Vehicle cabin multilingual literature management method and system and medium
By obtaining a list of classical Chinese texts to be adapted in the vehicle cockpit software and using corpus query and translation engines to generate standard translations, the translation quality and efficiency issues in the multilingual translation of vehicle cockpit software were resolved, achieving efficient and accurate multilingual adaptation.
Patent Information
- Application Number
- CN202510793104.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-13
- Publication Date
- 2025-09-26
AI Technical Summary
Existing technologies rely on manual translation for multilingual translation of vehicle cockpit software, which has limited quality, insufficient translation resources, and is unable to provide accurate translations in a timely manner, resulting in translation omissions or errors, and an inability to efficiently complete language adaptation tasks.
By obtaining a list of classical Chinese texts to be adapted, the target translation is searched for using the corpus. If not found, a standard translation is generated through a translation engine and manual verification, and the corpus is updated to generate a formatted language data package to ensure that the translation can be directly used for vehicle cockpit software development.
It improves the accuracy and efficiency of multilingual translation, reduces manual intervention, ensures that translation results are directly applied to software development, and improves the automation level of the development process and the application accuracy of translation results.
Smart Images
Figure CN120706443A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of vehicle cockpit development, and in particular to a vehicle cockpit multilingual classical Chinese management method, device and medium. Background Art
[0002] With the diversification of the global automotive market, and especially the increasing popularity of smart cockpit technology, automotive cockpit software interfaces need to adapt to a growing number of languages and regions to meet the needs of global users. In practical applications, vehicle cockpit software needs to support multiple languages to ensure that users can understand and operate the information displayed during use.
[0003] Traditional multilingual adaptation solutions typically rely on manual translation or manually maintained language files. These methods require significant human involvement, and the quality of the translation is limited by the translator's skill and experience. Furthermore, with the increasing complexity of vehicle cockpit systems, the volume of textual content that needs to be processed during development and updates is enormous. This is especially true for text content in specific languages, which can lead to translation omissions or errors. For less commonly used languages, especially those in regional languages, existing technologies still face challenges with insufficient translation resources and inconsistent translation standardization.
[0004] Most multilingual translation solutions rely on static translation databases, requiring users to adapt by querying existing translations. However, when faced with new or updated content, traditional methods often fail to provide accurate translations in a timely manner or incur significant delays during the translation process. In some cases, finding a suitable translation within the existing corpus makes it impossible to efficiently complete the language adaptation task.
[0005] In addition, existing translation systems and databases do not fully consider the specific needs of vehicle cockpit software, and the translation results often cannot be directly used for software development, resulting in additional post-adaptation workload. Summary of the Invention
[0006] The present invention aims to address, at least to some extent, one of the technical problems in the related art. To this end, the present invention aims to provide a method, system, and medium for managing multilingual text in vehicle cockpits. This approach improves the accuracy and efficiency of multilingual translation, reduces manual intervention, and ensures that translation results can be directly applied to vehicle cockpit software development.
[0007] To achieve the above objectives, a first embodiment of the present invention provides a vehicle cabin multilingual text management method, comprising:
[0008] Obtaining a list of Chinese languages to be adapted; the list of Chinese languages to be adapted records the Chinese languages to be adapted presented in the vehicle cockpit software and the target languages to be converted from the Chinese languages to be adapted;
[0009] Searching a corpus for a target translation of the Chinese classical text to be adapted in the target language; the corpus records the association between the Chinese classical text and translations in multiple languages;
[0010] If the target translation cannot be found in the corpus, a standard translation of the Chinese classical language to be adapted in the target language is generated based on a translation engine interface and manual verification, and the standard translation is updated in the corpus;
[0011] If the target translation is found in the corpus, the target translation is converted into a formatted language data packet for developing vehicle cockpit software in the target language.
[0012] In addition, the vehicle cockpit multilingual classical Chinese management method of the above embodiment of the present invention may also have the following additional technical features:
[0013] According to one embodiment of the present invention, the corpus associates the Chinese text with the translation based on markup coding, and searching the corpus for the target translation of the Chinese text to be adapted in the target language includes:
[0014] The markup code of the Chinese classical language to be adapted is searched in the corpus, and the target translation is determined according to the markup code.
[0015] According to one embodiment of the present invention, the target translation cannot be found in the corpus, including:
[0016] It is determined that the Chinese classical language to be adapted does not exist in the corpus, or it is determined that the target translation is missing from the corpus.
