Translation system and method and wearing equipment

Abstract

The invention relates to the technical field of translation, and discloses a translation system and method and a wearable device, and the translation system comprises a mobile terminal and the wearable device; the mobile terminal comprises application software, a load balancing server and a translation server cluster, and the translation server cluster comprises a plurality of translation servers; the wearable device is used for collecting voice data, processing the voice data and then sending the voice data to the mobile terminal; the mobile terminal is used for translating the voice data after data processing to obtain a translation result and feeding back the translation result to the wearable device, and the load balancing server is used for translating the voice data according to a plurality of translation tasks generated by the application software and the device state of each translation server. And determining to issue each translation task to the corresponding translation server to execute the translation task. The translation system can ensure the translation accuracy, improve the translation efficiency and the translation response speed, and meet the requirements of users in various complex language communication scenes.

Description

Technical Field

[0001] This application relates to the field of translation technology, and more particularly to a translation system, method, and wearable device. Background Technology

[0002] With the acceleration of globalization, the demand for cross-language communication is increasing. Existing translation systems suffer from significant delays and slow response times in processing voice input, transmitting data to servers, and waiting for server translation and results. Furthermore, existing translation systems are insufficiently adaptable to multilingual interaction scenarios. When multiple people participate in simultaneous communication involving mixed language dialogues, existing systems often struggle to accurately identify and translate the languages ​​of different speakers, leading to confusion, errors, and communication breakdowns. Summary of the Invention

[0003] In view of this, embodiments of this application provide a translation system, method, and wearable device that can effectively solve the problems of translation delay and poor communication in existing translation systems.

[0004] In a first aspect, embodiments of this application provide a translation system, including: a mobile terminal and a wearable device; the mobile terminal includes application software, a load balancing server, and a translation server cluster, the translation server cluster including a plurality of translation servers; The wearable device is used to collect the user's voice data, process the voice data, and send it to the mobile terminal. The mobile terminal is used to translate the processed voice data to obtain a translation result, and then feeds the translation result back to the wearable device, wherein: The load balancing server is used to determine, based on the several translation tasks generated by the application software and the device status of each translation server in the translation server cluster, to distribute each translation task to the corresponding translation server for execution. The translation task is a processing request to translate the user-input voice data into target language content.

[0005] In a first possible embodiment of the first aspect, the device state includes an idle state and a normal operating state; The load balancing server is also used to obtain the device status reported by each of the translation servers, and under the condition that the translation server is in the normal working state and in the idle state, the translation server is designated as a candidate translation server so that the candidate translation server waits to be assigned the translation task.

[0006] In a second possible embodiment of the first aspect, the device state further includes an abnormal operating state; The load balancing server is further configured to, when the candidate translation server is in the abnormal working state, stop assigning the translation task to the abnormal candidate translation server, and assign the unfinished translation task of the abnormal candidate translation server to the remaining candidate translation servers, so that the remaining candidate translation servers can continue to process the unfinished translation task.

[0007] In a third possible embodiment of the first aspect, the load balancing server is further configured to send a restart instruction to the abnormal candidate translation server after the unfinished translation task has been processed, so that the abnormal candidate translation server performs a restart operation; Once the abnormal candidate translation server has restarted and returned to normal operation, it will be re-designated as the candidate translation server.

[0008] In a fourth possible embodiment of the first aspect, the load balancing server is further configured to encapsulate and encrypt each translation task and the first checksum of each translation task in a target format to obtain encapsulated and encrypted data, and send the encapsulated and encrypted data to the candidate translation server; The candidate translation server is used to decrypt the encapsulated encrypted data after receiving it, and obtain the translation task and the first verification code corresponding to the encapsulated encrypted data. The candidate translation server is further configured to determine a second check code based on the translation task, determine whether the translation task passes the check based on the comparison result of the first check code and the second check code, and perform translation processing on the translation task if the translation task passes the check. The verification code is a verification field generated by a verification algorithm from the parameters of the translation task. The parameters of the translation task include the source of the content to be translated, the source language, the target language, and the content to be translated.

[0009] In a fifth possible embodiment of the first aspect, the candidate translation server is further configured to determine that the translation task passes the verification if the first verification code and the second verification code are consistent; If the first checksum and the second checksum are inconsistent, the translation task is determined to have failed the verification.

