the fusion of the time domain convolution network TCN and the bi-directional circulating neural network BGRU; fusion and decoding of word coding vectors. The invention can effectively overcome the communication obstacle caused by inaccurate interpretation of sign language translation by utilizing the network structure of different perspectives, learn and analyze different manifestations of data by utilizing different networks, further improve the accuracy of sign language translation, and increase the robustness of sign language translation.

The embodiment of the invention discloses a machine translation method and device, electronic equipment and a storage medium. IThe method comprises the steps of receiving to-be-translated statements;calling a machine translation model obtained by training, the machine translation model comprising a partitioning model and a translation model; then partitioning the to-be-translated statement according to the word vector of the to-be-translated word based on the partitioning model to obtain a to-be-translated block, and finally translating the to-be-translated statement based on the translationmodel and the to-be-translated block to obtain a translation result. In the present invention, the partitioning model is used for partitioning the to-be-translated statement according to the word vector to obtain the to-be-translated block; therefore, the to-be-translated statement can be divided into smaller to-be-translated blocks; and when the translation model translates based on the to-be-translated blocks, the translation results corresponding to the to-be-translated blocks are more accurate, and the translation results corresponding to the to-be-translated blocks are combined, so that the translation result of the whole to-be-translated statement is more accurate, and the accuracy of machine translation is improved.

The embodiments of the invention provide a text translation model training method and device. The method comprises the steps that a first training text set is acquired, the first training text set comprises first-class corpus data and second-class corpus data, a first translation model is trained through the first-class corpus data, and after the first translation model meets the training stoppingcondition, a second translation model is trained through the second-class corpus data, wherein the first translation model and the second translation model share part of model parameters, and the number of second-class corpus data input during training of the second translation model is smaller than the number of first-class corpus data input during training of the first translation model; and, after the second translation model meets the training stopping condition, whether the first translation model continues to be trained or not is judged, and if it is determined that the first translation model does not continue to be trained any more, the trained first translation model serves as a text translation model. According to the embodiments of the invention, the translation result obtainedby training is more accurate and the translation style is clearer.

The invention discloses a zero parallel corpus multi-modal neural machine translation method, which comprises the following steps: pre-training a pre-constructed neural machine translation model by utilizing a source language with corresponding picture information and a target language monolingual corpus; translating sentences in the source language into sentences in a target language by using a pre-trained neural machine translation model; calculating a reward value of a sentence level according to an internal relation between the sentence obtained by translation and a corresponding picture, and updating pre-trained neural machine translation model parameters by adopting a strategy gradient reinforcement learning method by taking the maximum expected total reward value as an optimization target so as to obtain a trained neural machine translation model; and translating the given source language sentence by using the trained neural machine translation model. According to the zero parallel corpus multi-modal neural machine translation method, a neural machine translation model of a zero resource language pair can be established by utilizing the internal relation between pictures and characters.

The invention discloses a Bluetooth fingertip translator and a translation method thereof. The translator comprises a ring body, a ring belt, a control circuit board, a microphone and a recording button; the ring belt encircles the two ends of the ring body. Both the control circuit board and the microphone are placed in the ring body. The recording button is arranged on the outer surface of the ring body. The input end of the microphone is connected with the recording button. The output end of the microphone is electrically connected with the control circuit board. The fingertip translator further comprises a Bluetooth chip for transmitting an audio signal obtained by the microphone to a mobile terminal. The Bluetooth chip is electrically connected with the control circuit board and is connected with the mobile terminal in a wireless mode. The microphone and the Bluetooth chip are arranged on the ring body, and thus the ring body is used as a carrier for receiving information to be translated. The Bluetooth chip is connected to the mobile terminal through a Bluetooth in a wireless mode, and in this way, translation and displaying can be directly carried out on the mobile terminal.

The invention provides a combined machine translation method by utilizing a segmentation technique, in particular to a combined machine translation method for translating Chinese into English by utilizing a segmentation technique. Through reasonable segmentation of Chinese sentences, similarity calculation and an English generation rule, English text meeting requirements is obtained without dependence on a network database at a certain degree, and by only processing the Chinese sentences to be translated and combining with a set English translation rule at the same time, an accurate translation result can be obtained.