[0017] According to one embodiment of the present invention, generating a standard translation of the Chinese classical text to be adapted in the target language based on a translation engine interface and manual verification includes:
[0018] Calling multiple translation engine interfaces to translate the Chinese classical language to be adapted, and obtaining multiple machine translations;
[0019] Performing multimodal quality assessment on the plurality of machine translations, and selecting at least one candidate translation based on the quality assessment results;
[0020] Manual verification is performed on at least one of the candidate translations; wherein the standard translation is the candidate translation that has passed the verification.
[0021] According to one embodiment of the present invention, the list of languages to be adapted includes at least two Chinese languages to be adapted; and the method further includes:
[0022] Generate a multilingual adaptation intermediate table based on the query result of the Chinese classical language to be adapted in the corpus; if the target translation cannot be found in the corpus, mark the Chinese classical language to be adapted as being in a translation-missing state in the multilingual adaptation intermediate table; if the target translation is found in the corpus, record the target translation of the Chinese classical language to be adapted in the multilingual adaptation intermediate table;
[0023] Based on the multi-language adaptation intermediate table, a formatted language data packet for developing vehicle cockpit software in the target language is output.
[0024] To achieve the above-mentioned objectives, a second embodiment of the present invention proposes a vehicle cockpit multilingual text management system, comprising an intelligent query module, a translation and verification module, and a structured data generation module;
[0025] The intelligent query module is used to obtain a list of Chinese texts to be adapted and search a corpus for target translations of the Chinese texts to be adapted in the target language; the list of Chinese texts to be adapted records the Chinese texts to be adapted presented in the vehicle cockpit software and the target languages into which the Chinese texts to be adapted are converted; the corpus records the associations between Chinese texts and translations in multiple languages;
[0026] The translation and verification module is used to generate a standard translation of the Chinese classical text to be adapted in the target language based on the translation engine interface and manual verification when the target translation cannot be found in the corpus, and update the standard translation into the corpus;
[0027] The structured data generation module is configured to convert the target translation into a formatted language data packet for developing vehicle cockpit software in the target language when the target translation is found in the corpus.
[0028] In addition, the vehicle cockpit multilingual text management system of the above embodiment of the present invention may also have the following additional technical features:
[0029] According to one embodiment of the present invention, the corpus associates the Chinese text with the translation based on tag encoding;
[0030] The intelligent query module is configured to query the markup code of the Chinese classical language to be adapted in the corpus, and determine the target translation according to the markup code.
[0031] According to an embodiment of the present invention, the failure to find the target translation in the corpus includes the absence of the to-be-adapted Chinese classical language in the corpus, or the determination that the target translation is missing from the corpus.
[0032] According to one embodiment of the present invention, the list of languages to be adapted includes at least two Chinese languages to be adapted;
[0033] The intelligent query module is configured to generate a multilingual adaptation intermediate table;
[0034] If the target translation cannot be found in the corpus, the Chinese classical language to be adapted is marked as missing in the multilingual adaptation intermediate table; if the target translation is found in the corpus, the target translation of the Chinese classical language to be adapted is recorded in the multilingual adaptation intermediate table; the multilingual adaptation intermediate table provides input for the translation and verification module and the structured data generation module.
[0035] To achieve the above objectives, a third embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the steps of the above-mentioned vehicle cockpit multilingual textual management method.
[0036] The vehicle cockpit multilingual text management method, system and medium of the embodiment of the present invention can effectively manage and process the multilingual text in the vehicle cockpit software by obtaining the list of texts to be adapted and querying it in the corpus, thereby ensuring the accuracy and consistency of translation between different languages. If the target translation cannot be found in the corpus, a mechanism based on the translation engine interface and manual verification is provided, so that a standard translation can be generated and updated to the corpus, avoiding the duplication and error risks of manual intervention and improving the efficiency and quality of translation. In the case where the target translation is found, the translation is converted into a formatted language data packet to ensure that the translation can be directly used in the development of vehicle cockpit software, meet development requirements, and improve work efficiency during the development process. Through this series of technical means, the automation level of vehicle cockpit multilingual text management and the application accuracy of translation results can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0037] Figure 1 1 is a flow chart of a method for managing multilingual text in a vehicle cockpit according to one embodiment;
[0038] Figure 2 A schematic diagram of a process for generating a standard translation in one embodiment;
[0039] Figure 3 A schematic diagram of a process for generating a multilingual adaptation intermediate table in one embodiment;
[0040] Figure 4Schematic diagram of the architecture of a multilingual text management system for a vehicle cockpit in one embodiment. DETAILED DESCRIPTION
[0041] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.