[0010] In a sixth possible embodiment of the first aspect, the wearable device is further configured to filter out audio interference information in the voice data to obtain filtered voice data, and to compress the filtered voice data and transmit it to the mobile terminal.

[0011] In a seventh possible embodiment of the first aspect, each of the candidate translation servers is configured to perform translation processing on the translation task, obtain the translation result, and send the translation result to the load balancing server, so that the load balancing server sends the translation result to the application software; The application software is also used to obtain the translation results sent by the load balancing server and feed the translation results back to the wearable device.

[0012] In an eighth possible embodiment of the first aspect, each of the candidate translation servers is further configured to convert the speech data into textual content to be translated through automatic language recognition, and after performing semantic segmentation, grammatical error correction and punctuation addition on the textual content to be translated, translate the textual content into target language content.

[0013] In a ninth possible embodiment of the first aspect, the translation task includes content to be translated, which includes one or more of voice data, text data, and image data. The text data is the content to be translated in text form input by the user through the application software, and the image data is the content to be translated in image form input by the user through the application software. The mobile terminal is also used to feed back the translation result to the user in a target format, which includes one or more of text, audio, and image formats.

[0014] In a tenth possible embodiment of the first aspect, the translation server cluster is used to process several translation tasks simultaneously through several candidate translation servers to obtain the translation results of each translation task; The translation server cluster is also used to upload the total translation tasks of all the candidate translation servers to the load balancing server.

[0015] Secondly, embodiments of this application provide a translation method, including: The user's voice data is collected by the wearable device, and the voice data is processed and sent to the mobile terminal. The translation result is obtained by translating the voice data processed by the mobile terminal. The mobile terminal includes application software, a load balancing server, and a translation server cluster, wherein the translation server cluster includes several translation servers; The load balancing server is used to determine, based on the several translation tasks generated by the application software and the device status of each translation server in the translation server cluster, to distribute each translation task to the corresponding translation server for execution.

[0016] Thirdly, embodiments of this application provide a wearable device, the wearable device including a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the translation method described above.

[0017] The embodiments of this application have the following beneficial effects: This embodiment of a translation system includes: a mobile terminal and a wearable device; the mobile terminal includes application software, a load balancing server, and a translation server cluster, the translation server cluster including several translation servers; the wearable device is used to collect user voice data, process the voice data, and send it to the mobile terminal; the mobile terminal is used to translate the processed voice data, obtain the translation result, and feed the translation result back to the wearable device, wherein: the load balancing server is used to determine which translation task to distribute to the corresponding translation server for execution based on several translation tasks generated by the application software and the device status of each translation server in the translation server cluster. Based on the above scheme, this translation system can translate processed voice data, significantly improving translation accuracy and avoiding interference from irrelevant voice data; by distributing several translation tasks to corresponding translation servers, it improves translation efficiency and response speed, achieving near real-time translation effects, ensuring smooth communication, and meeting the needs of users in various complex language communication scenarios. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram of the structure of a translation system according to an embodiment of this application is shown; Figure 2 This paper shows a schematic diagram of the structure of a load balancing server according to an embodiment of this application; Figure 3 A schematic diagram of a wearable device according to an embodiment of this application is shown; Figure 4 This paper shows a schematic diagram of the structure of an application software according to an embodiment of the present application; Figure 5 This paper illustrates a schematic diagram of a translation server cluster according to an embodiment of the present application. Figure 6 A flowchart illustrating a translation method according to an embodiment of this application is shown.

[0020] Explanation of key component symbols: 100 - Translation System; 110 - Mobile Terminal; 111 - Application Software; 1111 - Audio Processing Module; 1112 - Simultaneous Interpretation Module; 1113 - Dialogue Translation Module; 1114 - Text Translation Module; 1115 - Photo Translation Module; 112 - Load Balancing Server; 1121 - Cluster Monitoring Module; 1122 - Task Distribution Module; 1123 - Anomaly Handling Module; 113 - Translation Server Cluster; 1131 - Translation Server; 11311 - Voice Data Processing Module; 11312 - ASR Module; 11313 - Translation Module; 120 - Wearable Device; 121 - Microphone; 122 - Bluetooth Module; 123 - Data Processing Module. Detailed Implementation

[0021] The technical solutions in 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.

