Translation error correction method and related device

Abstract

The invention provides a translation error correction method and a related device, and the method comprises the steps: obtaining the text content of a user in a process of using target software, and determining the original language of the text content; in response to a translation instruction of a user, obtaining a target language required by the user, and generating translation request information for translating the text content from the original language into the target language; translating the text content according to the translation request information to obtain a translation output result; acquiring error correction information of the user for the translation output result, and auditing the error correction information; if the error correction information does not pass the auditing, determining that the translation output result is a target translation result; and if the error correction information passes the auditing, adjusting the translation output result according to the error correction information to obtain a target translation result, and issuing reward points corresponding to the error correction information to the user. The translation accuracy can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of translation error correction, and in particular to a translation error correction method and related devices. Background Art

[0002] Currently, when using various software, such as vehicle diagnostics, e-commerce shopping, and map navigation, users often directly use third-party translation services to automatically translate text content. This can result in inaccurate translations. Furthermore, addressing user feedback regarding translation errors can be time-consuming, making it difficult to obtain more accurate translation results in a timely manner, resulting in a poor user experience.

[0003] Therefore, how to improve the accuracy of translation needs to be solved urgently. Summary of the Invention

[0004] The embodiments of the present application provide a translation error correction method and related devices, which improve the accuracy of translation by quickly reviewing error correction information and optimizing the translation results based on the error correction information after the review is passed.

[0005] In a first aspect, an embodiment of the present application provides a translation error correction method, which is applied to a control center of a target software, wherein the target software includes any one of the following: vehicle diagnostic software, e-commerce shopping software, and map navigation software. The method includes:

[0006] Acquire text content generated by a user during use of the target software, and determine the original language of the text content;

[0007] In response to the user's translation instruction, obtaining the target language required by the user, and generating translation request information for translating the text content from the original language into the target language;

[0008] Translate the text content according to the translation request information to obtain a translation output result;

[0009] Obtaining error correction information from the user regarding the translation output result, and reviewing the error correction information;

[0010] If the error correction information fails to pass the review, determining the translation output result as the target translation result;

[0011] If the error correction information is approved, the translation output result is adjusted according to the error correction information to obtain the target translation result, and reward points corresponding to the error correction information are issued to the user; the reward points are used to shop in the shopping area of the target software.

[0012] In a second aspect, an embodiment of the present application provides a translation error correction device, which is applied to a control center of a target software, wherein the target software includes any one of the following: vehicle diagnostic software, e-commerce shopping software, and map navigation software. The device includes an acquisition module, a generation module, a translation module, a review module, an output module, and an adjustment module, wherein:

[0013] The acquisition module is used to acquire text content generated by the user during the use of the target software and determine the original language of the text content;

[0014] The generating module is configured to obtain the target language required by the user in response to the translation instruction of the user, and generate translation request information for translating the text content from the original language into the target language;

[0015] The translation module is configured to translate the text content according to the translation request information to obtain a translation output result;

[0016] The review module is used to obtain the user's error correction information for the translation output result and review the error correction information;

[0017] The output module is configured to determine that the translation output result is a target translation result if the error correction information fails to pass the review;

[0018] The adjustment module is configured to adjust the translation output result according to the error correction information if the error correction information is approved, thereby obtaining the target translation result, and to issue reward points corresponding to the error correction information to the user; the reward points are used for shopping in the shopping area of the target software.

[0019] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program comprises instructions for executing the steps of any method of the first aspect of the embodiment of the present application.

[0020] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the above-mentioned computer-readable storage medium stores a computer program for electronic data exchange, wherein the above-mentioned computer program enables a computer to execute part or all of the steps described in any method of the first aspect of the embodiment of the present application.

[0021] In a fifth aspect, embodiments of the present application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to execute some or all of the steps described in any method of the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

[0022] By implementing the embodiments of the present application, the error correction information is quickly reviewed, and after the review is passed, the translation result is optimized based on the error correction information, thereby improving the accuracy of the translation. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0024] Figure 1 This is a diagram of the structure of a vehicle diagnostic software provided in an embodiment of the present application;

[0025] Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0026] Figure 3 This is a flowchart of a translation error correction method provided by an embodiment of the present application;

[0027] Figure 4 This is a scenario architecture diagram of a vehicle diagnosis provided by an embodiment of the present application;

[0028] Figure 5 This is a flowchart of a multilingual text translation process provided by an embodiment of the present application;

[0029] Figure 6 This is a flowchart of a translation process provided by an embodiment of the present application;

[0030] Figure 7 This is a flowchart of an error correction review provided by an embodiment of the present application;

[0031] Figure 8 This is a block diagram of the functional modules of a translation error correction device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0034] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document indicates that the associated objects are in an "or" relationship. The "plurality" appearing in the embodiments of this application refers to two or more.

[0035] In the embodiments of the present application, "at least one item" or similar expressions refers to any combination of these items, including any combination of single items or plural items, and refers to one or more, and multiple refers to two or more. For example, at least one item (item) of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0036] The "connection" appearing in the embodiments of the present application refers to various connection methods such as direct connection or indirect connection to achieve communication between devices, and the embodiments of the present application do not impose any limitations on this.

[0037] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0038] The following are the explanations of the relevant terms involved in this application:

[0039] Third-party translation service providers are independent organizations or companies that specialize in providing translation services, such as Baidu, Google, and NetEase. These companies utilize specialized translation technology and teams to translate the original text of vehicle diagnostic software, including menus and icons, into multiple languages.

[0040] Vehicle diagnostic software: This refers to an application installed on smart devices, such as computers, mobile phones, and tablets, that monitors and analyzes vehicle conditions. By connecting to the vehicle's diagnostic interface, it reads fault codes and operating data from various vehicle systems, helping users or maintenance personnel determine whether a vehicle is faulty, the cause of the fault, and the vehicle's overall operating status.

[0041] E-commerce shopping software: refers to an application built on the Internet platform to serve the online transactions of goods and services. It integrates core modules such as information flow, capital flow and logistics to help users shop conveniently.