[0042] The following describes in detail the implementation details of the technical solutions of the embodiments of the present application.
[0043] In one embodiment, Figure 1 As shown, a flowchart of a method for managing multilingual text in a vehicle cockpit is provided. The method may include the following steps:
[0044] Step S101: Obtain a list of classical Chinese languages to be adapted.
[0045] First, you need to obtain a list of languages to be adapted. This list includes all the Chinese languages presented in the vehicle cockpit software, as well as the target languages corresponding to these Chinese languages. The list of languages to be adapted can be generated by automated tools or manually checking the Chinese languages in the vehicle cockpit software, and generating an adaptation list based on specific development requirements and target languages. The list of languages to be adapted not only contains the specific Chinese languages, but also the target language into which each Chinese language needs to be translated.
[0046] In actual applications, Chinese classical language is the classical language used in vehicle cockpit software developed in a Chinese environment. These Chinese classical languages are usually texts that have undergone multiple version iterations and have been developed and optimized in a Chinese environment. In order to support the development of vehicle cockpit software in different languages, these Chinese classical languages will be used as source languages to generate translations in the corresponding languages. In addition, the Chinese classical languages in the list of classical languages to be adapted can also include Chinese classical languages presented in different versions of vehicle cockpit software. Taking into account the update iterations of software versions, some Chinese classical languages may change in the new version, so the list needs to cover all relevant classical language version information.
[0047] Based on this, it is possible to accurately identify the classical Chinese that needs to be translated, and provide clear classical Chinese source and target language information for subsequent translation operations.
[0048] Step S102: searching the corpus for a target translation of the Chinese classical text to be adapted in the target language.
[0049] Based on the Chinese texts in the list of texts to be adapted, a pre-established corpus is searched. This corpus contains Chinese texts and their corresponding translations in multiple target languages, and records the relationships between the Chinese texts and the target translations. Once the Chinese text to be adapted is obtained, a search is performed within the corpus to find the corresponding translation in the target language for the text in the list of texts to be adapted. During the search process, techniques such as tag encoding and text matching algorithms are used to ensure fast and accurate matching of the target translation.
[0050] In practical applications, the matching of corpus queries and target translations can support real-time multilingual adaptation of cockpit software in scenarios such as classical Chinese interaction, graphical interface, and Internet of Vehicles services.
[0051] In one embodiment, the corpus associates the Chinese text with the translation based on the markup code, searches the corpus for the markup code of the Chinese text to be adapted, and determines the target translation according to the markup code.
[0052] The association between the Chinese texts in the corpus and the target translations is achieved not only through direct text matching but also through tag encoding, further enhancing query accuracy and efficiency. To ensure strong association between the Chinese texts and their target language translations, the corpus employs a tag encoding binding mechanism. Under this mechanism, each Chinese text in the corpus is assigned a unique tag encoding that clearly identifies its correspondence with its corresponding translation. This tag encoding binding mechanism ensures a close connection between each Chinese text and its corresponding target language translation. This mechanism not only ensures consistency between the Chinese texts and their single-language translations but also supports the management and updating of multilingual translations, making it suitable for version control of corpora for global vehicle models. For example, the Chinese text "start the engine" is bound to its Spanish translation "start the engine" through tag encoding, ensuring precise correspondence between translations in different languages and avoiding confusion during the translation process.
[0053] Based on this, when searching for a target translation, the tag code serves as a unique identifier for the Chinese text, enabling rapid extraction of relevant information through algorithms or database indexing. Once the tag code is found, the target translation of the Chinese text is further determined based on the code. A precise matching algorithm ensures a strict correspondence between the Chinese text and the target translation, avoiding semantic bias that could result from fuzzy matching.
[0054] In this embodiment, the tag encoding binding mechanism effectively eliminates errors in cross-language matching and enables seamless connection during multilingual translation, thereby reducing the error rate of cross-language matching to near zero. It can ensure the accuracy and efficiency of multilingual translation during software development, thereby significantly improving the development and adaptation speed of vehicle cockpit software.
[0055] In one embodiment, the failure to find the target translation in the corpus includes: determining that the Chinese classical language to be adapted does not exist in the corpus, or determining that the target translation is missing in the corpus.
[0056] There are two specific scenarios where the target translation cannot be found in the corpus. The first is when the Chinese text to be adapted does not exist in the corpus. Therefore, when searching the corpus, the first step is to determine whether the Chinese text to be adapted already exists in the corpus. If the Chinese text does not exist at all, this indicates that the Chinese text and its corresponding translation have not yet been included, confirming that the target translation cannot be found in the corpus.