The invention discloses a translation method and device. The translation method comprises the main steps that obtained voice signals are converted into audio information, then the audio information isseparated into multiple pieces of audio sub-information, and only the audio sub-information meeting the vocal print requirements is sent to a server for translation. By adopting the translation method, the translation work amount can be reduced, the translation efficiency can be improved, and the translation time can be shortened.

The invention relates to the artificial intelligence technology, and discloses a machine translation method. The method comprises the steps of obtaining a statement set containing Chinese statements and English statements, performing word segmentation processing on the statement set to obtain a word set, establishing corresponding labels for the Chinese statements and the English statements, and generating a label set; converting the word set into a word vector through a word2vec model, taking the word vector as a training set, and storing the training set and the label set into a database; utilizing the training set and the label set to train a constructed machine translation model; and receiving a to-be-translated statement of a user, performing machine translation on the to-be-translated statement of the user by utilizing the trained machine translation model, and outputting the translated statement. The invention further provides a machine translation device and a computer readablestorage medium. According to the invention, accurate translation of the statement is realized.

The invention belongs to the technical field of teaching, and discloses a remote Japanese teaching interaction system and method based on big data analysis. The remote Japanese teaching interaction system based on big data analysis comprises a teaching video acquisition module, an input module, a central control module, a network communication module, a voice translation module, a text translationmodule, a big data processing module, a storage module and a display module. Man-machine conversation is improved into direct conversation between people through the voice translation module, the vividness and authenticity of voice translation are improved, and the user experience is improved. Meanwhile, through the text translation module, the phoneme sequence can be utilized to carry out fault-tolerant processing on the speech recognition result, so that the translated target text can correspond to the source speech signal more accurately, the translation result is more accurate, and the Japanese teaching quality is improved.

The embodiments of the invention provide a voice translation processing method and device, belonging to the technical field of language processing. The method includes the following steps: if that a first voice signal in the last round and a second voice signal to be translated in the current round correspond to the same language type is judged, adjusting the text data corresponding to the secondvoice signal based on the text data corresponding to the first voice signal to get the adjusted text data corresponding to the second voice signal; and acquiring a synthesized voice signal corresponding to the adjusted text data, and broadcasting the synthesized voice signal. As the first voice signal in the last round and the second voice signal to be translated in the current round may be correlated in content, the adjustment of the text data corresponding to the second voice signal based on the text data corresponding to the first voice signal can make the translation result better suit thescene and more accurate.

The invention provides a character translation method and a device thereof. According to an embodiment, the character translation method executed by a character translation device can include a step of obtaining image contents; a step of identifying characters in first language in the image contents, and article confirming symbols of the first language; a step of extracting articles in the first language according to the identified article confirming symbols, the articles being formed by the identified characters; a step of using user event information to generate a translation object articleaccording to the extracted article in the first language; and a step of translating the generated translation object article to second language, and displaying the article which is translated into thesecond language. The character translation method and the device thereof can provide more accurate translation results for users.

A cloud-based translation method for a mobile client is provided. The mobile client receives a translation instruction and sends translation request information to a cloud server based on the translation instruction, where the translation request information includes text information and translation type information. The mobile client receives a translation result returned from the cloud server. When the cloud server detects that the mobile terminal logins to an account, and a cloud glossary of the account contains a word entry corresponding to the text information, the cloud server returns the translation result in the cloud glossary. When the cloud server detects that the mobile terminal does not login to the account, or when the cloud server detects that the mobile terminal logins to the account but the cloud glossary does not contain the word entry corresponding to the text information, the cloud server translates the text information.

The invention provides an English lexical analysis method for neural network machine translation. The English lexical analysis method comprises the following steps: performing English word segmentation on a to-be-processed English text; carrying out query screening on each word obtained after English word segmentation by utilizing a special vocabulary; reserving result information of the queried words in a lexical analysis result; performing rule processing on the words which are not queried; carrying out word architecture restoration on the words meeting the rule processing conditions, and directly storing the words which do not meet the rule processing conditions in a lexical analysis result; and outputting a lexical analysis result, and adding the lexical analysis result into machine deep learning training. The invention further provides an English lexical analysis system for neural network machine translation. According to the English lexical analysis method for neural network machine translation, the problems that the machine learning efficiency is reduced and the translation quality is poor due to the fact that training corpus data of neural network machine translation is sparse can be solved.

