A cross-platform internationalization file generation method and device, and electronic equipment

Abstract

The embodiment of the application provides a cross-platform internationalization file generation method and device and electronic equipment, including: obtaining incremental file data to be translated and a platform type of the incremental file data; performing language detection on the incremental file data to obtain at least one single-language file; for each single-language file, matching each entry data in the single-language file with a full-database according to the language type of the single-language file; for each entry data in the at least one single-language file, when the entry data is matched in the full-database, performing multilingual translation on the entry data according to a matching result to obtain a translation result of the entry data; integrating the translation results of the entry data in the at least one single-language file to obtain a plurality of translation files of different language types of the incremental file data; and generating a platform type corresponding internationalization file according to the translation files. The application realizes cross-platform generation of internationalization files.

Description

Technical Field

[0001] This application relates to the field of application development technology, and in particular to a cross-platform method, apparatus and electronic device for generating internationalized documents. Background Technology

[0002] With the development of globalization, applications are increasingly trending towards providing services to multiple countries and regions. Therefore, more and more applications are considering the operational needs of multiple languages ​​and systems in terms of functionality support and code design. For example, they consider supporting the language habits of different countries or regions (such as Chinese and English usage) and the operational logic of different systems (such as iOS and Android, both mobile operating systems). This is called application internationalization. A common approach is to first develop the application in one language, then translate the relevant development documents into multiple languages ​​to generate internationalization files, and finally implement the internationalization of the application based on these files.

[0003] Currently, developers often use development scripts and tools to perform preliminary translations, followed by manual re-translation to generate internationalization documents for the application. However, most existing preliminary translation tools are based on the multilingual import / export functions provided by a single system (iOS, Android, etc.), and can only perform simple preliminary translations of the text itself. Due to the complexity of application development, the related application documents are also quite complex. Therefore, the results of the preliminary translation are often not intelligent or satisfactory, and they only support a single system, making them inconvenient. Translators still need to spend a lot of effort on the re-translation, resulting in low efficiency. Summary of the Invention

[0004] The purpose of this application is to provide a cross-platform method, apparatus, and electronic device for generating internationalized documents, so as to improve the efficiency of generating internationalized documents. The specific technical solution is as follows:

[0005] In a first aspect, embodiments of this application provide a cross-platform method for generating internationalized documents, the method comprising:

[0006] Obtain the incremental file data to be translated and the platform type of the incremental file data;

[0007] The incremental file data is subjected to language detection to obtain at least one monolingual file, wherein each monolingual file includes only one type of vocabulary data;

[0008] For each monolingual file, according to the language type of the monolingual file, the data of each term in the monolingual file is matched with the full database;

[0009] For each term data in the at least one monolingual file, when the term data is matched in the full database, the term data is translated into multiple languages ​​according to the matching result to obtain the translation result of the term data.

[0010] The translation results of each term data in the at least one monolingual file are integrated to obtain multiple translation files of different language types of the incremental file data, wherein each translation file includes term data of only one language type;

[0011] Based on the translated documents, generate the internationalization documents corresponding to the platform type.

[0012] In one embodiment of this application, the step of obtaining the incremental file data to be translated and the platform type of the incremental file data includes:

[0013] Obtain the configuration file based on the input from the Jenkins tool, wherein the configuration file includes the SVN file path and platform type;

[0014] The file to be translated is pulled according to the SVN file path, and incremental file detection is performed on the file to be translated to obtain the incremental file data to be translated. The platform type of the incremental file data is the platform type in the configuration file.

[0015] In one embodiment of this application, the method further includes:

[0016] Obtain word data that is not matched in the full database from at least one monolingual file to obtain each first category of word data;

[0017] Add notes to the first category of term data whose similarity to the term data in the full database exceeds a preset similarity threshold, and merge the identical first category of term data to obtain the term file to be output;

[0018] According to the business module type, the term file to be output is divided into at least one table file;

[0019] For each form file, send it to the translator of the business module type to which the form file belongs;

[0020] Obtain the translation results of the terms data provided by the translators based on the form file.

[0021] In one embodiment of this application, the step of adding annotation information to first-category term data whose similarity to term data in the full database exceeds a preset similarity threshold, and merging identical first-category term data to obtain the term file to be output, includes:

[0022] For a first category of term data whose similarity to term data in the full database exceeds a preset similarity threshold, the matching result with the highest similarity to the first category of term data in the full database is added to the remarks information of the first category of term data.

[0023] Match the first type of term data under the Android platform type and the first type of term data under the iOS platform type. If there are isolated first type term data that fail to match, perform error correction annotation on the isolated first type term data.

[0024] Merge identical entries of the first category to obtain the output entry file.

[0025] In one embodiment of this application, the translation result includes the business module type and key-value pairs corresponding to each of the term data. After obtaining the translation result of the term data returned by the translator based on the table file, the method further includes:

[0026] For each term in the translation result, check whether the business module type and key-value pairs corresponding to the term are correct;

[0027] If the business module type and key-value pair corresponding to the term data are correct, the content corresponding to the term data in the translation result is stored in the full database and marked as pending upgrade;

[0028] Write the data marked as pending upgrade in the full database to the corresponding translation file, and clear the pending upgrade markers in the full database.

[0029] In one embodiment of this application, the method further includes:

[0030] Obtain the data of terms to be deleted based on the input from the Jenkins tool;

[0031] Delete the term data to be deleted and the translation results of the term data to be deleted from the full database;

[0032] Retrieve the first internationalization file corresponding to the term data to be deleted according to the SVN file path, and delete the term data to be deleted or the translation result of the term data to be deleted in the first internationalization file to obtain the updated internationalization file;

[0033] Upload the updated internationalization file according to the specified SVN file path.

[0034] Secondly, this application also provides a cross-platform internationalized document generation device, the device comprising:

[0035] The first data acquisition module is used to acquire the incremental file data to be translated and the platform type of the incremental file data;

[0036] The language detection module is used to perform language detection on the incremental file data to obtain at least one monolingual file, wherein each monolingual file includes only one type of word data in one language.