[0057] The second scenario is: the corpus contains the Chinese text to be adapted, but does not store the translation of the Chinese text in the target language, that is, there is a missing translation. Specifically, the corpus may contain translations of the Chinese text to be adapted in certain languages. For example, the corpus records the English translation of the Chinese text, but when querying the target language, such as Spanish, it is found that the corpus only contains the English translation of the Chinese text, but lacks the Spanish translation. In this case, although the corpus contains records of the Chinese text, the target translation cannot be found because the translation in the target language is missing.
[0058] Step S103: If the target translation cannot be found in the corpus, a standard translation of the Chinese classical text to be adapted in the target language is generated based on the translation engine interface and manual verification, and the standard translation is updated to the corpus.
[0059] If the target translation cannot be found in the corpus, the process of generating a standard translation will be triggered. It is necessary to generate a standard translation of the Chinese classical language to be adapted in the target language based on the translation engine interface and manual verification.
[0060] To generate accurate, contextually accurate, and standardized translations, machine translation is typically performed by invoking one or more translation engines. These engines translate the Chinese text based on the provided Chinese text and the target language. While machine translation can quickly translate Chinese text, the resulting translations may not fully conform to the target language's conventions or may deviate from the terminology used in specific technical fields.
[0061] In order to further ensure the quality of standard translations, manual verification is combined with machine translation. The manual verification step is usually carried out by personnel with professional language knowledge. They will check whether the results of machine translation conform to the language habits, technical terms and context requirements of the target language. If the translation results are inaccurate, unnatural or ambiguous, manual verification personnel can adjust or modify the translation according to actual language habits until a high-quality standard translation is achieved. This process not only guarantees the accuracy of the translation content, but also ensures that the translation results can meet the requirements of the target language culture and industry standards.
[0062] After machine translation and manual verification, the resulting standard translation is added to the corpus and serves as a reference for future translations of similar classical Chinese texts. These updated standard translations not only support the current translation task but also serve as a valuable resource in the corpus for subsequent translations of the same or similar classical Chinese texts, thereby continuously optimizing and enriching the corpus.
[0063] In one embodiment, Figure 2 The following is a flow chart of generating a standard translation, which may include the following steps:
[0064] Step S201: Call multiple translation engine interfaces to translate the Chinese classical text to be adapted, and obtain multiple machine translations.
[0065] Here, multiple translation engine interfaces are called upon, utilizing different machine translation technologies to translate the Chinese text to be adapted. In practice, integrating multiple mainstream translation engines ensures that the Chinese text is translated from diverse algorithmic perspectives. Each translation engine interface converts the Chinese text to be adapted into the target language, generating multiple machine translations. These machine translations, sourced from different translation engines, typically employ varying translation styles and terminology, providing a rich set of translation options for subsequent quality assessment.
[0066] Step S202 : performing multimodal quality assessment on a plurality of machine translations, and screening to obtain at least one candidate translation based on the quality assessment results.
[0067] This step evaluates the quality of multiple machine translations and selects the best translation based on the quality assessment results. The multimodal quality assessment process assesses each machine translation across multiple dimensions, including grammatical accuracy, semantic correctness, fluency, and contextual consistency. During the assessment process, automated quality scoring tools are combined with manually defined criteria to measure translation quality. Based on the quality assessment results for each machine translation, at least one candidate translation with high quality is selected from all machine translations.
[0068] Step S203: Manually verify at least one candidate translation.
[0069] Manual reviewers review the selected translation candidates to ensure they adhere to the target language's linguistic conventions, cultural context, and domain-specific terminology. Manual review, typically conducted by individuals with specialized linguistic expertise or domain experts, carefully examines each candidate for accuracy, identifying grammatical errors, unnatural expressions, and potential cultural mismatches.
[0070] It should be noted that translations that pass verification (i.e., translations that are confirmed to have no issues) will be used as standard translations and updated to the corpus for future use. This standard translation will be used for official releases and support multilingual text adaptation in software development.
[0071] In step S104 , if the target translation is found in the corpus, the target translation is converted into a formatted language data packet for developing vehicle cockpit software in the target language.
[0072] If the target translation is successfully found in the corpus, it will be used directly for subsequent processing. This translation will be converted into a formatted language package that meets the requirements for vehicle cockpit software development. This formatted language package is generated based on the development requirements of the target language. This package aligns the translated target translation with the vehicle cockpit software development needs, thus supporting the software development process.