[0042] Map navigation software: refers to an application that uses satellite positioning technology and electronic map data to provide users with geographic information query, route planning, navigation guidance and other functions.

[0043] Currently, when using various software, such as vehicle diagnostics, e-commerce shopping, and map navigation, users often directly use third-party translation services to automatically translate text content. This can result in inaccurate translations. Furthermore, addressing user feedback regarding translation errors can be time-consuming, making it difficult to obtain more accurate translation results in a timely manner, resulting in a poor user experience. Therefore, improving translation accuracy is an urgent issue that needs to be addressed.

[0044] To solve the above problems, the present invention provides a translation error correction method and related device, which are applied to the control center of the target software, wherein the target software includes any one of the following: vehicle diagnostic software, e-commerce shopping software, and map navigation software. First, the text content of the user in the process of using the target software is obtained and the original language of the text content is determined; in response to the translation instruction of the user, the target language required by the user is obtained, and a translation request information is generated for translating the text content from the original language to the target language; the text content is translated according to the translation request information to obtain a translation output result; the user's error correction information for the translation output result is obtained and the error correction information is reviewed; if the error correction information review fails, the translation output result is determined to be the target translation result; if the error correction information review passes, the translation output result is adjusted according to the error correction information to obtain the target translation result, and reward points corresponding to the error correction information are issued to the user; the reward points are used to shop in the shopping area of the target software. It can be seen that by quickly reviewing the error correction information and optimizing the translation result according to the error correction information after the review passes, the accuracy of the translation is improved.

[0045] See also Figure 1 , Figure 1 The following is a diagram of the component architecture of vehicle diagnostic software provided in an embodiment of the present application. The target software may be vehicle diagnostic software, without specific limitation. The vehicle diagnostic software includes a data monitoring unit, an information management unit, a vehicle diagnostic unit, and a control center. Within the vehicle diagnostic software, the various components work closely together through data communication and the exchange of control commands to provide comprehensive and accurate vehicle diagnostic services.

[0046] The data monitoring unit connects to the vehicle's various sensors and electronic control units to collect various data during vehicle operation in real time, such as engine speed, vehicle speed, oil pressure, water temperature, and exhaust emissions. This data is initially processed and filtered to obtain valid data, which is then transmitted to the control center. The control center then conducts further analysis and judgment based on the valid data, or forwards the valid data to other relevant units, such as the information management unit, for storage and management, allowing users to subsequently review and analyze the vehicle's operating status.

[0047] The information management unit is responsible for recording, storing, and managing various vehicle information. It receives vehicle operating data from the data monitoring unit, as well as basic vehicle information (such as vehicle model, frame number, and production date), maintenance records, and repair history. The information management unit categorizes this information according to pre-set rules and stores it in a database, facilitating query and retrieval. Furthermore, after the vehicle diagnostic unit completes its diagnosis, it also stores the diagnostic results and related fault information, providing a reference for subsequent repairs and analysis.

[0048] The vehicle diagnostic unit is a key component in implementing vehicle fault diagnosis. It connects to the vehicle and communicates with the vehicle's electronic control unit. It reads and analyzes the vehicle's fault codes to determine the type and possible cause of the fault. The diagnostic results are presented to the user in a detailed report, including the fault code, fault description, severity, and recommended repairs. The results are also fed back to the control center, which determines whether further action is required, such as notifying the information management unit to store the diagnostic results or triggering a fault warning function based on the fault condition.

[0049] The control center is responsible for coordinating the operation of the entire vehicle diagnostic software. It receives information and data from other units, performs comprehensive processing and analysis, and sends control signals and task assignment instructions to each unit based on specific situations and user instructions. For example, when a user issues a diagnostic request, the control center notifies the vehicle diagnostic unit to perform the diagnostic operation; when real-time vehicle data monitoring is required, the control center instructs the data monitoring unit to begin operation; and when a user issues a translation instruction, the control center translates the text content of the user's use of the vehicle diagnostic software from the original language into the target language, generating the translated output. It should be noted that if the control center receives error correction information from the user regarding the translated output, it will review it. If the error correction information fails the review, the translated output will be determined as the target translation result. If the error correction information passes the review, the translated output will be adjusted based on the error correction information to obtain the final target translation result.

[0050] As can be seen, vehicle diagnostic software provides intuitive insights into a vehicle's real-time status, historical information, and accurate diagnostic results. It also provides translation services tailored to the needs of different users, enhancing the user experience. Furthermore, through user error correction mechanisms, it can adapt to diverse needs and language habits, while also improving translation accuracy.

[0051] The following combination Figure 2 The electronic device in the embodiment of the present application is described. Figure 2is a structural diagram of an electronic device provided in an embodiment of the present application, such as Figure 2 As shown, the electronic device includes one or more processors, a memory, a communication interface and one or more programs, and the processor is communicatively connected with the memory and the communication interface via an internal communication bus.

[0052] Among them, the processor is mainly used for:

[0053] Obtain the text content of the user when using the target software and determine the original language of the text content;

[0054] In response to a user's translation instruction, obtaining the target language required by the user and generating translation request information for translating the text content from the original language into the target language;

[0055] Translate the text content according to the translation request information to obtain a translation output result;

[0056] Obtaining user correction information for translation output results and reviewing the correction information;

[0057] If the error correction information fails to pass the review, the translation output result is determined to be the target translation result;

[0058] If the error correction information is approved, the translation output result will be adjusted according to the error correction information to obtain the target translation result, and the user will be issued reward points corresponding to the error correction information; the reward points can be used to shop in the shopping area in the target software.

[0059] The one or more programs are stored in the above-mentioned memory and are configured to be executed by the above-mentioned processor, and the one or more programs include instructions for executing any step in the above-mentioned method embodiment.

[0060] Among them, the processor can be, for example, a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute the various exemplary logic blocks, units and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like. The communication unit can be a communication interface, a transceiver, a transceiver circuit, etc., and the storage unit can be a memory.