[0037] The data matching module is used to match the vocabulary data in each monolingual file with the full database according to the language type of the monolingual file.

[0038] The data translation module is used to perform multilingual translation on each term data in the at least one monolingual file, when the term data is matched in the full database, to obtain the translation result of the term data;

[0039] The result integration module is used to integrate the translation results of each term data in the at least one monolingual file to obtain multiple translation files of different language types of the incremental file data, wherein each translation file includes term data of only one language type;

[0040] The file generation module is used to generate internationalization files corresponding to the platform type based on each of the translated files.

[0041] In one embodiment of this application, the first data acquisition module is specifically used for:

[0042] Obtain the configuration file based on the input from the Jenkins tool, wherein the configuration file includes the SVN file path and platform type;

[0043] The file to be translated is pulled according to the SVN file path, and incremental file detection is performed on the file to be translated to obtain the incremental file data to be translated. The platform type of the incremental file data is the platform type in the configuration file.

[0044] In one embodiment of this application, the apparatus further includes:

[0045] The second data acquisition module is used to acquire word data that is not matched in the full database from the at least one monolingual file, and obtain each first category of word data;

[0046] The data processing module is used to add annotation information to the first type of term data whose similarity to the term data in the full database exceeds a preset similarity threshold, and to merge the identical first type of term data to obtain the term file to be output.

[0047] The file partitioning module is used to partition the term file to be output into at least one table file according to the business module type;

[0048] The file sending module is used to send each form file to the translator of the business module type to which the form file belongs;

[0049] The result acquisition module is used to acquire the translation results of the translators based on the term data returned by the table file.

[0050] In one embodiment of this application, the data processing module is specifically used for:

[0051] For a first category of term data whose similarity to term data in the full database exceeds a preset similarity threshold, the matching result with the highest similarity to the first category of term data in the full database is added to the remarks information of the first category of term data.

[0052] Match the first type of term data under the Android platform type and the first type of term data under the iOS platform type. If there are isolated first type term data that fail to match, perform error correction annotation on the isolated first type term data.

[0053] Merge identical entries of the first category to obtain the output entry file.

[0054] In one embodiment of this application, the apparatus further includes:

[0055] The data detection module is used to detect whether the business module type and key-value pairs corresponding to each term in the translation result are correct.

[0056] The data storage module is used to store the content corresponding to the term data in the translation result into the full database, and mark it as pending upgrade, provided that the business module type and key-value pair corresponding to the term data are correct;

[0057] The data writing module is used to write the data marked as to be upgraded in the full database to the corresponding translation file, and to clear the upgrade mark in the full database.

[0058] In one embodiment of this application, the apparatus further includes:

[0059] The third data acquisition module is used to acquire the data of terms to be deleted based on the input of the Jenkins tool;

[0060] The first data deletion module is used to delete the term data to be deleted and the translation results of the term data to be deleted from the full database.

[0061] The second data deletion module is used to pull the first internationalization file corresponding to the term data to be deleted according to the SVN file path, and delete the term data to be deleted or the translation result of the term data to be deleted in the first internationalization file to obtain the updated internationalization file.

[0062] The file upload module is used to upload the updated internationalized file according to the SVN file path.

[0063] Thirdly, embodiments of this application also provide an electronic device, including:

[0064] Memory, used to store computer programs;

[0065] The processor, when executing a program stored in memory, implements any of the cross-platform internationalized file generation methods described above.

[0066] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any of the aforementioned cross-platform internationalized file generation methods.

[0067] This application also provides a computer program product containing instructions that, when run on a computer, cause the computer to execute any of the cross-platform internationalized document generation methods described above.

[0068] Beneficial effects of the embodiments in this application:

[0069] The cross-platform internationalization document generation method provided in this application first obtains the incremental file data to be translated and the platform type of the incremental file data. That is, it only obtains the incremental file data that needs to be updated for translation, without having to re-translate the previously translated content, thus reducing the workload caused by repeated translation and improving translation efficiency. The incremental file data is then subjected to language detection to obtain at least one monolingual file. Each monolingual file includes only one type of term data, thereby separating the incremental file data of different languages, improving the convenience of subsequent translation, and reducing the probability of translation errors.

[0070] Then, for each monolingual file, according to the language type of the monolingual file, the term data in the monolingual file is matched with the full database. For each term data, if the term data is matched in the full database, it means that the term data has been translated before and stored in the full database. Then, the term data can be translated into multiple languages ​​according to the matching results to obtain the translation result of the term data. This effectively reduces the repeated translation of the same term data and improves the overall translation efficiency.

[0071] The translation results of each term in the monolingual files are then integrated to obtain multiple translation files in different language types for the incremental file data. Each translation file contains term data for only one language type. Finally, based on each translation file, an internationalization file corresponding to the platform type is generated. Thus, by only acquiring incremental file data including at least one language, multilingual translation can be achieved in one go, and an internationalization file corresponding to the required platform type can be obtained. This allows the internationalization file to adapt to the language rules and syntax of various platform types, improving the efficiency of internationalization file generation while achieving cross-platform compatibility. Consequently, the efficiency of internationalization implementation for the corresponding application is improved.

