Intelligent translation machine, intelligent translation method and application thereof

Abstract

The invention belongs to the technical field of intelligent translation, and discloses an intelligent translation machine, an intelligent translation method and application thereof, and the intelligent translation machine comprises a voice acquisition module, a voice analysis module, a database module, a keyword extraction module, a translation module, a result evaluation module, a man-machine interaction module, an instruction analysis module, an instruction feedback module and a central processing and control module. Through the keyword extraction module and the professional term database, terms in a specific field can be recognized and translated more accurately, deviation is avoided, and translation accuracy is improved; factors such as cultural backgrounds, contexts and rhetorics are considered, so that translated texts better conform to expression habits of target languages, and original charm and emotional colors are kept; a user can modify translation content through the man-machine interaction module, and meanwhile, the result evaluation module can give feedback of translation accuracy, so that the user can know expression intentions in time and modify inaccurate expressions in time, and the translation accuracy is further improved.

Description

Technical Field

[0001] This invention belongs to the field of intelligent translation technology, and in particular relates to an intelligent translation machine, an intelligent translation method, and their applications. Background Technology

[0002] With globalization, machine translation plays an increasingly important role in cross-language communication. However, traditional machine translation technologies, such as rule-based translation, statistical translation, and deep learning-based translation, still have many shortcomings in handling large-scale corpora and complex linguistic phenomena.

[0003] Due to a lack of in-depth understanding of specialized fields, traditional machine translation often deviates when handling terminology in specific domains, leading to inaccurate translations in professional contexts and potentially misleading readers. Traditional machine translation typically relies on pre-trained models and corpora; however, due to the complexity and dynamism of language itself, and semantic changes across different contexts, these methods struggle to capture all linguistic phenomena, thus affecting translation accuracy. One of the challenges of machine translation is preserving the context and rhetoric of the original text in the translation. Traditional machine translation often only performs word-for-word translation, neglecting cultural background, context, and rhetoric, resulting in translations that lose their original flavor and emotional nuance. Different application scenarios have different translation needs and standards, and traditional machine translation, due to its generality and limitations, struggles to meet the translation requirements of various specific scenarios. Traditional machine translation typically lacks an accuracy evaluation mechanism; users cannot predict the accuracy of the translation result and therefore cannot adjust and optimize it according to the actual situation. Because of the lack of feedback on translation accuracy, users often need to modify and adjust the entire translation, increasing their burden and impacting translation efficiency.

[0004] To address the aforementioned problems with existing machine translation, this invention proposes an intelligent translator with real-time rhetoric capabilities, an intelligent translation method, and its applications. Summary of the Invention

[0005] To overcome the problems existing in related technologies, the present invention discloses an intelligent translator, an intelligent translation method, and their applications.

[0006] The technical solution is as follows: A smart translator includes:

[0007] The voice acquisition module is used to collect the user's voice data using the voice acquisition component, obtain voice segments, and convert them into digital signals;

[0008] The speech analysis module analyzes and processes the speech data after speech processing, identifies and extracts words and phrases, and obtains the speech data to be translated.

[0009] The database module is used to store multi-language data and preset parameters using a database.

[0010] The keyword extraction module extracts keywords from the speech to be translated by obtaining information from the database, including translation optimization information, professional terminology, common words, and idioms, and divides the speech into keyword part and regular part;

[0011] The translation module is used to translate the extracted keywords and regular parts. First, it performs Chinese-to-foreign language translation, then foreign language-to-Chinese translation, and finally Chinese-to-foreign language translation to obtain more accurate translation results.

[0012] The results evaluation module evaluates the translation results, compares their matching degree with the original speech, and provides the most reasonable translation results among the four translations, marking them as the best translation results.

[0013] The human-computer interaction module receives and displays the interaction information between the user and the machine, displays the translation results to the user, and allows the user to modify the translation content as needed;

[0014] The instruction analysis module parses the user instructions received by the human-computer interaction module, analyzes their content, and determines the instructions that need to be executed.

[0015] The instruction feedback module executes corresponding instruction operations and modifies the content based on the analysis results of the instruction analysis module.