[0022] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0023] In the following text, the terms "comprising," "having," and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more combinations thereof. Furthermore, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0024] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0025] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0026] In today's increasingly globalized world, communication between different languages ​​is becoming more frequent, and the need to overcome language barriers is extremely urgent. Language barriers severely restrict the efficient conduct of many fields, including cross-border business cooperation, international academic exchange, and global tourism. In cross-border business meetings, language barriers make it difficult for representatives to accurately understand each other's viewpoints and intentions, leading to low communication efficiency and hindering cooperation. At international academic conferences, scholars cannot smoothly exchange research results, hindering the cross-border dissemination and innovative development of scholarship. When traveling globally, tourists encounter numerous difficulties in obtaining local information and communicating with residents due to language barriers, greatly impacting their travel experience. Therefore, developing an efficient, accurate, and convenient multilingual translation system has become a critical issue that urgently needs to be addressed.

[0027] Currently, some language translation technologies and related products exist on the market. For example, some smart translation devices use pre-set translation algorithms to translate input speech or text by building multiple language databases. Some online translation platforms, after users input source language content, leverage the powerful computing capabilities and large language models on their servers to quickly provide translation results. There are also some smart earphone products that, in conjunction with mobile applications, achieve simple voice translation functions. For instance, they receive user voice input, transmit it to the mobile application, the application uses an online translation interface to complete the translation, and then plays the translation result back to the user as speech through the earphones.

[0028] Taking a well-known brand of smart translation earphones as an example, its working principle is as follows: After the user turns on the earphones and connects to the mobile application, when translation is needed, they press and hold a specific button on the earphones to activate the voice input function, speak the content to be translated, and the earphones convert the voice signal into an electrical signal and transmit it to the mobile application. The mobile application connects to an online translation server via the network, and the server uses a specific translation algorithm to translate the text corresponding to the voice, generate the target language text, convert it back into voice format, and send it back to the mobile application, which finally plays it to the user. This method achieves voice translation to a certain extent and can meet the user's basic communication needs in scenarios with good network signal and relatively simple translation requirements.

[0029] However, these existing implementation schemes have many significant drawbacks. First, the translation accuracy is poor. In practical applications, language is highly complex, with factors such as polysemy, the diversity of grammatical structures, and the ever-changing contexts, which often lead to translation errors or inaccuracies in existing translation systems.

[0030] Secondly, the response speed is slow. Existing translation systems exhibit significant delays in processing voice input, transmitting data to the server, and waiting for the server to translate and return the result. In real-time dialogue scenarios, this delay disrupts the flow of communication, leading to disjointed conversations and severely impacting user experience. For example, in real-time communication during international business meetings, slow translation responses can cause speakers to wait excessively, interrupting their train of thought and reducing meeting efficiency.

[0031] Furthermore, there is an excessive reliance on the internet. Most existing translation systems, especially online translation platforms and smart devices that rely on internet-connected servers for translation, are almost impossible to function properly in environments with poor or no network signal, such as remote mountainous areas or underground parking lots, severely limiting their usage scenarios and scope. This is a serious constraint for business people, travelers, and other groups who frequently need to communicate in complex network environments.

[0032] Furthermore, existing translation systems lack adaptability in multilingual interactive scenarios. When multiple people participate in a conversation involving mixed languages, existing systems often struggle to accurately identify and translate the languages ​​of different speakers, leading to confusion and errors. At international academic conferences, where scholars using different languages ​​exchange ideas, existing translation systems often find it difficult to quickly and accurately handle such complex multilingual interactive scenarios.

[0033] To address the aforementioned issues, this application provides a translation system, method, and wearable device capable of processing speech data, converting it into text, and performing semantic segmentation and grammatical error correction to improve translation accuracy. Each translation task is distributed to idle and operational candidate translation servers, improving translation response speed and enabling scenarios with multiple participants engaging in simultaneous multilingual conversations, thus enhancing user experience. Furthermore, it reduces network dependence, functioning normally even in environments with poor network signal or no network access.

[0034] First, this application provides a translation system 100, please refer to... Figure 1 This is a schematic diagram of the structure of the translation system 100 provided in the embodiments of this application. Exemplarily, the translation system 100 includes: a mobile terminal 110 and a wearable device 120. The mobile terminal 110 includes application software 111, a load balancing server 112 and a translation server cluster 113. The translation server cluster 113 includes a plurality of translation servers 1131.