[0072] Of course, implementing any product or method of this application does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0073] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0074] Figure 1 A flowchart illustrating the first cross-platform internationalization document generation method provided in this application;

[0075] Figure 2 One possible implementation of step S11 provided in this application;

[0076] Figure 3 A flowchart illustrating the second cross-platform internationalization document generation method provided in this application;

[0077] Figure 4 One possible implementation of step S32 provided in this application;

[0078] Figure 5 One possible implementation of step S35 provided in this application;

[0079] Figure 6 A flowchart illustrating the third cross-platform internationalization document generation method provided in this application;

[0080] Figure 7 A system example diagram for implementing a cross-platform internationalized document generation method provided in this application;

[0081] Figure 8 Example diagram of a cross-platform internationalized document generation method provided in this application;

[0082] Figure 9 A schematic diagram of the structure of a cross-platform internationalized document generation device provided in this application;

[0083] Figure 10 This is a schematic diagram of the structure of an electronic device provided in this application. Detailed Implementation

[0084] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0085] A first aspect of the embodiments of this application, see [link to...]. Figure 1 First, a flowchart illustrating the first cross-platform internationalization document generation method is provided, including:

[0086] Step S11: Obtain the incremental file data to be translated and the platform type of the incremental file data.

[0087] The incremental file data to be translated can be part or all of the data in the file to be translated. Specifically, if the previous version of the file to be translated has been translated into multiple languages, then the incremental file data is the file data that has been changed or added due to the version update, that is, only the incremental file data is the content that has not yet been translated into multiple languages; when the previous version of the file to be translated has not been translated into multiple languages, or when the file to be translated is the first version, that is, all the content of the file to be translated has not been translated into multiple languages, then the incremental file data is the entire content of the file to be translated.

[0088] The platform type of incremental file data indicates the operating platform or development platform of the application corresponding to the file containing the incremental file data. Examples include Android, iOS (for both operating platforms), RN, and Flutter (for both development platforms). Different platform types generally have different requirements for internationalization files; therefore, it is necessary to obtain the platform type to facilitate the subsequent generation of internationalization files that run on the corresponding platform type. Incremental file data can correspond to one platform type or multiple platform types.

[0089] Step S12: Perform language detection on the incremental file data to obtain at least one monolingual file;

[0090] Each of the aforementioned monolingual files contains only one type of vocabulary data.

[0091] The incremental file data includes terminology data in one or more languages. The languages ​​are common languages ​​used in various countries or regions, such as Chinese, English, and German. The terminology data consists of sentences and terms included in the incremental file data. The incremental file data may include terminology data in only one language, for example, all terminology data may be in Chinese; or it may include terminology data in multiple languages, for example, including both Chinese and English terminology data.

[0092] It's understandable that translating incremental file data involves translating the included terminology data into languages ​​other than the original terminology data type. For example, if the terminology data is in Chinese, it needs to be translated into languages ​​other than Chinese, such as English or German; similarly, if the terminology data is in English, it needs to be translated into languages ​​other than English, such as Chinese or German. However, incremental file data contains terminology data in one or more languages. The matching language and the resulting language differ depending on the terminology data type. Therefore, it's necessary to perform language detection on the incremental file data and divide it into one or more single-language files based on different language types. Each single-language file contains terminology data in only one language type.

[0093] When the incremental file data contains only one type of term data, only one monolingual file can be obtained, which includes all the term data in the incremental file data. When the incremental file data contains term data in multiple language types, multiple monolingual files can be obtained according to each language type. Each monolingual file includes term data in one language type, that is, it includes term data in one language type from the incremental file data.

[0094] Step S13: For each monolingual file, match the vocabulary data in the monolingual file with the full database according to the language type of the monolingual file.

[0095] The aforementioned full database includes historically translated terminology data and multilingual translations of each term. Each term in every single-language file is matched against the full database to confirm whether any matching terms exist in the full database for the single-language file requiring translation. As mentioned above, translating terminology in a single-language file involves translating each term into a language other than its original language. Therefore, when matching against the full database, the matching is based on the language type of the single-language file to confirm whether translations exist in the full database for each term in a language other than its original language.

[0096] Step S14: For each term in at least one monolingual file, if the term is matched in the full database, the term is translated into multiple languages ​​based on the matching result to obtain the translation result of the term.

[0097] For each term in a single-language file, when a match is found in the full database, it means that the term and its corresponding multilingual translations exist in the database. This could be because the term has been translated into multiple languages ​​in the past, or because the full database has pre-stored the term and its corresponding multilingual translations. The resulting match is the multilingual translation of that term, including any languages ​​other than the original term. Therefore, based on the match, multilingual translation of the term can be performed, yielding the translation result.

[0098] Step S15: Integrate the translation results of each term in at least one monolingual file to obtain multiple translation files of different language types from the incremental file data.

[0099] As mentioned above, the translation of each term data is performed in languages ​​other than the language type of the term data itself. Therefore, the translation results of each term data in each monolingual file include translation results of multiple language types. By integrating the translation results of the same language type of each term data, the translation file of the incremental file data can be obtained. That is, the incremental file data has multiple translation files corresponding to different language types, and each translation file contains term data of only one language type.

[0100] Step S16: Generate internationalization files corresponding to each platform type based on the translated files.

[0101] As mentioned above, incremental file data is a portion of the content of its containing file. When the file containing incremental file data has been translated into multiple languages ​​in the past, the incremental file data is the currently updated portion of the file containing it, while the rest of the file contains content that has already been translated into multiple languages. Therefore, after obtaining multiple translation files of the incremental file data, these multiple translation files are used to update the file containing the incremental file data to obtain a complete internationalization file. Furthermore, as mentioned above, different platform types may have the same or different requirements for internationalization files. Therefore, when updating the file containing the incremental file data with multiple translation files, the platform type of the incremental file data is also taken into account. When the incremental file data has multiple platform types, internationalization files corresponding to each platform type are generated; when the incremental file data has only one platform type, the internationalization file corresponding to that platform type is generated.

[0102] When the file containing the incremental data is one that has not been translated into many languages ​​in the past, meaning that the entire content of the file has not been translated into many languages, after obtaining multiple translation files of the incremental data, an internationalization file corresponding to the platform type is generated based on the multiple translation files of the incremental data. When the incremental data has multiple platform types, an internationalization file corresponding to each platform type is generated; when the incremental data has only one platform type, an internationalization file corresponding to that platform type is generated.