[0016] The central processing and control module is connected to the voice acquisition module, voice analysis module, database module, keyword extraction module, translation module, result evaluation module, human-computer interaction module, instruction analysis module, and instruction feedback module. It is used to receive information from each module, process and make decisions according to preset logic and rules, coordinate the work of each module, and control the execution of the entire translation process.

[0017] In one embodiment, the intelligent translator further includes a training and optimization module, which is connected to the translation module and is used to train and optimize the translation model of the translation module based on the translation results confirmed by the user.

[0018] In one embodiment, the voice acquisition module includes a microphone, a signal filtering unit, an AD conversion unit, and a signal amplification unit connected in sequence. The signal filtering unit performs low-pass filtering on the voice data acquired by the microphone, the AD conversion unit converts the voice data into a digital signal, and the signal amplification unit amplifies and enhances the digital signal.

[0019] In one embodiment, the voice analysis module includes a voiceprint recognition unit, which is used to compare the voiceprint features in the collected voice information with the pre-stored user voiceprint features to determine whether the collected voice information comes from a set user.

[0020] Another object of the present invention is to provide an intelligent translation method, the intelligent translation method comprising:

[0021] S1: Select the multiple language data that need to be translated and store them in the database, and use the human-computer interaction module to preset the input of control parameters;

[0022] S2: The voice acquisition component collects the user's voice data, obtains voice segments, and converts them into digital signals; the voice analysis module analyzes and processes the processed voice data, identifies and extracts words and phrases, and obtains the voice data to be translated.

[0023] S3: The keyword extraction module obtains information from the database, including translation optimization information, professional terms, common words, and idioms, and extracts keywords from the speech to be translated, dividing the speech into keyword part and regular part;

[0024] S4: Translate the extracted keywords and regular parts. First, translate from Chinese to foreign language, then translate from foreign language to Chinese, and finally translate from Chinese to foreign language again to obtain a more accurate translation result.

[0025] S5: The result evaluation module evaluates the translation results, compares their matching degree with the original speech, gives the most reasonable translation results among the four translations, and marks them as the best translation results;

[0026] S6: The human-computer interaction module receives and displays the interaction information between the user and the machine, displays the translation results to the user, and allows the user to modify the translation content as needed;

[0027] S7: The instruction analysis module parses the user instructions received by the human-computer interaction module, analyzes their content, and determines the instructions that need to be executed. The instruction feedback module executes the corresponding instruction operation and modifies the content based on the analysis results of the instruction analysis module.

[0028] In one embodiment, the intelligent translation method further includes: using a training optimization module to train and optimize the translation model of the translation module based on the translation results confirmed by the user, specifically including:

[0029] The system reads user-defined modification instructions for the translation results and generates corresponding training data. This data includes the original translation content, the modified translation content, and the corresponding modification instructions. Using the generated training data, the translation module's translation model is adjusted by modifying model parameters, updating the lexicon, or improving translation strategies. After updating the translation model, the new model is tested and validated, and user feedback is continuously collected to iterate and optimize the model.

[0030] In one embodiment, in step S2, when the voice acquisition component acquires the user's voice data, it first uses the voiceprint recognition unit to compare the voiceprint features in the acquired voice information with the pre-stored user voiceprint features to determine whether the acquired voice information comes from a set user. If it does, the subsequent translation operation is performed; otherwise, the subsequent processing steps are terminated.

[0031] Combining all the above technical solutions, the advantages and positive effects of this invention are as follows:

[0032] This invention, through a keyword extraction module and a database of specialized terms, can more accurately identify and translate terms in specific fields, avoiding common biases in traditional machine translation and improving translation accuracy. It not only performs word-to-word translation but also considers cultural background, context, and rhetoric, making the translation more consistent with the target language's expression habits and preserving its original flavor and emotional tone. Users can modify the translation through a human-computer interaction module, while the result evaluation module provides feedback on the translation accuracy, allowing users to immediately understand the intended meaning and promptly correct inaccurate expressions, further improving translation accuracy.