[0035] In this embodiment, the wearable device 120 is used to collect the user's voice data, process the voice data, and send it to the mobile terminal 110. The mobile terminal 110 is used to translate the processed voice data, obtain the translation result, and feed the translation result back to the wearable device 120. The load balancing server 112 is used to determine which translation task to distribute to the corresponding translation server 1131 for execution, based on the several translation tasks generated by the application software 111 and the device status of each translation server 1131 in the translation server cluster 113. The mobile terminal 110 includes, but is not limited to, mobile phones, tablet computers, and laptop computers.

[0036] Exemplarily, a translation task is a processing request to translate user-input speech data into target language content. This application effectively avoids task blocking and response delays in high-concurrency scenarios by introducing a load balancer server 112 to monitor and distribute translation tasks to the translation server cluster 113 in real time.

[0037] In one embodiment, the device status includes an idle state and a normal operating state. The load balancing server 112 is also used to obtain the device status reported by each translation server 1131, and under the condition that the translation server 1131 is in a normal operating state and an idle state, the translation server 1131 is selected as a candidate translation server so that the candidate translation server waits to be assigned a translation task.

[0038] In this embodiment, as Figure 2 As shown, the load balancing server 112 includes a cluster monitoring module 1121 and a task distribution module 1122. Each translation server 1131 periodically or promptly synchronizes its own device status when its device status changes, and also feeds back its own device status to the load balancing server 112. The cluster monitoring module 1121 is used to obtain the device status fed back by each translation server 1131, so as to achieve the purpose of real-time monitoring of the device status of the translation server 1131. The task distribution module 1122 is used to introduce a dual judgment mechanism of idle state and normal working state to determine the candidate translation server that can process translation tasks in real time, and distribute each translation task to the candidate translation server. This effectively improves the accuracy and speed of translation task scheduling, and avoids assigning translation tasks to abnormal translation servers 1131 that can work normally but cannot process translation tasks in real time, thus preventing further pressure on the high-load translation server 1131, thereby significantly reducing the response latency of translation tasks and improving the user experience in high-concurrency scenarios.

[0039] In one embodiment, the device state also includes an abnormal operating state. Exemplarily, the load balancer 112 is further configured to, when a candidate translation server is in an abnormal operating state, stop assigning translation tasks to the abnormal candidate translation server and assign the unfinished translation tasks of the abnormal candidate translation server to the remaining candidate translation servers, so that the remaining candidate translation servers can continue to process the unfinished translation tasks.

[0040] In this embodiment, when a candidate translation server encounters an anomaly during translation task processing, the load balancing server 112 can promptly identify the anomaly. The load balancing server 112 also includes an anomaly handling module 1123, which migrates unfinished translation tasks across servers to other normally functioning and idle candidate translation servers for continued processing. This avoids repeated user input and communication interruptions, greatly enhancing the system's stability and reliability under high concurrency and long-term operation scenarios. For example, if a candidate translation server experiences prolonged high-intensity operation leading to excessively high CPU (Central Processing Unit) or mobile terminal 110 temperatures, task processing time will significantly increase. The anomaly handling module 1123 will allocate unfinished translation tasks to other normally functioning and idle candidate translation servers, preventing translation task processing interruptions due to candidate translation server anomalies and ensuring translation task processing efficiency.

[0041] In another embodiment, the load balancer 112 is further configured to send a restart command to the abnormal candidate translation server after the incomplete translation task has been processed, so that the abnormal candidate translation server performs a restart operation. Once the abnormal candidate translation server has restarted and returned to normal working status, it is re-designated as a candidate translation server.

[0042] In this embodiment, the exception handling module 1123 in the load balancing server 112 is also used to trigger the automatic restart of the abnormal candidate translation server after the translation task is completed. After an individual candidate translation server exits abnormally, the load balancing server 112 can not only migrate its unfinished translation tasks in a timely manner, but also use the abnormal candidate translation server as a candidate translation server that can process translation tasks in real time when it recovers to normal, which greatly improves the system's adaptability and long-term operational stability.