[0103] In one embodiment of this application, when generating internationalization files corresponding to platform types based on multiple translated files, the translated files are further processed for detection due to the characteristics of some platform types. For example, Android and Flutter have language characteristics; during interactive development, Chinese characters are written into English files, otherwise the development project will not compile. Therefore, when generating internationalization files corresponding to platform types, it is also checked whether the language type in the internationalization files matches the language type required by the platform type. In one example, this can be achieved using Python langid (a language detection tool). If they do not match, the internationalization files are adjusted. For example, for Android and Flutter platform types, the Chinese monolingual files included in the Chinese translated files or incremental file data are written into English translated files to generate internationalization files corresponding to Android and Flutter platform types.

[0104] As can be seen from the above, the cross-platform internationalization document generation method provided in this application first obtains the incremental file data to be translated and the platform type of the incremental file data. That is, it only obtains the incremental file data that needs to be updated for translation, without having to re-translate the previously translated content, thus reducing the workload caused by repeated translation and improving translation efficiency. The incremental file data is then subjected to language detection to obtain at least one monolingual file. Each monolingual file includes only one type of term data, thereby separating the incremental file data of different languages, improving the convenience of subsequent translation, and reducing the probability of translation errors.

[0105] Then, for each monolingual file, according to the language type of the monolingual file, the term data in the monolingual file is matched with the full database. For each term data, if the term data is matched in the full database, it means that the term data has been translated before and stored in the full database. Then, the term data can be translated into multiple languages ​​according to the matching results to obtain the translation result of the term data. This effectively reduces the repeated translation of the same term data and improves the overall translation efficiency.

[0106] The translation results of each term in the monolingual files are then integrated to obtain multiple translation files in different language types for the incremental file data. Each translation file contains term data for only one language type. Finally, based on each translation file, an internationalization file corresponding to the platform type is generated. Thus, by only acquiring incremental file data including at least one language, multilingual translation can be achieved in one go, and an internationalization file corresponding to the required platform type can be obtained. This allows the internationalization file to adapt to the language rules and syntax of various platform types, improving the efficiency of internationalization file generation while achieving cross-platform compatibility. Consequently, the efficiency of internationalization implementation for the corresponding application is improved.

[0107] In one possible implementation, such as Figure 2 As shown, step S11 above, which obtains the incremental file data to be translated and the platform type of the incremental file data, includes:

[0108] Step S21: Obtain the configuration file based on the input from the Jenkins tool;

[0109] The configuration file includes the SVN (subversion, an open-source version control system) file path and platform type;

[0110] Step S22: Pull the file to be translated according to the SVN file path, perform incremental file detection on the file to be translated, and obtain the incremental file data to be translated;

[0111] The platform type of the incremental file data is the platform type in the configuration file.

[0112] Jenkins is a continuous integration tool developed based on Java (a computer language). It is used to monitor repetitive tasks and aims to provide an open and easy-to-use software platform that enables continuous integration of software projects (applications). When an application developed using Jenkins has a newly uploaded update file, the server will immediately and automatically deploy the application for iterative version updates, so that the application running on the server is immediately updated to the latest version.

[0113] In this embodiment, a configuration file is obtained based on the input from the Jenkins tool. The path to the file to be translated and its corresponding platform type can be determined based on the SVN file path and platform type included in the configuration file. Specifically, this can be achieved using the SVN checkout function (the download function of the SVN server). Then, the file to be translated is retrieved from the server to the local machine according to the SVN file path; this file is the one required for translation in this application.

[0114] Incremental file detection is performed on the file to be translated. This involves checking whether the file has been translated into multiple languages ​​in the past. If it has, the system checks whether there is any updated content that has not yet been translated into multiple languages. If the updated content is found to exist, it is considered the incremental file data to be translated. If it does not exist, it means there is no updated content or no incremental file data to be translated. If the file has not been translated into multiple languages ​​in the past, the entire file is considered as the incremental file data to be translated.

[0115] In one embodiment of this application, after generating the internationalization file as described above, it is also necessary to upload the internationalization file to the server according to the SVN file path. This allows the Jenkins tool to obtain the internationalization file, generate a modification component package based on it for the application corresponding to the file to be translated, and upload the modification component package to the SVN server, enabling the SVN server to automatically update the application. In addition, the generated internationalization file is also sent to the application's developers for timely monitoring.

[0116] As can be seen from the above, the cross-platform internationalization document generation method provided in this application uses the Jenkis tool and SVN file path to automatically pull and detect the files to be translated, thereby obtaining the incremental file data to be translated and its platform type. It realizes automatic acquisition and processing when there are files to be translated, and can detect the incremental file data to be translated included in the files to be translated. Only the incremental file data to be translated is translated, reducing the repeated translation of file data that has been translated into multiple languages ​​in the past, and effectively improving the processing efficiency of the files to be translated.

[0117] In one embodiment of this application, such as Figure 3 The diagram illustrates the process of generating internationalized documents across platforms, as shown below.

[0118] Step S31: Obtain the term data that is not matched in the full database from the at least one monolingual file to obtain the term data of each first category.

[0119] In this embodiment of the application, each monolingual file may include term data that is not matched in the full database, which means that the term data and its corresponding multilingual translation results do not exist in the full database. Such term data that cannot be matched with the full database is regarded as the first type of term data, that is, the first type of term data may include term data of multilingual types.

[0120] Step S32: Add notes to the first category of term data whose similarity to the term data in the full database exceeds a preset similarity threshold, and merge the identical first category of term data to obtain the term file to be output.

[0121] It's understandable that although no matching entry for Category 1 terms is found in the full database, indicating the absence of identical terms, other terms similar to Category 1 terms may exist. These similar terms may have the same or similar meanings. Therefore, the similarity between the terms in the full database and Category 1 terms can be calculated. When the similarity exceeds a preset similarity threshold, it indicates a high probability of having the same or similar meanings. In this case, a note is added to the Category 1 term, which can be the meaning of similar terms or multilingual translations, providing a reference for subsequent translations. In one example, this similarity can be obtained using Python's Levenshtein (a text comparison tool). The preset similarity threshold is a pre-defined value that can be adjusted according to actual needs.