[0073] In actual applications, when generating formatted language data packages, an appropriate template can be selected based on the development requirements of the target language. The choice of template is customized according to the specific needs of the development framework. By selecting an appropriate template, the structure and format of various text elements can be predefined, allowing for more efficient generation of data packages that meet the requirements when adapting to multiple languages. After selecting a template, automated format verification is performed. Format verification ensures that the generated data package complies with syntax specifications, encoding requirements, and other development standards, ensuring smooth operation during subsequent development. After format verification, the data package can be used directly for development without the need for additional manual processing or adjustments. This process reduces manual intervention by developers, improves development efficiency, and minimizes the impact of formatting issues and translation errors on development progress and quality.
[0074] The specific format of the formatted language data package can be selected according to different development platforms and technical requirements. Common formats include XML format, JSON format, etc. During the development process, the formatted language data package will be directly connected to the front-end interface of the software to ensure that the target translation can be accurately displayed on the interface. In actual applications, the formatted language data package supports the organization of nested structures to adapt to the hierarchical text layout in complex interfaces, and also supports the definition and binding of placeholder variables to facilitate language adaptation of dynamic content. In addition, the system also has multi-language version control capabilities, which can uniformly manage the translation status and version information in each language, reducing manual coding errors made by programmers during the language file configuration process.
[0075] During the development of vehicle cockpit software in the target language, developers simply import formatted language data packages into the development environment, which are automatically recognized and processed by the development platform. This allows developers to customize the interface text display as needed, ensuring that all classical Chinese within the vehicle cockpit software complies with the target language specifications and is presented correctly to end users. Because the formatted language data packages are pre-organized and tailored to development needs, developers can quickly implement multilingual adaptation and display within the vehicle cockpit software, improving development efficiency and accuracy while avoiding software display issues caused by inconsistent formatting or translation errors.
[0076] Ultimately, the pre-organization and standardization of formatted language data packages significantly reduces the need for text format conversion or manual adjustments, thereby reducing the burden on developers and ensuring the consistency and stability of different language versions of vehicle cockpit software. The automation and standardization of this process not only improves development efficiency but also ensures high-quality software deployment worldwide.
[0077] In one embodiment, Figure 3 A schematic diagram of the process of generating a multilingual adaptation intermediate table is shown, which may include the following steps:
[0078] Step S301: Generate a multilingual adaptation intermediate table based on the query results of the Chinese classical language to be adapted in the corpus.
[0079] When the list of adapted languages contains at least two Chinese languages to be adapted, a multilingual adaptation intermediate table is needed to manage the processing of the Chinese languages to be adapted. Specifically, each Chinese language to be adapted in the list of adapted languages needs to be queried in the corpus and a multilingual adaptation intermediate table is generated. During the query process, if the target translation corresponding to the Chinese language to be adapted cannot be found in the corpus, the Chinese language will be marked as missing in the intermediate table. On the contrary, if the target translation is successfully found in the corpus, the translation and the corresponding Chinese language will be recorded one by one in the intermediate table.
[0080] The generated multilingual adaptation intermediate table stores the relationship between each target language translation and each target language translation. If some target translations are missing, these target language translations are marked as missing in the multilingual adaptation intermediate table. In subsequent steps, the standard translation generation mechanism for these target language translations is triggered based on the missing translation status marked in the multilingual adaptation intermediate table.
[0081] This process ensures that the status of all Chinese texts to be adapted can be clearly reflected in the intermediate table, providing an accurate basis for subsequent translation and software development.
[0082] Step S302 : outputting a formatted language data packet of the vehicle cockpit software in the target language based on the multilingual adaptation intermediate table.
[0083] Based on the generated multilingual adaptation intermediate table, formatted language data packages are output to support vehicle cockpit software development in the target languages. This step extracts each target translation from the intermediate table and converts it into a formatted language package that meets the requirements of vehicle cockpit software development, further facilitating smooth multilingual adaptation. This intermediate table enables precise translation management for different target languages, ensuring translation consistency and accuracy, while also significantly supporting vehicle cockpit software development.
[0084] Based on this, through the management of the multilingual adaptation intermediate table, each translation status in the development process is clearly recorded, and various links such as translation, verification, and formatting can be efficiently coordinated, greatly improving development efficiency and ensuring the high-quality delivery of the final multilingual software.