[0061] The memory may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Among them, the non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM).

[0062] It is understood that the electronic device may include more or fewer structural elements than those in the above structural block diagram, for example, including a power module, physical buttons, Wi-Fi module, speaker, Bluetooth module, sensor, display module, etc., which are not limited here. It is understood that the electronic device may be equipped with Figure 1 The composition architecture.

[0063] After understanding the software and hardware architecture of this application, Figure 3 A translation error correction method in an embodiment of the present application is described. Figure 3 This is a flowchart of a translation error correction method provided in an embodiment of the present application, which is applied to the control center of a target software, wherein the target software includes any of the following: vehicle diagnostic software, e-commerce shopping software, and map navigation software. Specifically, the method includes the following steps:

[0064] Step S301: obtaining text content when the user is using the target software, and determining the original language of the text content.

[0065] Specifically, when a user interacts with the target software, such as vehicle diagnostic software, they generate system interaction information, such as diagnostic commands sent by the user and feedback from the vehicle. The vehicle diagnostic software records the text generated during this interaction. For example, the vehicle's electronic control unit returns fault code descriptions, which the software captures and stores in full. Furthermore, the software also captures textual content, such as prompts and error messages, generated by the user during operation of the vehicle diagnostic software (not specifically limited here). The vehicle diagnostic software has built-in feature libraries for multiple languages, which contain information such as alphabets, common vocabulary, and grammatical structures for different languages. After acquiring the text content, the vehicle diagnostic software's control center analyzes features such as character composition and vocabulary distribution. For example, if the text contains a large number of Chinese characters and punctuation marks, it is initially determined that the original language is likely Chinese. If the text contains a large number of Latin characters and conforms to English vocabulary and grammatical structures, it is likely that the original language is English. By matching and analyzing language features, the original language of the text can be quickly determined. It should be noted that the target software includes but is not limited to vehicle diagnostic software, e-commerce shopping software, and map navigation software, and is not specifically limited here.

[0066] It can be seen that by analyzing features such as character composition and vocabulary distribution to quickly determine the original language of the text content, it is easier to understand and process the text content more accurately, avoid diagnostic errors caused by language misunderstandings, and thus improve the accuracy and reliability of vehicle diagnosis.

[0067] Step S302 : In response to the translation instruction of the user, obtaining the target language required by the user, and generating translation request information for translating the text content from the original language into the target language.

[0068] Specifically, when a user triggers the translation function button on the software interface, such as clicking the "Translate" option or using a shortcut key to issue a translation instruction, the vehicle diagnostic software can immediately capture the translation instruction, thereby initiating the subsequent translation process. The target language required by the user can be obtained in a variety of ways. For example, a drop-down menu or language selection box can be set on the software interface. When the user selects from it, the user's selection is determined to be the target language, such as "English," "Chinese," "French," etc. If the user does not make an explicit selection, the default target language is used, that is, the user's usage habits or the previously set default target language. In addition, the target language required by the user can also be determined through voice input, which is not specifically limited here. Then, a corresponding translation request information is generated based on the original language, text content, and target language. This translation request information is used to translate the text content from the original language to the target language.

[0069] As can be seen, by acquiring the target language and generating translation request information, we can flexibly meet users' diverse language needs, improving user satisfaction and user experience. Furthermore, accurately translating the text content of vehicle diagnostic software can avoid misunderstandings or incorrect operations caused by language barriers.

[0070] Step S303: Translate the text content according to the translation request information to obtain a translation output result.

[0071] The step of translating the text content according to the translation request information to obtain a translation output result specifically includes:

[0072] A1. Determine the server corresponding to the target software;

[0073] A2. searching the local cache of the server according to the translation request information to determine whether a first text record exists in the local cache; the first text record corresponds to the text content;

[0074] A3. If the first text record exists, determining, based on a preset mapping relationship between text records and translation results, that the translation result corresponding to the first text record is the first translation result;

[0075] A4. If the language of the first translation result is the target language, determining the first translation result as the translation output result;

[0076] A5. If the first text record does not exist or the language of the first translation result is not the target language, a third-party translation service provider is used to perform translation according to the translation request information to obtain a second translation result, and the second translation result is determined as the translation output result.

[0077] In a specific embodiment, the target software's corresponding server can first be determined based on its configuration information, which includes information such as the server's address and port number. Then, based on the translation request, a search operation is performed in the server's local cache to determine whether a first text record exists in the local cache that is identical to the text content in the current translation request. For example, if the same vehicle fault description text has been previously translated, the corresponding text record and its translation result will be stored in the local cache. Subsequently, the text record can be searched and matched against the data in the local cache to obtain its corresponding translation result.

[0078] Then, if there is a first text record corresponding to the current text content in the local cache, the translation result corresponding to the first text record can be obtained by utilizing a pre-set mapping relationship, thereby obtaining the first translation result. Then, check whether the language of the first translation result is consistent with the target language in the translation request information. If the language of the first translation result is the target language, the first translation result is determined to be the translation output result. If there is no first text record in the local cache or the language of the first translation result is not the target language, a third-party translation service provider is used to translate according to the translation request information to obtain a second translation result, and the second translation result is determined to be the translation output result. Among them, the third-party translation service provider has a professional translation engine and rich language resources, including but not limited to Baidu, Google, and NetEase, which are not specifically limited here. The third-party translation service provider can perform translation processing based on the received translation request information (including text content, original language and target language) to generate a second translation result. It should be noted that after generating the second translation result, a text record will be generated according to the text content and stored in the local cache. At the same time, the second translation result corresponding to the text record will be recorded, so that subsequent searches can be performed directly through the local cache to avoid calling a third-party translation service provider.

[0079] It can be seen that by searching for translation records in the local cache of the server, the translation processing time can be reduced. For frequently appearing identical or similar text content, the translation results can be returned quickly, which improves the user experience and makes the target software respond more quickly.