[0122] Simultaneously, identical Category I terminology data is merged. Specifically, Category I terminology data with the same meaning but different language types are considered identical. Only one instance of identical Category I terminology data is retained to avoid duplicate translation work for the same term. Finally, the Category I terminology data, after processing such as adding notes and merging identical items, is integrated into the output terminology file.

[0123] Step S33: Divide the term file to be output into at least one table file according to the business module type.

[0124] The business module type represents different business modules. It's understandable that different business modules may require different specialized translators. Therefore, the output terminology file is divided into one or more table files according to the business module type. If all terminology data in the output terminology file belongs to the same business module type, then the output terminology file can be considered as a single table file. If the terminology data in the output terminology file belongs to multiple different business module types, then the terminology data in the output terminology file is divided into separate table files corresponding to each business module type. Specifically, for ease of operation, the output terminology file can be an Excel spreadsheet (a table file format), and dividing it into different table files can be done by dividing it into different sheets within the Excel spreadsheet.

[0125] Step S34: For each form file, send the form file to the translator of the business module type to which the form file belongs;

[0126] Step S35: Obtain the translation results of the term data returned by the translator based on the form file.

[0127] Each table file is sent to the translator of the business module type corresponding to the term data in that table file, so that the translator can perform multilingual translation of the term data in the table file and return the multilingual translation results. Finally, the translation results of each term data returned by the translator are obtained.

[0128] As can be seen from the above, the cross-platform internationalization document generation method provided in this application, when the single-language file includes first-category terminology data that cannot be matched in the full database, firstly adds annotation information to the first-category terminology data whose similarity to the terminology data in the full database exceeds a preset similarity threshold, thereby providing translation reference for subsequent translators, minimizing repetitive translation, and improving translation efficiency. Furthermore, it merges identical first-category terminology data to reduce repetitive translation. The processed first-category terminology data is integrated into an output terminology file, and then divided into table files corresponding to each business module type according to the business module type. This allows translators corresponding to each business module type to perform multilingual translation of each terminology data in the table files, obtaining translation results for each terminology data, which can improve the translation efficiency and accuracy of terminology data.

[0129] In one possible implementation, such as Figure 4 As shown, step S32 above adds annotation information to the first type of term data whose similarity to the term data in the full database exceeds a preset similarity threshold, and merges the identical first type of term data to obtain the term file to be output, including:

[0130] Step S41: For the first type of term data whose similarity to the term data in the full database exceeds a preset similarity threshold, add the matching result with the highest similarity to the first type of term data in the full database to the remarks information of the first type of term data;

[0131] Step S42: Match the first type of term data under the Android platform type and the first type of term data under the iOS platform type. If there are isolated first type term data that fail to match, perform error correction annotation on the isolated first type term data.

[0132] Step S43: Merge the identical first-category term data to obtain the term file to be output.

[0133] When adding notes to the first type of term data, there may be multiple terms in the full database that have a similarity to the first type of term data that exceeds a preset similarity threshold. In this case, the matching result with the highest similarity is selected and added to the notes of the first type of term data. That is, the word meaning or multilingual translation result of the term data with the highest similarity to the first type of term data can be added as the notes of the first type of term data.

[0134] In addition, as mentioned above, incremental file data can have one or more platform types. When incremental file data has both Android and iOS platform types, the first category of term data for the Android platform type and the first category of term data for the iOS platform type should be consistent, that is, they should correspond one-to-one. Therefore, the first category of term data for the Android platform type and the first category of term data for the iOS platform type are also matched. If there is an isolated first category of term data that fails to match, it means that the isolated first category of term data may be incorrect. The isolated first category of term data is then marked with an error correction label to provide a reference for translators or developers who will process it later.

[0135] Next, merge the same first-category term data. In one example, each first-category term data has key-value pairs. For first-category term data of different platform types, different business module types, and different language types, there may be first-category term data with the same meaning but different key-value pairs. These first-category term data are also merged, and finally the term file to be output is obtained.

[0136] As can be seen from the above, the cross-platform internationalization document generation method provided in this application selects the matching result with the highest similarity between the full database and the first type of term data and adds it to the remarks information of the first type of term data, thereby adding the most valuable remarks information for translation reference to the first type of term data; it also matches the first type of term data under the Android platform type and the first type of term data under the iOS platform type, and in the case of isolated first type term data that fails to match, it performs error correction annotation on the isolated first type term data, providing reference information for translators or developers to check and correct errors in subsequent processing, thereby improving the overall efficiency of generating internationalization documents.

[0137] In one possible implementation, such as Figure 5 As shown, the translation results include the business module type and key-value pairs corresponding to each of the term data. After obtaining the translation results of the term data returned by the translator based on the table file in step S35 above, the method further includes:

[0138] Step S51: For each term in the translation result, check whether the business module type and key-value pair corresponding to the term are correct;

[0139] Step S52: If the business module type and key-value pair corresponding to the term data are correct, store the content corresponding to the term data in the translation result into the full database and mark it as pending upgrade;

[0140] Step S53: Write the data marked as to be upgraded in the full database into the corresponding translation file, and clear the upgrade-to-upgrade markers in the full database.

[0141] After obtaining the translation results of the term data provided by the translators based on the table file, the system first checks whether the business module type and key-value pairs of each term data in the translation results correspond correctly. If correct, the term data and its corresponding translation results are stored in the full database and marked as pending upgrade. Then, the data marked as pending upgrade in the full database is written into the corresponding translation file according to the language type, thereby obtaining the complete translation file of the incremental file data, and the pending upgrade mark in the full database is cleared.