[0085] In the above embodiment, by efficiently querying the corpus, it is ensured that each Chinese classical language to be adapted can accurately obtain the translation in the target language, thereby ensuring the language accuracy and consistency of the vehicle cockpit software. In the case of missing translations in the corpus, the combination of the translation engine interface and manual verification can not only generate standard translations, but also update them to the corpus, continuously enrich the corpus content, and further improve the accuracy and quality of the translation. In addition, the use of formatted language data packets to directly import the translation results into the development environment avoids the problems of inconsistent text formats or translation errors that occur in the traditional development process, greatly improving development efficiency and accuracy. Through the combination of this series of technical means, a closed-loop classical language management mechanism from corpus query, missing translation completion to formatted output is established, and multilingual classical language management is deeply embedded in the entire life cycle of cockpit application development, ensuring the efficiency and stability of the cockpit software of global models in multilingual adaptation, and optimizing the development process and cost.
[0086] In one embodiment, Figure 4This is a schematic diagram of the architecture of a multilingual Chinese language management system for vehicle cockpits. The management system includes an intelligent query module, a translation and verification module, and a structured data generation module. The system's modular architecture works together to achieve efficient query, intelligent translation, manual verification, and formatted output of the Chinese language to be adapted. It is suitable for cockpit software development processes targeting the multilingual market.
[0087] The intelligent query module is configured to receive and parse a list of Chinese texts to be adapted, which contains several Chinese texts to be displayed in the vehicle cabin and their corresponding target language information. Upon receiving the list, the intelligent query module automatically identifies each Chinese text to be adapted and, based on the matching of the Chinese text to the target language, initiates a corresponding query request within a pre-defined corpus. This corpus contains a large number of Chinese texts and their standard translations in multiple target languages. The intelligent query module uses a precise matching algorithm to determine whether the target translation already exists in the corpus.
[0088] When the intelligent query module determines that it cannot obtain the translation of the Chinese text to be adapted in the target language from the corpus, it will pass the Chinese text to be adapted to the translation and verification module, which will trigger the process of generating a standard translation.
[0089] The translation and verification module first calls multiple translation engine interfaces, so that the translation engine will translate the Chinese text according to the provided Chinese text to be adapted and the target language. Because the translation generated by machine translation may not fully conform to the language habits of the target language, or there may be deviations in the use of terminology in specific technical fields. In order to further ensure the quality of standard translations, the translation and verification module also introduces manual verification, which is manually reviewed by personnel with professional language knowledge. The translation that passes the verification is marked as the standard translation of the Chinese text in the target language, and is synchronously written into the corpus through the system interface to keep the corpus content dynamically updated and version controllable.
[0090] In practice, to improve data processing efficiency, a multimodal quality assessment is performed on multiple machine translations generated by the translation engine. This process assesses each machine translation across multiple dimensions, including grammatical accuracy, semantic correctness, fluency, and contextual consistency. Based on the quality assessment results of each machine translation, at least one candidate translation with high translation quality is selected from all machine translations. This at least one selected candidate translation is then manually reviewed for accuracy, carefully checking for grammatical errors, unnatural expressions, or potential cultural mismatches, thereby determining the standard translation of classical Chinese.
[0091] For Chinese classical texts for which the target translation already exists in the corpus, the system passes the data to the structured data generation module. This processing module retrieves the target translation from the corpus and converts it into a formatted language data package that meets the requirements of vehicle cockpit software development. The generated data package can be directly imported into the cockpit software's multilingual resource files, enabling rapid deployment and one-click adaptation of multilingual interface content.
[0092] In practice, the structured data generation module selects appropriate templates based on the development requirements of the target language and predefines the structure and format of various text elements to ensure that the resulting data package is fully compatible with the target software development environment. The specific format of the formatted language data package can be selected based on different development platforms and technical requirements. Common formats include XML and JSON.
[0093] The multilingual text management system for vehicle cockpits in this embodiment utilizes multiple modules to form a closed-loop process, from extracting original Chinese text to translation, verification, and structured output. This system is suitable for global vehicle software development, where adaptation requirements fluctuate frequently. The system dynamically expands the corpus while avoiding the inefficiencies and errors associated with manual translation and format integration in traditional processes. Its high degree of automation and adaptability significantly improves the efficiency and quality control of multilingual vehicle cockpit software development.
[0094] In one embodiment, each Chinese text in the corpus is assigned a unique tag code, which identifies the relationship between the text and its corresponding translations in multiple target languages. This tag code is a unique identifier generated internally by the system. It is non-repeatable and language-neutral, avoiding redundant parsing of Chinese semantics and simplifying the logical complexity of cross-language querying and management.