[0080] For example, let's assume the target diagnostic software is vehicle diagnostic software. Each year, 100,000 vehicles of a certain model experience a specific fault, with the fault description being "Clogged fuel injection system, resulting in reduced engine power." Each translation of this text into multiple languages (e.g., English, Japanese, German, French, etc., for a total of 10 languages) costs a third-party translation service provider 10 yuan per translation (1 yuan per language). Without a local caching mechanism, the annual translation cost for just this single fault description would be as high as: 100,000 (number of vehicles) × 10 (number of languages) × 10 (cost per translation) = 10 million yuan. Furthermore, each time a translation issue is reported by a user, the third-party translation service provider must hire a translation specialist to optimize it. Developers save the latest translation in a configuration file, release it, and then provide feedback to customer service and dealers. The dealers then provide feedback to users. This entire translation process is lengthy, time-consuming, and results in a poor user experience. After adopting the local caching mechanism, assuming that the first translation of the text and its 10 language versions cost 100 yuan (10 languages, 10 yuan for each language), then because there are records in the local cache, there is no need to call a third-party translation service for the subsequent 99,999 times the fault description appears, then within one year, the translation cost for the text is only 100 yuan. At the same time, by directly calling the records in the local cache, the time cost of translation can be saved and the user experience can be improved. It can be seen that the local caching mechanism has significantly reduced costs at the million-level cost level, and as the scale of the company's business expands, the number of vehicle sales and the number of faults increase, the cost savings will be even more considerable. Among them, in actual use, there are many types of texts that need to be translated in the target software, and the cost reduction effect brought by the local caching mechanism will be more prominent.

[0081] For easier understanding, see Figure 4 , Figure 4 This is a scenario architecture diagram of vehicle diagnosis provided by an embodiment of the present application, in which a vehicle is diagnosed and processed by vehicle diagnostic software, and the text content of the user in the process of using the vehicle diagnostic software is obtained. If the user is not familiar with the original language of the text content and needs to translate it into the target language, a translation request information is generated based on the text content, the original language and the target language. For example, if the original language of the fault diagnosis result is English and the target language is Chinese, the translation request information can be to translate the fault diagnosis result from English to Chinese. Then, the server corresponding to the vehicle diagnostic software is determined, and a search is performed in the local cache of the server according to the translation request information to find the text record corresponding to the text content in the local cache. Finally, the translation result corresponding to the text record is determined based on the mapping relationship between the preset text record and the translation result. If the language of the translation result is the target language, the translation result is output.

[0082] For easier understanding, see Figure 5 , Figure 5 This is a flowchart illustrating a multilingual text translation process provided by an embodiment of the present application. In vehicle diagnostic software, multilingual original text content can first be processed through a translation interface. This multilingual original text content can come from text on menu options, explanatory text represented by icons, and other content, without specific limitations here. If the translation result exists in the local cache, it is directly output through the translation interface. If not, the translation is performed using a third-party translation service provider, and the translation result is then stored in the local cache for subsequent direct access through the local cache.

[0083] For easier understanding, see Figure 6 , Figure 6 This is a flowchart of a translation process provided by an embodiment of the present application, and the specific steps include:

[0084] B1. Preprocessing the text content to obtain a text to be translated;

[0085] B2. Obtain multiple translation models corresponding to the third-party translation service provider;

[0086] B3. determining a first language combination based on the original language and the target language;

[0087] B4. Determine a first translation model as a target translation model based on the first language combination; the first translation model is the translation model that best suits the first language combination among the multiple translation models;

[0088] B5. Extracting features from the text to be translated to obtain feature information;

[0089] B6. Process the feature information according to the target translation model to obtain the second translation result.

[0090] In a specific embodiment, first, the text content is cleaned and standardized to obtain the text to be translated so that it is more suitable for subsequent translation processing, for example, special characters, extra spaces, and punctuation marks in the text content are removed. Then, multiple translation models corresponding to the third-party translation service provider are obtained. Translation models include but are not limited to rule-based translation models, statistical machine translation models, and neural network translation models, which are not specifically limited here. The third-party translation service provider can use different translation models to handle different languages and translation tasks. Then, the first language combination is determined based on the original language and the target language, and the most suitable first translation model is screened from multiple translation models based on the first language combination, and it is determined as the target translation model. For example, for the language combination of "English-Chinese", the translation model based on the neural network performs better in processing automotive-related professional texts, and will be selected as the target translation model, thereby improving the quality of the translation and ensuring that the translation results are more in line with user needs.

[0091] Next, feature extraction is performed on the preprocessed text to be translated, extracting characteristic information of the text to be translated, such as lexical features, grammatical features, and semantic features. This characteristic information is then input into the target translation model, which processes the characteristic information according to its own algorithm and parameters to generate the corresponding translation result, i.e., the second translation result.

[0092] It can be seen that through the preprocessing of text content, the selection of models, and the extraction and processing of features, the process from original text content to accurate translation results is realized, and the performance and quality of the target software in translation are improved.

[0093] Step S304: obtaining the user's error correction information for the translation output result, and reviewing the error correction information.

[0094] The obtaining of the user's error correction information for the translation output result and reviewing the error correction information specifically includes the following steps:

[0095] C1. Obtaining original translation information in the translation output result;

[0096] C2. Responding to the user's error correction instruction, obtaining error type information and correct translation information corresponding to the original translation information;

[0097] C3. Generate error correction information based on the original translation information, the error type information, and the correct translation information;

[0098] C4. Checking the format of the error correction information. If the format of the error correction information is incomplete, marking the error correction information as pending to prompt the user to modify it.

[0099] C5. If the format of the error correction information is complete, review the error correction information.

[0100] In a specific embodiment, the translation output is first extracted and the original translation information is obtained. Then, when the user discovers a problem with the original translation information and issues a correction instruction, the user can be prompted to enter the error type of the original translation information and the translation content that the user believes to be correct in response to the correction instruction, thereby obtaining the error type information and the correct translation information corresponding to the original translation information. For example, the original translation information is "engine abnormal vibration" and is translated as "engine abnormal vibration". The user believes that translating "abnormal" as "abnormal" is inaccurate and should be translated as "unusual". In this case, the error type of the original translation information is determined to be a lexical error, and the correct translation information is "engine unusual vibration".