[0142] As can be seen from the above, the cross-platform internationalization document generation method provided in this application, when the business module type and key-value pair of each term data in the translation result are correctly matched, stores the term data and its corresponding translation result in the full database, thereby realizing automatic updates to the full database. This reduces duplicate translations when the term data needs to be translated into multiple languages ​​in the future. The translation result of the term data is marked as to be upgraded, and then the data marked as to be upgraded is written into the corresponding translation file, thereby obtaining the complete translation file of the incremental file data and improving the translation accuracy of the incremental file data.

[0143] In one possible implementation, such as Figure 6 The diagram illustrates a third method for generating internationalized documents across platforms, and also includes:

[0144] Step S61: Obtain the data of terms to be deleted based on the input of the Jenkins tool;

[0145] Step S62: Delete the term data to be deleted and the translation results of the term data to be deleted from the full database;

[0146] Step S63: Retrieve the first internationalization file corresponding to the term data to be deleted according to the SVN file path, and delete the term data to be deleted or the translation result of the term data to be deleted in the first internationalization file to obtain the updated internationalization file;

[0147] Step S64: Upload the updated internationalization file according to the SVN file path.

[0148] When there is data on terms to be deleted, the process first retrieves the data based on the input from the Jenkins tool. Then, it deletes all such data and their translations from the entire database. Next, it pulls the corresponding first internationalization file from the server to the local machine according to the SVN file path. Finally, it deletes the term or its translation from the first internationalization file. In one example, this could be done by determining the term or its translation from the first internationalization file based on key-value pairs of the term. After deletion, an updated internationalization file is obtained, which is then uploaded according to the SVN file path.

[0149] As can be seen from the above, the cross-platform internationalization file generation method provided in this application, when there is deletable term data, also retrieves the first internationalization file corresponding to the term data to be deleted and deletes it, and deletes the term data to be deleted and the translation results of the term data to be deleted from the full database, so as to achieve the complete deletion of the term data to be deleted.

[0150] In one embodiment of this application, such as Figure 7 As shown, a system example diagram for generating internationalized documents across platforms is also provided. Developers input a configuration file via Jenkins, which includes the SVN file path of the file to be translated. SVN stores the file in the corresponding application's development code storage address. A full database stores terminology data and multilingual translation results. Product managers, acting as translators for their respective business module types, provide translation feedback on the terminology data in the spreadsheet file. The system exports multilingual translation results from the full database and the spreadsheet file provided by translators, imports these results into the translated document file, and can modify the internationalized document for multilingual compatibility with platform types before uploading. It can also delete terminology data and its multilingual translation results from the internationalized document. Furthermore, it can perform language detection on incremental document data, historical matching between terminology data and the full database, similarity detection between first-category terminology data and the full database, and merge identical first-category terminology data. The resulting terminology file is then split into spreadsheet files according to business module types.

[0151] In one embodiment of this application, such as Figure 8 As shown, an example diagram of a cross-platform internationalization document generation method is also provided.

[0152] See Figure 9 This disclosure also provides a schematic diagram of a cross-platform internationalized document generation device, the device comprising:

[0153] The first data acquisition module 901 is used to acquire the incremental file data to be translated and the platform type of the incremental file data;

[0154] The language detection module 902 is used to perform language detection on the incremental file data to obtain at least one monolingual file, wherein each monolingual file includes only one type of word data in one language.

[0155] The data matching module 903 is used to match the data of each term in each monolingual file with the full database according to the language type of the monolingual file.

[0156] The data translation module 904 is used to perform multilingual translation on each term data in the at least one monolingual file, when the term data is matched in the full database, to obtain the translation result of the term data;

[0157] The result integration module 905 is used to integrate the translation results of each term data in the at least one monolingual file to obtain multiple translation files of different language types of the incremental file data, wherein each translation file includes term data of only one language type.

[0158] The document generation module 906 is used to generate an internationalization document corresponding to the platform type based on each of the translated documents.

[0159] As can be seen from the above, the cross-platform internationalization document generation device provided in this application first obtains the incremental document data to be translated and the platform type of the incremental document data. That is, it only obtains the incremental document data that needs to be updated for translation, without having to repeatedly translate the previously translated content, thereby reducing the workload caused by repeated translation and improving translation efficiency. The incremental document data is then subjected to language detection to obtain at least one monolingual file. Each monolingual file includes only one type of term data, thereby separating the incremental document data of different languages, improving the convenience of subsequent translation, and reducing the probability of translation errors.

[0160] Then, for each monolingual file, according to the language type of the monolingual file, the term data in the monolingual file is matched with the full database. For each term data, if the term data is matched in the full database, it means that the term data has been translated before and stored in the full database. Then, the term data can be translated into multiple languages ​​according to the matching results to obtain the translation result of the term data. This effectively reduces the repeated translation of the same term data and improves the overall translation efficiency.

[0161] The translation results of each term in the monolingual files are then integrated to obtain multiple translation files in different language types for the incremental file data. Each translation file contains term data for only one language type. Finally, based on each translation file, an internationalization file corresponding to the platform type is generated. Thus, by only acquiring incremental file data including at least one language, multilingual translation can be achieved in one go, and an internationalization file corresponding to the required platform type can be obtained. This allows the internationalization file to adapt to the language rules and syntax of various platform types, improving the efficiency of internationalization file generation while achieving cross-platform compatibility. Consequently, the efficiency of internationalization implementation for the corresponding application is improved.

[0162] In one embodiment of this application, the first data acquisition module 901 is specifically used for:

[0163] Obtain the configuration file based on the input from the Jenkins tool, wherein the configuration file includes the SVN file path and platform type;

[0164] The file to be translated is pulled according to the SVN file path, and incremental file detection is performed on the file to be translated to obtain the incremental file data to be translated. The platform type of the incremental file data is the platform type in the configuration file.