[0095] When the intelligent query module receives a Chinese text from the list of texts to be adapted, it first searches the corpus for the markup code corresponding to the Chinese text. After obtaining the markup code, the intelligent query module locates all target translation information associated with it in the corpus based on the code.
[0096] In practical applications, this tag encoding mechanism avoids semantic bias or query errors caused by fuzzy matching based on string content. In multilingual translation scenarios, a unified tag encoding is used to create a one-to-one or one-to-many mapping relationship between classical Chinese and translations in different languages, thus supporting concurrent multilingual management and ensuring the consistency and accuracy of translation calls.
[0097] In one embodiment, the system determines whether the target translation of the Chinese classical text to be adapted in the target language can be queried in the corpus through the intelligent query module, and accordingly determines whether to trigger the translation and verification module. Among them, the situation where the target translation cannot be queried can be divided into two categories:
[0098] The first category of situation is that the Chinese classical text to be adapted itself does not exist in the corpus. During the query process, the system fails to retrieve the Chinese classical text to be adapted in the corpus, indicating that the Chinese classical text to be adapted has not been included in the corpus management. In this case, it is confirmed that the Chinese classical text does not exist in the corpus, and the translation and verification module needs to generate and supplement the standard translation of this Chinese classical text to be adapted.
[0099] The second category of situation is that the Chinese classical text to be adapted exists in the corpus, but the translation record of this classical text in the target language is missing. This means that the system successfully retrieves the translation corresponding to the Chinese classical text to be adapted in the corpus, but it does not include the standard translation entry bound to the target language. For example, for the Chinese text "start the engine", the corpus records its Spanish translation "start the engine", but the German translation is missing. In such cases, although the Chinese classical text has been included in the corpus, it is still considered that the target translation is missing.
[0100] Based on this, the system can accurately and comprehensively identify the Chinese classical texts that need to supplement the translation content, ensure that the translation and verification module starts the translation process in the truly missing scenarios, thereby improving the efficiency and necessity of the translation generation, avoiding redundant translation or repeated input, and ensuring the intelligence and accuracy of the multi-language translation process for the vehicle cockpit.
[0101] In one embodiment, the list of classical texts to be adapted contains at least two Chinese classical texts to be adapted. The system queries the corpus item by item for each Chinese classical text in this list through the intelligent query module, and generates a multi-language adaptation intermediate table based on this, which is used to centrally record the query results and guide the subsequent translation processing and data packet generation.
[0102] Specifically, when the intelligent query module fails to retrieve the target translation of a certain Chinese classical text to be adapted in the corpus (for example, the Chinese classical text to be adapted is missing in the corpus or only the translation of the Chinese classical text to be adapted in other languages exists), the Chinese classical text to be adapted is marked as "translation missing" in the multi-language adaptation intermediate table, so that the subsequent translation and verification module can perform the operation of generating the standard translation targeted. For the Chinese classical texts whose target translations can be queried in the corpus, the system directly records their corresponding target translations in the intermediate table.
[0103] The generated multilingual adaptation intermediate table serves as a key intermediate data structure in the system. Its output results will serve as the input source for the translation and verification module to identify Chinese classical texts that require additional translation. It also provides basic data for the structured data generation module, so that the existing target translations can be uniformly constructed into formatted language data packages in the target language.
[0104] Through this intermediate table mechanism, the system can batch process queries and status management of multiple Chinese texts, improving the automation and adaptation efficiency of the multilingual translation process. It is particularly suitable for vehicle cockpit software development scenarios for the global market.
[0105] In the above-mentioned embodiment, the vehicle cockpit multilingual text management system establishes a closed-loop text management mechanism from corpus query, missing translation completion, to formatted output by integrating an intelligent query module, a translation and verification module, and a structured data generation module. This system not only automatically identifies whether the target language translation exists in the corpus, but also, in the absence of translations, it leverages the translation engine and manual verification process to complete high-quality translations. It also dynamically updates the corpus and continuously optimizes corpus resources. With technical advantages such as high intelligence, strong translation consistency, and high adaptation efficiency, it is particularly suitable for cockpit software development scenarios targeting multiple languages and vehicle models. It significantly improves the standardization and automation of multilingual content management, reduces maintenance costs, and ensures the consistency and correctness of language content across language versions.
[0106] In one embodiment, a computer storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a method for managing multilingual text in a vehicle cabin is implemented.
[0107] It should be noted that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device), or in conjunction with such instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system, apparatus, or device, or in conjunction with such instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion having one or more wires (electronic device), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner if necessary, and then storing it in a computer memory.