[0101] Next, the original translation information, error type information, and corrected translation information are integrated to generate correction information. To ensure the standardization and completeness of the correction information, the format of the correction information is checked. If the correction information is missing necessary parts or the format does not meet the requirements, it will be marked as pending and a prompt will be issued to the user, informing them that the relevant content needs to be supplemented or modified. If the correction information meets the format requirements and the content is complete, it will be reviewed to determine its rationality and accuracy.

[0102] It can be seen that through user participation in error correction, processing and review of error correction information, the quality and accuracy of the target software translation results can be continuously improved, and user satisfaction with the target software can be enhanced.

[0103] The error type information includes at least one of the following: grammatical error, vocabulary error, and inappropriate context; and the review of the error correction information includes the following specific steps:

[0104] D1. Checking the original translation information according to the error type information to obtain a check result;

[0105] D2. Determine the translation problem corresponding to the error type information;

[0106] D3. If the checking result indicates that the original translation information has the translation problem, the correct translation information is judged based on the translation problem to obtain a judgment result;

[0107] D4. If the judgment result is that the correct translation information does not have the translation problem, then determining that the error correction information has passed the review;

[0108] D5. If the judgment result is that the correct translation information still has the translation problem, it is determined that the error correction information review has failed.

[0109] In a specific embodiment, the original translation information is first subjected to a targeted check based on the error type information to obtain corresponding check results. For example, if the error type information is a lexical error, the original translation information is checked for accurate vocabulary usage, inappropriate word usage, or confusion of word meanings. If the error type information is a grammatical error, the grammatical structure of the original translation information is checked to ensure that it conforms to the grammatical rules of the target language. The translation problem corresponding to the error type information is then determined. For example, if the error type information is a grammatical error, the corresponding translation problem may be a missing sentence component, subject-verb inconsistency, or a tense error.

[0110] Next, the check results are analyzed. If the check result indicates that the original translation information contains the translation problem, that is, the original translation information does contain the translation problem corresponding to the error type pointed out by the user, the correct translation information is judged based on the translation problem to obtain a judgment result to check whether the correct translation information has resolved the translation problem. If the judgment result shows that the correct translation information does not have the translation problem, then the error correction information is reasonable and valid, and the error correction information is determined to have passed the review. If the judgment result shows that the correct translation information still has the translation problem, then the error correction information may be inaccurate or incomplete, and the error correction information is determined to have failed the review.

[0111] It can be seen that by gradually checking and judging the original translation information and the correct translation information, it is ensured that only reasonable and effective error correction information can be adopted, thereby continuously optimizing the translation results of the target software and providing users with more accurate translation services.

[0112] The step of checking the original translation information according to the error type information to obtain a check result specifically includes:

[0113] E1. Acquire grammatical rules and vocabulary information corresponding to the target language;

[0114] E2. If the error type information includes the grammatical error, checking the original translation information according to the grammatical rule to obtain a first checking result;

[0115] E3. If the error type information includes the vocabulary error, checking the original translation information according to the vocabulary information to obtain a second checking result;

[0116] E4. Obtaining context information corresponding to the target software;

[0117] E5. If the error type information includes the inappropriate context, checking the original translation information according to the context information to obtain a third checking result;

[0118] E6. Determine the inspection result according to at least one of the first inspection result, the second inspection result, and the third inspection result.

[0119] In a specific embodiment, different languages have their own unique grammatical rules and rich vocabulary systems. The grammatical rules and vocabulary information corresponding to the target language can be extracted from a preset language database. If the error type information includes grammatical errors, the original translation information is checked according to the grammatical rules, for example, to check whether the subject and predicate are consistent, whether the tense is correct, and whether the sentence components are complete, thereby obtaining a first check result. If the error type information includes lexical errors, the original translation information is checked for accurate vocabulary usage based on the lexical information, for example, to check the spelling of the vocabulary, the accuracy of the word meaning, and the rationality of the collocation, thereby obtaining a second check result.

[0120] Next, the vehicle diagnostic software's historical diagnostic records, professional terminology database, common fault descriptions, and other data can be analyzed to determine the contextual information corresponding to the vehicle diagnostic software. If the error type information includes inappropriate context, this contextual information is combined to evaluate whether the original translation conforms to the expression conventions and semantic requirements of the scenario. For example, in a vehicle diagnostic scenario, "fault" is generally more professional and accurate than "problem," thereby obtaining a third inspection result. Finally, the inspection result is determined based on at least one of the first, second, and third inspection results.

[0121] It can be seen that by checking multiple aspects such as grammar, vocabulary and context, the accuracy and appropriateness of the original translation information can be comprehensively and carefully evaluated, providing a reliable basis for subsequent error correction and review, and helping to improve the quality of the target software translation results.

[0122] Step S305: If the error correction information fails to pass the review, the translation output result is determined to be the target translation result.

[0123] Specifically, if the correction information provided by the user fails to pass review, indicating that the correction information is unreasonable, such as errors, failure to accurately identify the problem with the original translation, or inaccurate correct translation information, the original translation output will be maintained as the final target translation result. This ensures the stability and reliability of the translation results and avoids arbitrary changes to the translation results due to unreasonable corrections, which may lead to more serious errors or misunderstandings.

[0124] Step S306: If the error correction information passes the review, the translation output result is adjusted according to the error correction information to obtain the target translation result, and reward points corresponding to the error correction information are issued to the user.

[0125] The reward points are used for shopping in the shopping area of the target software, the translation output result is adjusted according to the error correction information to obtain the target translation result, and the reward points corresponding to the error correction information are issued to the user. Specifically, the steps include:

[0126] F1. Adjusting the original translation information according to the correct translation information to obtain a reference translation result;

[0127] F2. Verifying the reference translation result. If the verification passes, determining the reference translation result as the target translation result; if the verification fails, re-adjusting the reference translation result.