[0043] In one embodiment, the translation server cluster 113 is used to process several translation tasks simultaneously through several candidate translation servers to obtain the translation results of each task. The translation server cluster 113 is also used to upload the total translation task volume of all candidate translation servers to the load balancing server 112.

[0044] In this embodiment, the translation server cluster 113 processes multiple translation tasks simultaneously through multiple candidate translation servers, improving the system's concurrent processing capability and meeting the needs of scenarios with multiple users or continuous input of multiple sentences. Simultaneously, the translation server cluster 113 uploads the total translation task volume information of all translation servers 1131 to the load balancing server 112 in real time, enabling the load balancing server 112 to make translation task scheduling decisions based on the dynamic load status of the translation server cluster 113.

[0045] In another embodiment, the load balancer 112 is further configured to encapsulate and encrypt each translation task and the first checksum of each translation task in a target format to obtain encapsulated and encrypted data, and send the encapsulated and encrypted data to the candidate translation server.

[0046] For example, the parameters of the translation task include, but are not limited to, the source of the content to be translated, the source language, the target language, and the content to be translated. The checksum is a verification field generated by a verification algorithm from the parameters of the translation task. The first checksum is used at the receiving end to verify whether the translation task has been tampered with or corrupted during transmission. Verification algorithms include, but are not limited to, CRC32 (Cyclic Redundancy Check 32-bit), MD5 (Message Digest Algorithm 5), and SHA-Secure Hash Algorithm 1.

[0047] In one embodiment, the candidate translation server, upon receiving the encapsulated encrypted data, decrypts the encapsulated encrypted data to obtain the translation task and a first verification code corresponding to the encapsulated encrypted data. The candidate translation server is further configured to determine a second verification code based on the translation task, and determine whether the translation task passes verification based on the comparison result of the first and second verification codes. If the translation task passes verification, the translation task is then processed.

[0048] In this embodiment, the parameters of the translation task and the first checksum of the translation task can be assembled into JSON (JavaScript Object Notation) format data, encrypted using the AES-256 symmetric encryption algorithm, and then transmitted to the corresponding candidate translation server. The candidate translation server can use the key to decode the encapsulated encrypted data to obtain the parameters of the translation task and the first checksum. The parameters of the translation task are then used to determine the second checksum using the same verification algorithm. The candidate translation server is also used to determine that the translation task passes the verification if the first checksum and the second checksum match, indicating that the translation task has not been tampered with and has passed the integrity verification; if the first checksum and the second checksum do not match, the translation task fails the verification, indicating that the translation task has experienced data abnormality or tampering during transmission, and the translation task is refused to be executed and a verification failure response is returned.

[0049] In this embodiment, by encapsulating and encrypting the translation task parameters together with the first verification code, secure transmission between the load balancing server 112 and the translation server 1131 is achieved, which can verify the integrity of the data and prevent tampering with the translation task request.

[0050] For example, speech data is an audio signal carrying the user's spoken content, used for subsequent operations such as language recognition and translation. For example... Figure 3 As shown, the wearable device 120 includes, but is not limited to, a microphone 121, a Bluetooth module 122, and a data processing module 123. The wearable device 120 can collect the user's audio data through the microphone 121 and establish a connection with the mobile terminal 110 through the Bluetooth module 122. The Bluetooth connection can enable the transmission of voice data from the wearable device 120 to the mobile terminal 110 when there is no network, as well as receive the translation results in audio form fed back by the mobile terminal 110, reducing the dependence on the network.

[0051] In one embodiment, the wearable device 120 is further configured to filter out audio interference information in the voice data to obtain filtered voice data, and to compress the filtered voice data before transmitting it to the mobile terminal 110. In this embodiment, to improve the accuracy and real-time performance of voice translation, the wearable device 120 can perform filtering, noise reduction, and compression processing on the audio data through the data processing module 123. Noise reduction can eliminate environmental interference and ensure the input quality of subsequent recognition and translation; compression reduces the amount of data, lowers wireless transmission power consumption and latency, and improves translation response speed.

[0052] In one embodiment, a time-frequency feature model of noise can be constructed based on the non-speech segments in the input audio data. Based on this model, a filter is used to separate audio interference information from the audio data, outputting denoised audio data. The denoised audio data can be compressed using the Opus encoding / decoding algorithm before transmission; for example, the denoised audio data can be compressed by 16 times to reduce the transmission load.