[0108] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.
[0109] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
[0110] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.
[0111] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.
Claims
1. A vehicle cockpit multilingual text management method, characterized by: include: Get the list of classical Chinese to be adapted; The list of Chinese languages to be adapted records the Chinese languages to be adapted presented in the vehicle cockpit software and the target languages to be converted from the Chinese languages to be adapted; Searching the corpus for a target translation of the Chinese classical text to be adapted in the target language; The corpus records the relationship between classical Chinese and its translations in multiple languages; If the target translation cannot be found in the corpus, a standard translation of the Chinese classical language to be adapted in the target language is generated based on a translation engine interface and manual verification, and the standard translation is updated in the corpus; If the target translation is found in the corpus, the target translation is converted into a formatted language data packet for developing vehicle cockpit software in the target language.
2. The vehicle cockpit multilingual text management method according to claim 1, characterized in that: The corpus associates the Chinese text with the translation based on the markup code, and the querying of the corpus for the target translation of the Chinese text to be adapted in the target language includes: The markup code of the Chinese classical language to be adapted is searched in the corpus, and the target translation is determined according to the markup code.
3. The vehicle cockpit multilingual text management method according to claim 1, characterized in that: The target translation cannot be found in the corpus, including: It is determined that the Chinese classical language to be adapted does not exist in the corpus, or it is determined that the target translation is missing from the corpus.
4. The vehicle cockpit multilingual text management method according to claim 1, characterized in that: The method of generating a standard translation of the Chinese classical text to be adapted in the target language based on the translation engine interface and manual verification includes: Calling multiple translation engine interfaces to translate the Chinese classical language to be adapted, and obtaining multiple machine translations; Performing multimodal quality assessment on the plurality of machine translations, and selecting at least one candidate translation based on the quality assessment results; Manual verification is performed on at least one of the candidate translations; wherein the standard translation is the candidate translation that has passed the verification.
5. The vehicle cockpit multilingual text management method according to claim 1, characterized in that: The list of languages to be adapted includes at least two Chinese languages to be adapted; and the method further includes: Generate a multilingual adaptation intermediate table based on the query result of the Chinese classical language to be adapted in the corpus; if the target translation cannot be found in the corpus, mark the Chinese classical language to be adapted as being in a translation-missing state in the multilingual adaptation intermediate table; if the target translation is found in the corpus, record the target translation of the Chinese classical language to be adapted in the multilingual adaptation intermediate table; Based on the multi-language adaptation intermediate table, a formatted language data packet for developing vehicle cockpit software in the target language is output.
6. A vehicle cockpit multilingual text management system, characterized by: It includes intelligent query module, translation and verification module and structured data generation module; The intelligent query module is used to obtain a list of Chinese texts to be adapted and search the corpus for target translations of the Chinese texts to be adapted in the target language; The list of Chinese languages to be adapted records the Chinese languages to be adapted presented in the vehicle cockpit software and the target languages into which the Chinese languages to be adapted are converted; the corpus records the associations between Chinese languages and translations in multiple languages; The translation and verification module is used to generate a standard translation of the Chinese classical text to be adapted in the target language based on the translation engine interface and manual verification when the target translation cannot be found in the corpus, and update the standard translation into the corpus; The structured data generation module is configured to convert the target translation into a formatted language data packet for developing vehicle cockpit software in the target language when the target translation is found in the corpus.
7. The vehicle cockpit multilingual text management system according to claim 6, characterized in that: The corpus associates the Chinese text with the translation based on the markup code; The intelligent query module is configured to query the markup code of the Chinese classical language to be adapted in the corpus, and determine the target translation according to the markup code.
8. The vehicle cockpit multilingual text management system according to claim 6, characterized in that: The inability to find the target translation in the corpus includes that the Chinese classical language to be adapted does not exist in the corpus, or it is determined that the corpus lacks the target translation.
9. The vehicle cockpit multilingual text management system according to claim 6, characterized in that: The list of languages to be adapted includes at least two Chinese languages to be adapted; The intelligent query module is configured to generate a multilingual adaptation intermediate table; If the target translation cannot be found in the corpus, the Chinese classical language to be adapted is marked as missing in the multilingual adaptation intermediate table; If the target translation is found in the corpus, the target translation of the Chinese classical language to be adapted is recorded in a multilingual adaptation intermediate table; the multilingual adaptation intermediate table provides input for the translation and verification module and the structured data generation module.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle cockpit multilingual text management method according to any one of claims 1 to 5 is implemented.