[0165] As can be seen from the above, the cross-platform internationalization document generation device provided in this application embodiment utilizes the Jenkis tool and SVN file path to automatically retrieve and detect the files to be translated, thereby obtaining the incremental file data to be translated and its platform type. It realizes automatic acquisition and processing when there are files to be translated, and can detect the incremental file data to be translated included in the files to be translated, and only perform subsequent translation processing on the incremental file data to be translated, reducing the repeated translation of file data that has been translated into multiple languages ​​in the past included in the files to be translated, and effectively improving the processing efficiency of the files to be translated.

[0166] In one embodiment of this application, the apparatus further includes:

[0167] The second data acquisition module is used to acquire word data that is not matched in the full database from the at least one monolingual file, and obtain each first category of word data;

[0168] The data processing module is used to add annotation information to the first type of term data whose similarity to the term data in the full database exceeds a preset similarity threshold, and to merge the identical first type of term data to obtain the term file to be output.

[0169] The file partitioning module is used to partition the term file to be output into at least one table file according to the business module type;

[0170] The file sending module is used to send each form file to the translator of the business module type to which the form file belongs;

[0171] The result acquisition module is used to acquire the translation results of the translators based on the term data returned by the table file.

[0172] As can be seen from the above, the cross-platform internationalization document generation device provided in this application, when the monolingual file includes first-category terminology data that cannot be matched in the full database, firstly adds annotation information to the first-category terminology data whose similarity to the terminology data in the full database exceeds a preset similarity threshold, thereby providing translation reference for subsequent translators, minimizing repetitive translation, and improving translation efficiency. Furthermore, it merges identical first-category terminology data to reduce repetitive translation. The processed first-category terminology data is integrated into an output terminology file, and then divided into table files corresponding to each business module type according to the business module type. This allows translators corresponding to each business module type to perform multilingual translation of each terminology data in the table files, obtaining translation results for each terminology data, which can improve the translation efficiency and accuracy of terminology data.

[0173] In one embodiment of this application, the data processing module is specifically used for:

[0174] For a first category of term data whose similarity to term data in the full database exceeds a preset similarity threshold, the matching result with the highest similarity to the first category of term data in the full database is added to the remarks information of the first category of term data.

[0175] Match the first type of term data under the Android platform type and the first type of term data under the iOS platform type. If there are isolated first type term data that fail to match, perform error correction annotation on the isolated first type term data.

[0176] Merge identical entries of the first category to obtain the output entry file.

[0177] As can be seen from the above, the cross-platform internationalization document generation device provided in this application embodiment selects the matching result with the highest similarity between the full database and the first type of term data and adds it to the remarks information of the first type of term data, thereby adding the most valuable remarks information for translation reference to the first type of term data; it also matches the first type of term data under the Android platform type and the first type of term data under the iOS platform type, and in the case of isolated first type term data that fails to match, it performs error correction annotation on the isolated first type term data, providing reference information for translators or developers to check and correct errors in subsequent processing, thereby improving the overall efficiency of generating internationalization documents.

[0178] In one embodiment of this application, the apparatus further includes:

[0179] The data detection module is used to detect whether the business module type and key-value pairs corresponding to each term in the translation result are correct.

[0180] The data storage module is used to store the content corresponding to the term data in the translation result into the full database, and mark it as pending upgrade, provided that the business module type and key-value pair corresponding to the term data are correct;

[0181] The data writing module is used to write the data marked as to be upgraded in the full database to the corresponding translation file, and to clear the upgrade mark in the full database.

[0182] As can be seen from the above, the cross-platform internationalization document generation device provided in this application, when the business module type and key-value pair of each term data in the translation result are correctly matched, stores the term data and its corresponding translation result in the full database, thereby realizing automatic updates to the full database. This reduces redundant translations when the term data needs to be translated into multiple languages ​​in the future. The translation result of the term data is marked as to be upgraded, and then the data marked as to be upgraded is written into the corresponding translation file, thereby obtaining the complete translation file of the incremental document data and improving the translation accuracy of the incremental document data.

[0183] In one embodiment of this application, the apparatus further includes:

[0184] The third data acquisition module is used to acquire the data of terms to be deleted based on the input of the Jenkins tool;

[0185] The first data deletion module is used to delete the term data to be deleted and the translation results of the term data to be deleted from the full database.

[0186] The second data deletion module is used to pull the first internationalization file corresponding to the term data to be deleted according to the SVN file path, and delete the term data to be deleted or the translation result of the term data to be deleted in the first internationalization file to obtain the updated internationalization file.

[0187] The file upload module is used to upload the updated internationalized file according to the SVN file path.

[0188] As can be seen from the above, the cross-platform internationalization document generation device provided in this application embodiment, when there is deletable term data, also pulls the first internationalization document corresponding to the term data to be deleted for deletion, and deletes the term data to be deleted and the translation results of the term data to be deleted from the full database, so as to achieve the complete deletion of the term data to be deleted.

[0189] This application also provides an electronic device, such as... Figure 10 As shown, it includes:

[0190] Memory 1001 is used to store computer programs;

[0191] The processor 1002, when executing a program stored in the memory 1001, implements any of the above-mentioned cross-platform internationalized file generation methods.

[0192] Furthermore, the aforementioned electronic device may also include a communication bus and / or a communication interface, with the processor 1002, the communication interface, and the memory 1001 communicating with each other via the communication bus.

[0193] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0194] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0195] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0196] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0197] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of any of the above-described cross-platform internationalized document generation methods.

[0198] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the cross-platform internationalized document generation methods described above.