[0128] F3. Determine the reward level corresponding to the error type information;

[0129] F4. Distribute the reward points corresponding to the reward level to the user.

[0130] In a specific embodiment, first, the original translation information is modified and adjusted according to the correct translation information to obtain a reference translation result. Then, the reference translation result is verified, such as rechecking whether the grammatical rules and vocabulary usage are accurate, whether they conform to the context of the target software, etc., or comparing with professional language dictionaries, industry standard terminology libraries, etc., or evaluating the accuracy and fluency of the translation through a preset machine learning model, which is not specifically limited here. If the reference translation result meets the corresponding requirements during the verification process, it means that the adjusted reference translation result is accurate and reliable, and the reference translation result can be determined as the final target translation result. If the reference translation result does not meet the corresponding requirements during the verification process, such as there are still grammatical errors, inappropriate vocabulary or it does not conform to the context, the reference translation result is adjusted and verified again until the verification is passed.

[0131] Next, a reward level rule table is pre-set to clarify the reward levels corresponding to different error types. When the error correction information is reviewed and approved, the corresponding reward level is found from the reward level rule table based on the error type information. For example, the reward level rule table stipulates that grammatical errors correspond to level one rewards, vocabulary errors correspond to level two rewards, inappropriate contexts correspond to level three rewards, etc., which are not specifically limited here. Finally, the corresponding reward points are determined based on the reward level, and the reward points are distributed to the user's account. Among them, the reward points are used to shop in the shopping area of the target software and can be redeemed for related goods or services, such as purchasing vehicle diagnostic tool models, software usage tutorial materials, etc., which are not specifically limited here.

[0132] It can be seen that the accuracy of the final translation is ensured by adjusting and verifying the translation results, and the reward points mechanism stimulates users' enthusiasm for participating in error correction, which helps to continuously improve the translation quality and user experience of the target software.

[0133] It should be noted that users can access the shopping area through the target software and browse the various products and services on display. When a user selects a desired product or service, the target software automatically checks the user's points balance in response to the user clicking the redeem button. If sufficient points are available, the corresponding points are deducted to complete the redemption. If insufficient points are available, the user is prompted and guided to increase their points by earning more rewards. For physical goods, users must enter a delivery address, and the target software will arrange delivery. For virtual goods, such as tutorials and e-books, the target software will immediately push the relevant materials to the user after a successful redemption, allowing them to learn and use them at any time. To encourage timely consumption, points can be valid for one year; unused points will automatically be reset. For physical goods, the software platform updates inventory information in real time. If a product is out of stock, users cannot redeem it and must wait for the platform to restock it. Furthermore, the target software can set reminders to notify users who follow the product when it is restocked.

[0134] In one possible embodiment, during the use of the target software, when a user corrects a translation, the target software will record the correction information and allow other users to view these records, so that more users can learn from others' corrections and avoid repeating mistakes, while also promoting knowledge sharing and communication. In addition, multiple users can jointly participate in the review of the translation content. Each user can express their own review opinions, and the target software will synthesize these opinions according to certain rules to determine whether the translation content has passed the review, thereby improving the accuracy and efficiency of the review. It should be noted that when the user views the translation content, the target software will display a list of correction records for the content. In response to the user clicking on a specific correction record, more detailed correction information can be displayed, including the nickname of the correcting user, the correction content, and the correction time. Among them, the target software will automatically assign the translation content to multiple review users, and these multiple review users can review the translation content and submit review opinions and review results (pass or fail). The target software can synthesize the opinions of all review users according to preset rules (such as the majority voting principle) to obtain the final review result.

[0135] In one possible embodiment, a scheduled task framework can be used to schedule an update every 1-2 months, extracting approved error correction text information. The target software can prompt the user that updateable error correction text information exists and provide the option to update or not. If the user chooses to update, the target software will update the latest error correction text information locally; if not, the target software will maintain the current version of the text information.

[0136] For easier understanding, see Figure 7 , Figure 7 This is a flowchart of an error correction review provided by an embodiment of the present application, wherein, on the user side, the feedback content corresponding to the error correction information can be submitted through the feedback menu. The background management side makes a preliminary judgment through the feedback error correction menu. After the preliminary judgment is passed, the reply information is sent to the user side and the corresponding reward points are issued. Among them, the user's point information can be viewed through the feedback error correction menu or the error correction management menu. If the preliminary judgment fails, the error correction information will be saved as an error correction record, and the status of the error correction record will be set to pending review.

[0137] Then, you can submit the correction record for further review through the correction button. In the background management side, the correction record is reviewed through the diagnostic correction menu. After the correction record is reviewed and approved, the status of the correction record is updated to the approved status, and the reward points are issued. Among them, the correction management menu can display the reward points issued, and the correction permission menu can be used to set users who are eligible for correction. For example, only users with a specific serial number can submit correction records, which makes it easy to adjust the permission configuration according to the actual situation and ensure that the correction work is carried out in an orderly manner.

[0138] The above mainly introduces the solution of the embodiment of the present application from the perspective of the execution process of the method side. It is understandable that, in order to realize the above functions, the electronic device includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in a hardware or computer software driven hardware manner depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0139] The embodiment of the present application can divide the functional units of the electronic device according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0140] In the case of dividing each functional module into corresponding functional modules, Figure 8 This is a functional module block diagram of a translation error correction device provided in an embodiment of the present application, which is applied to the control center of a target software, wherein the target software includes any of the following: vehicle diagnostic software, e-commerce shopping software, and map navigation software. The translation error correction device 800 includes an acquisition module 810, a generation module 820, a translation module 830, a review module 840, an output module 850, and an adjustment module 860, wherein:

[0141] The acquisition module 810 is used to acquire text content generated by the user during the use of the target software and determine the original language of the text content;

[0142] The generating module 820 is configured to obtain the target language required by the user in response to the user's translation instruction, and generate translation request information for translating the text content from the original language into the target language;

[0143] The translation module 830 is configured to translate the text content according to the translation request information to obtain a translation output result;

[0144] The review module 840 is used to obtain the user's error correction information for the translation output result and review the error correction information;

[0145] The output module 850 is configured to determine that the translation output result is a target translation result if the error correction information fails to pass the review;

[0146] The adjustment module 860 is used to adjust the translation output result according to the error correction information if the error correction information is approved, obtain the target translation result, and issue reward points corresponding to the error correction information to the user; the reward points are used to shop in the shopping area of the target software.