The invention provides a similarity-based intelligent offline translation machine and particularly relates to similarity-based intelligent offline translation machine for translating Chinese into English. The similarity-based intelligent offline translation machine has the advantages that by performing reasonable dividing and similarity calculation on Chinese sentences and setting English generating rules, the English satisfying requirements can be obtained, and an accurate translation result can be obtained without a network database and only by processing the to-be-translated Chinese sentences and the set English translation rules to a certain degree.

The invention provides a classification model training method and device, a translation method and device and electronic equipment, and relates to the technical field of natural language processing and machine learning. The method comprises the following steps: acquiring bilingual parallel corpora, wherein the bilingual parallel corpora comprise a source language corpus and a target language corpus; determining translable fragments and untranslable fragments in the source language corpus, wherein the translable fragments are determined based on unambiguous fragments in the source language corpus; and training a classification model based on the translatable fragments and the untranslatable fragments. According to the above technical scheme, the classification model is trained based on the translable fragments and the untranslable fragments, the trained classification model is applied to translation, a translation result can be more accurate, and requirements for high quality and low time delay are met.

The invention discloses a Mongolian-Chinese machine translation method combining a Meta-KD framework and fine-grained compression. The method comprises the following steps: performing data preprocessing and data set division on Chinese corpora, English corpora and Mongolian corpora, learning Chinese-English translation by using the Meta-KD framework, training a BERT language model, learning a student model under the guidance of a meta-teacher according to a meta-distillation algorithm to obtain transferable knowledge for Mongolian-Chinese translation, and in combination with a fine-grained compression method, performing training verification of the Mongolian-Chinese translation on the student model. According to the method, data set training is performed through the Meta-KD framework, so that the method is more suitable for translation of small languages, and a more accurate translation result is obtained; and the fine-grained compression enables the trained model to have a higher training speed. Then, in combination with the fine-grained compression method, fine-grained compression is performed on information representation through information entropy, so that the purpose of model accelerated inference is achieved.

The invention discloses a scene matching fused Chinese sign language translation model construction method and device. The method comprises the steps of S1, constructing a sign language word recognition model of a mapping relationship between sign language actions and words in different scenes, and constructing a scene matching model of a mapping relationship between different scene vocabularies and sign language actions; s2, respectively training the sign language word recognition model and the scene matching model to obtain a trained sign language word recognition model and a scene matching model; s3, cascading the trained sign language word recognition model and the scene matching model to form a Chinese sign language translation model, acquiring a sign language action data set, and respectively inputting the sign language action data set into the sign language word recognition model and the scene matching model of the Chinese sign language translation model to update the models, and obtaining a final Chinese sign language translation model until the sign language word recognition model and the scene matching model reach dynamic balance. The method and device have the advantages of simple implementation method, high construction efficiency, high accuracy and the like.

The invention provides a translation corpus processing method and device. The translation corpus processing method comprises the steps of acquiring a first language translation corpus, a first language corpus phrase and a post-translation phrase; performing word segmentation processing on the first language translation corpus to obtain a corpus word segmentation table, and performing word segmentation processing on the first language corpus phrase and the post-translation phrase to obtain a phrase word segmentation table; creating a word probability table according to the corpus word segmentation table and the phrase word segmentation table, wherein the word probability table comprises to-be-selected words and probabilities corresponding to the to-be-selected words; taking each word in thecorpus word segmentation table as a reference word, traversing the reference word to obtain a reference word which is the same as the to-be-selected word, taking the reference word as a target word,and obtaining the probability of the to-be-selected word corresponding to the reference word; and determining phrases in the first language translation corpus corresponding to the first language corpus phrase according to the target word and the probability of the target word.

The invention discloses a scanning pen. The scanning pen comprises a pen body structure, a camera and a light beam positioning structure, the camera is used for collecting an image of a to-be-scannedinterface, the light beam positioning structure is used for emitting a light beam to form a positioning light mark on the to-be-scanned interface, and the positioning light mark is located on the leftside of a scanning window of the camera in the scanning direction of the scanning pen. The scanning pen is used; the positioning light mark can be formed through the light beam positioning structure;before scanning, the positioning light mark can be controlled to be located on the left side of a to-be-scanned character, which means that the scanning starting position is prompted to a user, the scanning window of the camera can be aligned with the to-be-scanned character, the complete information scanning can be realized based on the above basis, the conditions of missing the characters and the like are avoided, the finally scanned electronic information is more complete and accurate, and the translation result is more accurate.