[0053] In one embodiment, the content to be translated includes one or more of voice data, text data, and image data. The text data is the text-based content to be translated input by the user through application software 111, and the image data is the image-based content to be translated input by the user through application software 111. The translation task can also be a processing request to translate the user-input text data or image data into target language content.

[0054] Exemplary, such as Figure 4 As shown, the application software 111 includes an audio processing module 1111, a simultaneous translation module 1112, a dialogue translation module 1113, a text translation module 1114, and a photo translation module 1115. The application software 111 can support multiple systems, including but not limited to Android, iOS, Windows, and mosOS.

[0055] The audio processing module 1111 acquires voice data collected by the mobile terminal 110, meaning it doesn't need to acquire voice data sent by the wearable device 120; the mobile terminal 110 can independently acquire user-input voice data, and the audio processing module 1111 performs noise reduction filtering on the voice data. The simultaneous interpretation module 1112 performs real-time recognition of continuous speech streams and sends the corresponding translation tasks to the load balancing server 112 and the translation server cluster 113, enabling real-time translation of continuous speech streams, suitable for conference and lecture scenarios. The dialogue translation module 1113 automatically segments the target language of alternating speech by two people and sends the corresponding translation tasks to the load balancing server 112 and the translation server cluster 113, enabling bidirectional translation. The text translation module 1114 processes user-input text data and sends the corresponding translation tasks to the load balancing server 112 and the translation server cluster 113, providing instant text translation responses. The photo translation module 1115 processes the image data input by the user and sends the corresponding translation task to the load balancer server 112 and the translation server cluster 113 to provide an instant photo translation response.

[0056] In one embodiment, the application software 111 can respond to the target language set by the user, obtain voice data sent by the wearable device 120, or obtain text data and image data input by the user through the mobile terminal 110, determine the source language information associated with the content to be translated, and can automatically detect or set by the user. The application software 111 generates an independent translation task based on the current content to be translated, the source language, the target language, and the content to be translated, realizing the transformation from the input of the content to be translated to an executable translation request or instruction.

[0057] In another embodiment, each candidate translation server is used to process the translation task, obtain the translation result, and send the translation result to the load balancing server 112, so that the load balancing server 112 sends the translation result to the application software 111. The application software 111 is also used to obtain the translation result sent by the load balancing server 112 and feed the translation result back to the wearable device 120.

[0058] In this embodiment, after the candidate translation server completes the translation, it returns the result to the load balancing server 112. The load balancing server 112 forwards the translation result to the corresponding application software 111. After receiving the result, the application software 111 pushes the translation result to the wearable device 120 used by the corresponding user via Bluetooth, thereby achieving the final feedback to the user. This ensures the accurate matching of translation requests and responses and supports a real-time cross-language interactive experience with multiple users, high concurrency, and low latency.

[0059] In one embodiment, when a candidate translation server receives a translation task with voice data, each candidate translation server is further configured to convert the voice data into text-based content to be translated through automatic language recognition, perform semantic segmentation, grammatical error correction, and add punctuation marks to the text-based content to be translated into the target language content.

[0060] In this embodiment, as Figure 5As shown, each translation server 1131 includes a speech data processing module 11311, an ASR (Automatic Speech Recognition) module 11312, and a translation module 11313. The speech data processing module 11311 decodes the compressed speech data. The ASR module 11312 converts the decoded speech data into text, analyzes the acoustic and linguistic features in the audio, and identifies the language type, including but not limited to Chinese, English, Japanese, or French. Simultaneously, it performs semantic segmentation based on semantic boundaries, corrects grammatical errors, and automatically adds punctuation marks such as periods, commas, and question marks to output standardized text with complete structure and clear semantics for subsequent translation by the translation module 11313, improving the accuracy of subsequent translations. The translation module 11313 performs language conversion processing on the received content to be translated, automatically translating it from the source language to the target language, generating a semantically accurate and grammatically correct target language translation. It should be noted that the translation technology used by the translation module 11313 is known in the field, and its structure and principle will not be elaborated here.

[0061] In another embodiment, for text-based content to be translated, the candidate translation server can translate it into the target language translation using a translation module. For image-based content to be translated, the candidate translation server can obtain the text in the image through Optical Character Recognition (OCR), convert it into text-based content to be translated, and then translate it into the target language translation using a translation module. The mobile terminal 110 is also used to feed back the translation results to the user in the target format, which includes one or more of the following formats: text, audio, and images.