[0147] Optionally, in translating the text content according to the translation request information to obtain a translation output result, the translation module 830 is specifically configured to:

[0148] Determine the server corresponding to the target software;

[0149] Searching the local cache of the server according to the translation request information to determine whether a first text record exists in the local cache; the first text record corresponds to the text content;

[0150] If the first text record exists, determining, based on a preset mapping relationship between text records and translation results, that the translation result corresponding to the first text record is the first translation result;

[0151] If the language of the first translation result is the target language, determining the first translation result as the translation output result;

[0152] If the first text record does not exist or the language of the first translation result is not the target language, a third-party translation service provider performs translation according to the translation request information to obtain a second translation result, and determines the second translation result as the translation output result.

[0153] Optionally, in the aspect of translating the translation request information by a third-party translation service provider to obtain a second translation result, the translation module 830 is specifically configured to:

[0154] Preprocessing the text content to obtain a text to be translated;

[0155] Obtaining multiple translation models corresponding to the third-party translation service provider;

[0156] determining a first language combination based on the original language and the target language;

[0157] Determining a first translation model as a target translation model according to the first language combination; the first translation model is the translation model that is most suitable for the first language combination among the multiple translation models;

[0158] Extracting features from the text to be translated to obtain feature information;

[0159] The feature information is processed according to the target translation model to obtain the second translation result.

[0160] Optionally, in the aspect of obtaining the user's error correction information regarding the translation output result and reviewing the error correction information, the review module 840 is specifically configured to:

[0161] Obtaining original translation information in the translation output result;

[0162] In response to the user's error correction instruction, obtaining error type information and correct translation information corresponding to the original translation information;

[0163] generating error correction information according to the original translation information, the error type information, and the correct translation information;

[0164] Performing a format check on the error correction information; if the format of the error correction information is incomplete, marking the error correction information as pending to be completed to prompt the user to modify it;

[0165] If the format of the error correction information is complete, the error correction information is reviewed.

[0166] Optionally, the error type information includes at least one of the following: grammatical error, vocabulary error, and inappropriate context; in terms of reviewing the error correction information, the review module 840 is specifically configured to:

[0167] Checking the original translation information according to the error type information to obtain a check result;

[0168] Determining the translation problem corresponding to the error type information;

[0169] If the checking result indicates that the original translation information has the translation problem, the correct translation information is judged according to the translation problem to obtain a judgment result;

[0170] If the judgment result is that the correct translation information does not have the translation problem, then determining that the error correction information has passed the review;

[0171] If the judgment result is that the correct translation information still has the translation problem, it is determined that the error correction information review has failed.

[0172] Optionally, in terms of checking the original translation information according to the error type information to obtain a check result, the review module 840 is specifically configured to:

[0173] Obtaining grammatical rules and vocabulary information corresponding to the target language;

[0174] If the error type information includes the grammatical error, checking the original translation information according to the grammatical rule to obtain a first checking result;

[0175] If the error type information includes the vocabulary error, checking the original translation information according to the vocabulary information to obtain a second checking result;

[0176] Obtaining context information corresponding to the target software;

[0177] If the error type information includes the inappropriate context, checking the original translation information according to the context information to obtain a third checking result;

[0178] The inspection result is determined according to at least one detection result among the first inspection result, the second inspection result, and the third inspection result.

[0179] Optionally, in adjusting the translation output result according to the error correction information to obtain the target translation result, and issuing reward points corresponding to the error correction information to the user, the adjustment module 860 is specifically configured to:

[0180] Adjusting the original translation information according to the correct translation information to obtain a reference translation result;

[0181] Verifying the reference translation result, and if the verification passes, determining the reference translation result as the target translation result; if the verification fails, re-adjusting the reference translation result;

[0182] Determine a reward level corresponding to the error type information;

[0183] The reward points corresponding to the reward level are issued to the user.

[0184] As can be seen, by utilizing the server's local cache, the frequency of calls to third-party translation service providers is reduced, speeding up the translation process. By quickly reviewing user correction information and optimizing the translation results based on the correction information after approval, the accuracy of the translation is improved.

[0185] It should be noted that the specific implementation of each operation can adopt the corresponding description of the method embodiment shown above. The translation error correction device 800 can be used to execute the above method embodiment of the present application, which will not be described in detail.

[0186] An embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0187] The present application also provides a computer program product comprising a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may comprise an electronic device.

[0188] It should be noted that, for the above-mentioned various embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations. Those skilled in the art should know that this application is not limited by the order of the actions described, because some steps in the embodiments of the present application can be performed in other orders or simultaneously. In addition, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions, steps, modules or units involved are not necessarily required by the embodiments of the present application.

[0189] In the above embodiments, the embodiments of the present application have different focuses on the description of each embodiment. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0190] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

[0191] The steps of the method or algorithm described in the embodiments of the present application can be implemented in hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, which can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and storage medium can be located in an ASIC. In addition, the ASIC can be located in a terminal device or a management device. Of course, the processor and storage medium can also be present in a terminal device or a management device as discrete components.

[0192] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, they can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0193] The modules / units included in the devices and products described in the above embodiments may be software modules / units, hardware modules / units, or partly software modules / units and partly hardware modules / units. For example, for the devices and products applied to or integrated in the chip, the modules / units included therein may all be implemented in the form of hardware such as circuits, or at least part of the modules / units may be implemented in the form of software programs, which run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits; for the devices and products applied to or integrated in the chip module, the modules / units included therein may all be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (such as chip, circuit module, etc.) or different components of the chip module, or at least part of the modules / units may be It is implemented in the form of a software program, which runs on the processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in the form of hardware such as circuits; for various devices and products applied to or integrated in the terminal equipment, the various modules / units contained therein can be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or different components in the terminal equipment, or, at least some modules / units can be implemented in the form of a software program, which runs on the processor integrated inside the terminal equipment, and the remaining (if any) modules / units can be implemented in the form of hardware such as circuits.