The invention discloses a multifunctional English translator. The translator comprises a hand input unit, an infrared scanning unit, a speech input unit, a translation unit, a digital converter and a central processing unit; the hand input unit is used for inputting corresponding statements according to sentence pairs, terms or discourses and sending the input statements to the central processing unit; the infrared scanning unit is used for scanning English words, meanwhile converting the English words into scanning information and sending the scanning information obtained after conversion to the central processing unit; the speech input unit is used for inputting speech information through user accents, continuous speeches or an irregular word order and speed and sending the input speech information to the central processing unit and the digital converter; the digital converter is used for receiving the speech information sent from the speech input unit, converting the speech information into digital signals and sending the digital signals to the central processing unit. The translator is good in recognition effect, accurate in translation result, rich in function and quite convenient to use and intelligent.

The invention provides a translation method and system for a Chinese sentence containing unconventional vocabularies. For the Chinese sentence containing the unconventional vocabularies, firstly conventional vocabularies and the unconventional vocabularies in the Chinese sentence are identified through a word segmentation technology; and secondly two parts including the conventional vocabularies and the unconventional vocabularies are analyzed and translated, and a translation result is obtained through combination, wherein the conventional vocabularies can be obtained through an automatic translation tool, and for the unconventional vocabularies, a relatively accurate translation result can be obtained by adopting a corpus library retrieval technology proposed in the method. Through the method, a translator can obtain the translation result of the whole sentence only by finishing editing and proof-reading work with relatively small workload, and relatively high accuracy is ensured.

The invention provides a training method and device of a translation model, a translation method and device, equipment and a storage medium, and relates to the technical field of computers, in particular to the field of artificial intelligence such as natural language processing and machine translation. According to the specific implementation scheme, a sample document is processed, an RST chapter structure tree in a dependency form of the sample document is obtained, and the edge of the RST chapter structure tree in the dependency form represents the RST relation in the chapter of the sample document; determining an attention mechanism of the translation model to be trained based on an RST relationship in the RST text structure tree of the dependency form; and inputting the RST text structure tree in the dependency form and the sample document into the to-be-trained translation model for training to obtain a trained translation model. According to the embodiment of the invention, the translation result of the translation model is more accurate.

The present invention provides a Chinese-to-English off-line translation method, especially a Chinese-to-English off-line translation method from Chinese to English, through reasonable segmentation of Chinese sentences, similarity calculation, and English generation rules to obtain English that meets the requirements, To a certain extent, it has realized that there is no need to rely on the network database, only by processing the Chinese sentences to be translated, and combined with the set English translation rules, more accurate translation results can also be obtained.

The embodiment of the invention provides a translation method and device, a server and a computer readable storage medium. The method comprises the following steps: receiving a translation request sent by a terminal; obtaining a to-be-translated text requested to be translated by the translation request; determining area information of an area to which the terminal belongs; searching for a sentence-level translation library having a mapping relationship with the regional information; wherein the sentence-level translation library stores preset sentences and sentence translations correspondingto the preset sentences; and according to the sentence-level translation library, searching a translation of each sentence to be translated in the text to be translated. In this way, the sentence-level translation library can be used for translating the to-be-translated text from the sentence level. Therefore, an accurate translation result conforming to the translation mode of the region can be quickly obtained.

The invention relates to the technical field of translation, and particularly relates to a Chinese and Wuerjia synchronous inter-translation system, which comprises: an input module used for inputtingand sending voice of a first language; a recognition module which is used for converting the voice of the first language into characters of the first language; an analysis module which is used for identifying polysemy and context information of the first language; a query module which is used for finding the explanation of the first language most relevant to the polysemy of the first language inthe database according to the context information and replacing the polysemy of the first language with the explanation of the first language; a translation module which is used for translating the characters in the first language into the characters in the second language; a synthesis module which is used for converting the characters of the second language into voice of the second language; andan output module which is used for outputting the voice of the second language. When mutual translation is carried out, the probability of mismatching and mismatching when the database is matched with the target language is reduced, so that the translation result is more accurate.