[0199] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially 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, all or part of the processes or functions described in the embodiments of this application are generated. 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. 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 wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0200] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0201] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, electronic devices, and storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0202] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A method for generating a cross-platform internationalized file, the method comprising: The method comprises: obtaining a configuration file input based on a Jenkins tool, wherein the configuration file comprises an SVN file path and a platform type; pulling a to-be-translated file according to the SVN file path, and performing incremental file detection on the to-be-translated file to obtain incremental file data to be translated, wherein the platform type of the incremental file data is the platform type in the configuration file; performing language detection on the incremental file data to obtain at least one single-language file, wherein each single-language file comprises only term data of one language type; for each single-language file, matching each term data in the single-language file with a full-database according to the language type of the single-language file; for each term data in the at least one single-language file, when the term data is matched in the full-database, performing multilingual translation on the term data according to a matching result to obtain a translation result of the term data; obtaining term data in the at least one single-language file that is not matched in the full-database to obtain first-type term data, adding remark information to the first-type term data that has a similarity exceeding a preset similarity threshold with the term data of the full-database, and merging the same first-type term data to obtain a to-be-output term file; dividing the to-be-output term file into at least one table file according to a business module type; sending each table file to a translator of the business module type to which the table file belongs; and obtaining a translation result of term data fed back by the translator according to the table file; integrating translation results of term data in the at least one single-language file to obtain a plurality of translation files of different language types of the incremental file data, wherein each translation file comprises only term data of one language type; generating an internationalization file corresponding to the platform type according to the translation files.

2. The method of claim 1, wherein, The adding of remark information to the first-type term data that has a similarity exceeding a preset similarity threshold with the term data of the full-database, and the merging of the same first-type term data to obtain a to-be-output term file, comprises: for the first-type term data that has a similarity exceeding a preset similarity threshold with the term data of the full-database, adding a matching result in the full-database that has the highest similarity with the first-type term data to remark information of the first-type term data; performing matching on the first-type term data under an Android platform type and the first-type term data under an IOS platform type, and if there is isolated first-type term data that fails to be matched, performing error correction annotation on the isolated first-type term data; merging the same first-type term data to obtain a to-be-output term file.

3. The method of claim 1, wherein, The translation result comprises a business module type and a key-value pair corresponding to each term data, and after the obtaining of the translation result of term data fed back by the translator according to the table file, the method further comprises: For each word data in the translation result, detect whether the business module type and key-value pair corresponding to the word data are correct; In the case where the business module type and key-value pair corresponding to the word data are correct, store the content corresponding to the word data in the translation result in the full-database, and mark as to be upgraded; Write the data marked as to be upgraded in the full-database into the corresponding translation file, and clear the to-be-upgraded mark in the full-database.

4. The method of claim 1, wherein, The method further comprises: Obtain word data to be deleted based on the Jenkins tool input; Delete the word data to be deleted and the translation result of the word data to be deleted in the full-database; Pull a first internationalization file corresponding to the word data to be deleted according to the SVN file path, and delete the word data to be deleted or the translation result of the word data to be deleted in the first internationalization file to obtain an updated internationalization file; Upload the updated internationalization file according to the SVN file path.

5. An apparatus for generating a cross-platform internationalized file, the apparatus comprising: The device comprises: A first data acquisition module configured to acquire a configuration file based on a Jenkins tool input, wherein the configuration file comprises an SVN file path and a platform type; pull a file to be translated according to the SVN file path, and perform incremental file detection on the file to be translated to obtain incremental file data, wherein the platform type of the incremental file data is the platform type in the configuration file; A language detection module configured to perform language detection on the incremental file data to obtain at least one single-language file, wherein each single-language file comprises word data of only one language type; A data matching module configured to, for each single-language file, match each word data in the single-language file with a full-database according to the language type of the single-language file; A data translation module configured to, for each word data in the at least one single-language file, perform multilingual translation on the word data according to a matching result when the word data is matched in the full-database to obtain a translation result of the word data; A second data acquisition module configured to obtain word data in the at least one single-language file that is not matched in the full-database to obtain first-type word data; A data processing module configured to add remark information to the first-type word data whose similarity to the word data of the full-database exceeds a preset similarity threshold, and merge the same first-type word data to obtain a word file to be output; A file division module configured to divide the word file to be output into at least one table file according to a business module type; A file sending module configured to, for each table file, send the table file to a translator of the business module type to which the table file belongs; A result acquisition module configured to obtain a translation result of word data fed back by the translator according to the table file. A result integration module is configured to integrate translation results of each entry data in the at least one single-language file to obtain a plurality of translation files of different language types of the incremental file data, wherein each of the translation files includes only entry data of one language type. A file generation module is configured to generate an internationalization file corresponding to the platform type according to each of the translation files.

6. The apparatus of claim 5, wherein, The data processing module is specifically configured to: For first type entry data with a similarity to the entry data of the full-database exceeding a preset similarity threshold, add a matching result with the highest similarity to the first type entry data in the full-database to a remark information of the first type entry data; Match the first type entry data under the Android platform type and the first type entry data under the IOS platform type, and if there is an isolated first type entry data with a failed matching, perform error correction labeling on the isolated first type entry data; Merge each of the first type entry data to obtain a to-be-output entry file. The apparatus further includes: A data detection module is configured to detect, for each entry data in the translation result, whether a business module type and a key-value pair corresponding to the entry data are correct. A data storage module is configured to, in a case where the business module type and the key-value pair corresponding to the entry data are correct, store content corresponding to the entry data in the translation result in the full-database and mark as to-be-upgraded. A data writing module is configured to write data marked as to-be-upgraded in the full-database into a corresponding translation file and clear the to-be-upgraded mark in the full-database. The apparatus further includes: A third data acquisition module is configured to acquire to-be-deleted entry data based on input of the Jenkins tool. A first data deletion module is configured to delete the to-be-deleted entry data and a translation result of the to-be-deleted entry data in the full-database. A second data deletion module is configured to pull a first internationalization file corresponding to the to-be-deleted entry data according to an SVN file path, and delete the to-be-deleted entry data or the translation result of the to-be-deleted entry data in the first internationalization file to obtain an updated internationalization file. A file uploading module is configured to upload the updated internationalization file according to the SVN file path.

7. An electronic device, comprising: It includes: A memory is configured to store a computer program. A processor is configured to execute the program stored in the memory to implement the method in any one of claims 1-4.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method in any one of claims 1-4.

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