[0194] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the embodiments of the present application. It should be understood that the above description is only a specific implementation method of the embodiments of the present application and is not intended to limit the scope of protection of the embodiments of the present application. Any modifications, equivalent replacements, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application should be included in the scope of protection of the embodiments of the present application.

Claims

1. A translation error correction method, characterized in that: A control center is applied to a target software, wherein the target software includes any one of the following: vehicle diagnostic software, e-commerce shopping software, and map navigation software. The method includes: Acquire text content generated by a user during use of the target software, and determine the original language of the text content; In response to the user's translation instruction, obtaining the target language required by the user, and generating translation request information for translating the text content from the original language into the target language; Translate the text content according to the translation request information to obtain a translation output result; Obtaining error correction information from the user regarding the translation output result, and reviewing the error correction information; If the error correction information fails to pass the review, determining the translation output result as the target translation result; If the error correction information is approved, the translation output result is adjusted according to the error correction information to obtain the target translation result, and reward points corresponding to the error correction information are issued to the user; the reward points are used to shop in the shopping area of the target software.

2. The method according to claim 1, wherein The step of translating the text content according to the translation request information to obtain a translation output result includes: Determine the server corresponding to the target software; Searching the local cache of the server according to the translation request information to determine whether a first text record exists in the local cache; the first text record corresponds to the text content; If the first text record exists, determining, based on a preset mapping relationship between text records and translation results, that the translation result corresponding to the first text record is the first translation result; If the language of the first translation result is the target language, determining the first translation result as the translation output result; If the first text record does not exist or the language of the first translation result is not the target language, a third-party translation service provider performs translation according to the translation request information to obtain a second translation result, and determines the second translation result as the translation output result.

3. The method according to claim 2, wherein The third-party translation service provider performs translation according to the translation request information to obtain a second translation result, including: Preprocessing the text content to obtain a text to be translated; Obtaining multiple translation models corresponding to the third-party translation service provider; determining a first language combination based on the original language and the target language; Determining a first translation model as a target translation model according to the first language combination; the first translation model is the translation model that is most suitable for the first language combination among the multiple translation models; Extracting features from the text to be translated to obtain feature information; The feature information is processed according to the target translation model to obtain the second translation result.

4. The method according to claim 1, wherein The obtaining of error correction information from the user regarding the translation output result and reviewing the error correction information includes: Obtaining original translation information in the translation output result; In response to the user's error correction instruction, obtaining error type information and correct translation information corresponding to the original translation information; generating error correction information according to the original translation information, the error type information, and the correct translation information; Performing a format check on the error correction information; if the format of the error correction information is incomplete, marking the error correction information as pending to be completed to prompt the user to modify it; If the format of the error correction information is complete, the error correction information is reviewed.

5. The method according to claim 4, wherein The error type information includes at least one of the following: grammatical error, vocabulary error, and inappropriate context; and the review of the error correction information includes: Checking the original translation information according to the error type information to obtain a check result; Determining the translation problem corresponding to the error type information; If the checking result indicates that the original translation information has the translation problem, the correct translation information is judged according to the translation problem to obtain a judgment result; If the judgment result is that the correct translation information does not have the translation problem, then determining that the error correction information has passed the review; If the judgment result is that the correct translation information still has the translation problem, it is determined that the error correction information review has failed.

6. The method according to claim 5, wherein The checking of the original translation information according to the error type information to obtain a checking result includes: Obtaining grammatical rules and vocabulary information corresponding to the target language; If the error type information includes the grammatical error, checking the original translation information according to the grammatical rule to obtain a first checking result; If the error type information includes the vocabulary error, checking the original translation information according to the vocabulary information to obtain a second checking result; Obtaining context information corresponding to the target software; If the error type information includes the inappropriate context, checking the original translation information according to the context information to obtain a third checking result; The inspection result is determined according to at least one detection result among the first inspection result, the second inspection result, and the third inspection result.

7. The method according to any one of claims 4 to 6, characterized in that The adjusting the translation output result according to the error correction information to obtain the target translation result, and issuing reward points corresponding to the error correction information to the user, includes: Adjusting the original translation information according to the correct translation information to obtain a reference translation result; Verifying the reference translation result, and if the verification passes, determining the reference translation result as the target translation result; if the verification fails, re-adjusting the reference translation result; Determine a reward level corresponding to the error type information; The reward points corresponding to the reward level are issued to the user.

8. A translation error correction device, characterized in that: A control center for target software, wherein the target software includes any of the following: vehicle diagnostic software, e-commerce shopping software, and map navigation software. The device includes an acquisition module, a generation module, a translation module, a review module, an output module, and an adjustment module, wherein: The acquisition module is used to acquire text content generated by the user during the use of the target software and determine the original language of the text content; The generating module is configured to obtain the target language required by the user in response to the translation instruction of the user, and generate translation request information for translating the text content from the original language into the target language; The translation module is configured to translate the text content according to the translation request information to obtain a translation output result; The review module is used to obtain the user's error correction information for the translation output result and review the error correction information; The output module is configured to determine that the translation output result is a target translation result if the error correction information fails to pass the review; The adjustment module is configured to adjust the translation output result according to the error correction information if the error correction information is approved, thereby obtaining the target translation result, and to issue reward points corresponding to the error correction information to the user; the reward points are used for shopping in the shopping area of the target software.

9. An electronic device, characterized in that: include: a processor, a memory, a communication interface, and one or more programs; The one or more programs are stored in the memory and configured to be executed by the processor, wherein the programs include instructions for executing the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 7.

Images