[0033] This invention, through the coordination of a central processing and control module, can adjust translation strategies according to different scenarios and needs, providing more personalized translation services. Due to the collaborative work between various modules, as well as continuous training and optimization based on user feedback, it can significantly improve translation efficiency and provide users with faster and more accurate translation services.

[0034] This invention uses a voiceprint recognition unit as a security measure to ensure that only authorized users can use the translation function, thus protecting the security and privacy of user data. The training and optimization module can continuously train and optimize based on user feedback and actual usage, thereby continuously improving translation quality and performance. Attached Figure Description

[0035] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure;

[0036] Figure 1 This is a structural schematic diagram of the intelligent translator provided in an embodiment of the present invention;

[0037] Figure 2 This is a flowchart of the intelligent translation method provided in an embodiment of the present invention;

[0038] In the diagram: 1. Voice acquisition module; 2. Voice analysis module; 3. Database module; 4. Keyword extraction module; 5. Translation module; 6. Result evaluation module; 7. Human-computer interaction module; 8. Instruction analysis module; 9. Instruction feedback module; 10. Central processing and control module; 11. Training optimization module. Detailed Implementation

[0039] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0040] Example 1:

[0041] like Figure 1 As shown, the intelligent translator provided in this embodiment of the invention includes:

[0042] Voice acquisition module 1 is used to acquire the user's voice data using the voice acquisition component, obtain voice segments, and convert them into digital signals;

[0043] Speech analysis module 2 analyzes and processes the speech data after speech processing, identifies and extracts words and phrases, and obtains the speech data to be translated;

[0044] Database module 3 is used to store multi-language data and preset parameters using a database;

[0045] Keyword extraction module 4 extracts keywords from the speech to be translated by acquiring information from the database, including translation optimization information, professional terminology, common words, and idioms, and divides the speech to be translated into a keyword part and a regular part;

[0046] Translation module 5 is used to translate the extracted keywords and regular parts. First, it performs Chinese-to-foreign language translation, then foreign language-to-Chinese translation, and finally Chinese-to-foreign language translation to obtain more accurate translation results.

[0047] Result evaluation module 6 evaluates the translation results, compares their matching degree with the original speech, gives the most reasonable translation results among the four translations, and marks them as the best translation results;

[0048] The human-computer interaction module 7 receives and displays the interaction information between the user and the machine, displays the translation results to the user, and allows the user to modify the translation content as needed;

[0049] The instruction analysis module 8 parses the user instructions received by the human-computer interaction module, analyzes their content, and determines the instructions that need to be executed.

[0050] The instruction feedback module 9 executes corresponding instruction operations and modifies the content based on the analysis results of the instruction analysis module.

[0051] The central processing and control module 10 is connected to the voice acquisition module 1, voice analysis module 2, database module 3, keyword extraction module 4, translation module 5, result evaluation module 6, human-computer interaction module 7, instruction analysis module 8, and instruction feedback module 9, respectively. It is used to receive information from each module, process and make decisions according to preset logic and rules, coordinate the work of each module, and control the execution of the entire translation process.

[0052] The intelligent translator provided in this invention, through a keyword extraction module and a database of professional terms, can more accurately identify and translate terms in specific fields, avoiding common deviations in traditional machine translation and improving translation accuracy. It not only performs word-to-word translation but also considers cultural background, context, and rhetoric, making the translation more consistent with the expression habits of the target language and maintaining its original flavor and emotional tone. Users can modify the translated content through the human-computer interaction module, while the result evaluation module provides feedback on the translation accuracy, allowing users to immediately understand the intended meaning and promptly correct inaccurate expressions, further improving translation accuracy.

[0053] Preferably, the voice acquisition module in this embodiment of the invention includes a microphone, a signal filtering unit, an AD conversion unit, and a signal amplification unit connected in sequence. The signal filtering unit is used to perform low-pass filtering on the voice data acquired by the microphone, the AD conversion unit converts the voice data into a digital signal, and the signal amplification unit is used to amplify and enhance the digital signal.

[0054] Preferably, the voice analysis module in this embodiment of the invention includes a voiceprint recognition unit, which is used to compare the voiceprint features in the collected voice information with the pre-stored user voiceprint features to determine whether the collected voice information comes from a set user.

[0055] Example 2:

[0056] Based on Example 1, this embodiment adds a training optimization module 11 to meet the dialogue habits of different users during use. The training optimization module 11 is connected to the translation module 5 and is used to train and optimize the translation model of the translation module according to the translation results confirmed by the user.

[0057] This embodiment continuously improves its translation quality and performance by collecting user feedback and optimization suggestions, thus providing users with better translation services.

[0058] Example 3:

[0059] like Figure 2 As shown, the intelligent translation method provided in this embodiment of the invention includes the following steps:

[0060] S1: Select the multiple language data that need to be translated and store them in the database, and use the human-computer interaction module to preset the input of control parameters;

[0061] S2: The voice acquisition component collects the user's voice data, obtains voice segments, and converts them into digital signals; the voice analysis module analyzes and processes the processed voice data, identifies and extracts words and phrases, and obtains the voice data to be translated.

[0062] S3: The keyword extraction module obtains information from the database, including translation optimization information, professional terms, common words, and idioms, and extracts keywords from the speech to be translated, dividing the speech into keyword part and regular part;

[0063] S4: Translate the extracted keywords and regular parts. First, translate from Chinese to foreign language, then translate from foreign language to Chinese, and finally translate from Chinese to foreign language again to obtain a more accurate translation result.

[0064] S5: The result evaluation module evaluates the translation results, compares their matching degree with the original speech, gives the most reasonable translation results among the four translations, and marks them as the best translation results;

[0065] S6: The human-computer interaction module receives and displays the interaction information between the user and the machine, displays the translation results to the user, and allows the user to modify the translation content as needed;

[0066] S7: The instruction analysis module parses the user instructions received by the human-computer interaction module, analyzes their content, and determines the instructions that need to be executed. The instruction feedback module executes the corresponding instruction operation and modifies the content based on the analysis results of the instruction analysis module.

[0067] Preferably, the intelligent translation method in this embodiment of the invention further includes: using a training and optimization module to train and optimize the translation model of the translation module based on the translation results confirmed by the user, specifically including:

[0068] The system reads user-defined modification instructions for the translation results and generates corresponding training data. This data includes the original translation content, the modified translation content, and the corresponding modification instructions. Using the generated training data, the translation module's translation model is adjusted by modifying model parameters, updating the lexicon, or improving translation strategies. After updating the translation model, the new model is tested and validated, and user feedback is continuously collected to iterate and optimize the model.

[0069] Preferably, in step S2 of this embodiment of the invention, when the voice acquisition component acquires the user's voice data, it first uses the voiceprint recognition unit to compare the voiceprint features in the acquired voice information with the pre-stored user voiceprint features to determine whether the acquired voice information comes from a set user. If it comes from a set user, the subsequent translation operation is then performed; otherwise, the subsequent processing steps are terminated.

[0070] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0071] Based on the technical solutions described in the above embodiments of the present invention, the following application examples can be further proposed.

[0072] According to an embodiment of this application, the present invention also provides an information data processing terminal, which is used to implement the intelligent translation method provided in embodiment 3.

[0073] This invention also provides a computer device, which includes a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the intelligent translation method provided in embodiment 3.

[0074] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the intelligent translation method provided in Embodiment 3.

[0075] The information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of the present invention. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0076] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this invention. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments.

[0077] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a photographic device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0078] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0079] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention and within the spirit and principles of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A smart translator, characterized in that, The intelligent translator includes: The voice acquisition module is used to collect the user's voice data using the voice acquisition component, obtain voice segments, and convert them into digital signals; The speech analysis module analyzes and processes the speech data after speech processing, identifies and extracts words and phrases, and obtains the speech data to be translated. The database module is used to store multi-language data and preset parameters using a database. The keyword extraction module extracts keywords from the speech to be translated by obtaining information from the database, including translation optimization information, professional terminology, common words, and idioms, and divides the speech into keyword part and regular part; The translation module is used to translate the extracted keywords and regular parts. First, it performs Chinese-to-foreign language translation, then foreign language-to-Chinese translation, and finally Chinese-to-foreign language translation to obtain more accurate translation results. The results evaluation module evaluates the translation results, compares their matching degree with the original speech, and provides the most reasonable translation results among the four translations, marking them as the best translation results. The human-computer interaction module receives and displays the interaction information between the user and the machine, displays the translation results to the user, and allows the user to modify the translation content as needed; The instruction analysis module parses the user instructions received by the human-computer interaction module, analyzes their content, and determines the instructions that need to be executed. The instruction feedback module executes corresponding instruction operations and modifies the content based on the analysis results of the instruction analysis module. The central processing and control module is connected to the voice acquisition module, voice analysis module, database module, keyword extraction module, translation module, result evaluation module, human-computer interaction module, instruction analysis module, and instruction feedback module. It is used to receive information from each module, process and make decisions according to preset logic and rules, coordinate the work of each module, and control the execution of the entire translation process.

2. The intelligent translator according to claim 1, characterized in that, The intelligent translator also includes a training and optimization module, which is connected to the translation module and is used to train and optimize the translation model of the translation module based on the translation results confirmed by the user.

3. The intelligent translator according to claim 1, characterized in that, The voice acquisition module includes a microphone, a signal filtering unit, an AD conversion unit, and a signal amplification unit connected in sequence. The signal filtering unit performs low-pass filtering on the voice data acquired by the microphone, the AD conversion unit converts the voice data into a digital signal, and the signal amplification unit amplifies and enhances the digital signal.

4. The intelligent translator according to claim 1, characterized in that, The voice analysis module includes a voiceprint recognition unit, which compares the voiceprint features in the collected voice information with the pre-stored user voiceprint features to determine whether the collected voice information comes from a set user.

5. An intelligent translation method for implementing the intelligent translator according to any one of claims 1 to 4, characterized in that, The intelligent translation method includes: S1: Select the multiple language data that need to be translated and store them in the database, and use the human-computer interaction module to preset the input of control parameters; S2: The voice acquisition component collects the user's voice data, obtains voice segments, and converts them into digital signals; the voice analysis module analyzes and processes the processed voice data, identifies and extracts words and phrases, and obtains the voice data to be translated. S3: The keyword extraction module obtains information from the database, including translation optimization information, professional terms, common words, and idioms, and extracts keywords from the speech to be translated, dividing the speech into keyword part and regular part; S4: Translate the extracted keywords and regular parts. First, translate from Chinese to foreign language, then translate from foreign language to Chinese, and finally translate from Chinese to foreign language again to obtain a more accurate translation result. S5: The result evaluation module evaluates the translation results, compares their matching degree with the original speech, gives the most reasonable translation results among the four translations, and marks them as the best translation results; S6: The human-computer interaction module receives and displays the interaction information between the user and the machine, displays the translation results to the user, and allows the user to modify the translation content as needed; S7: The instruction analysis module parses the user instructions received by the human-computer interaction module, analyzes their content, and determines the instructions that need to be executed. The instruction feedback module executes the corresponding instruction operation based on the analysis results of the instruction analysis module and modifies the content.

6. The intelligent translation method according to claim 5, characterized in that, The intelligent translation method further includes: using a training and optimization module to train and optimize the translation model of the translation module based on the translation results confirmed by the user, specifically including: The system reads user-defined modification instructions for the translation results and generates corresponding training data. This data includes the original translation content, the modified translation content, and the corresponding modification instructions. Using the generated training data, the translation module's translation model is adjusted by modifying model parameters, updating the lexicon, or improving translation strategies. After updating the translation model, the new model is tested and validated, and user feedback is continuously collected to iterate and optimize the model.

7. The intelligent translation method according to claim 5, characterized in that, In step S2, when the voice acquisition component collects the user's voice data, it first uses the voiceprint recognition unit to compare the voiceprint features in the collected voice information with the pre-stored user voiceprint features to determine whether the collected voice information comes from the set user. If it does, the subsequent translation operation is performed; otherwise, the subsequent processing steps are terminated.

8. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the intelligent translation method according to any one of claims 5 to 7.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the intelligent translation method according to any one of claims 5 to 7.

10. A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the intelligent translation method according to any one of claims 5 to 7.

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