[0062] As an example, after obtaining the translation results, the application software 111 in the mobile terminal 110 can directly feed them back to the user in the form of text, audio or image fusion, or it can convert the translation results into voice data and send them to the wearable device 120 to feed them back to the user, thereby improving the user experience.

[0063] Figure 6 A schematic flowchart of a translation method according to an embodiment of this application is shown. Exemplarily, this translation method is applied to a wearable device 120 and specifically includes the following steps: S210 collects the user's voice data through the wearable device 120, processes the voice data, and sends it to the mobile terminal 110.

[0064] S220: Obtain the translation result obtained by translating the voice data processed by the mobile terminal 110.

[0065] The mobile terminal 110 includes application software 111, load balancing server 112, and translation server cluster 113. The translation server cluster 113 includes several translation servers 1131. The load balancing server 112 is used to determine which translation task to send to the corresponding translation server 1131 for execution based on the several translation tasks generated by the application software 111 and the device status of each translation server 1131 in the translation server cluster 113.

[0066] It is understood that the method in this embodiment corresponds to the translation system 100 in the above embodiment, and the options in the above embodiment are also applicable to this embodiment, so they will not be described again here.

[0067] This application also provides a wearable device 120, exemplary of which includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to cause the terminal device to perform the above-described translation method. The wearable device 120 includes, but is not limited to, wireless headphones, wired headphones, hearing aids, head-mounted displays, etc.

[0068] The processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, including at least one of a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Network Processor (NP), Digital Signal Processor (DSP), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0069] The memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory is used to store computer programs, and the processor can execute the computer programs accordingly after receiving execution instructions.

[0070] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that, as an alternative implementation, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0071] In addition, the functional modules or units in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0072] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a smartphone, personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0073] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A translation system, characterized in that, include: Mobile terminal and wearable device; the mobile terminal includes application software, a load balancing server and a translation server cluster, the translation server cluster including a plurality of translation servers; The wearable device is used to collect the user's voice data, process the voice data, and send it to the mobile terminal. The mobile terminal is used to translate the processed voice data to obtain a translation result, and then feeds the translation result back to the wearable device, wherein: The load balancing server is used to determine, based on the several translation tasks generated by the application software and the device status of each translation server in the translation server cluster, to distribute each translation task to the corresponding translation server for execution. The translation task is a processing request to translate the user-input voice data into target language content.

2. The translation system according to claim 1, characterized in that, The device status includes idle status and normal working status; The load balancing server is also used to obtain the device status reported by each of the translation servers, and under the condition that the translation server is in the normal working state and in the idle state, the translation server is designated as a candidate translation server so that the candidate translation server waits to be assigned the translation task.

3. The translation system according to claim 2, characterized in that, The device status also includes abnormal operating status; The load balancing server is further configured to, when the candidate translation server is in the abnormal working state, stop assigning the translation task to the abnormal candidate translation server, and assign the unfinished translation task of the abnormal candidate translation server to the remaining candidate translation servers, so that the remaining candidate translation servers can continue to process the unfinished translation task.

4. The translation system according to claim 3, characterized in that, The load balancing server is also used to send a restart command to the abnormal candidate translation server after the unfinished translation task is completed, so that the abnormal candidate translation server performs a restart operation; Once the abnormal candidate translation server has restarted and returned to normal operation, it will be re-designated as the candidate translation server.

5. The translation system according to claim 2, characterized in that, The load balancing server is also used to encapsulate and encrypt each translation task and the first checksum of each translation task in a target format to obtain encapsulated and encrypted data, and send the encapsulated and encrypted data to the candidate translation server; The candidate translation server is used to decrypt the encapsulated encrypted data after receiving it, and obtain the translation task and the first verification code corresponding to the encapsulated encrypted data. The candidate translation server is further configured to determine a second check code based on the translation task, determine whether the translation task passes the check based on the comparison result of the first check code and the second check code, and perform translation processing on the translation task if the translation task passes the check. The verification code is a verification field generated by a verification algorithm from the parameters of the translation task. The parameters of the translation task include the source of the content to be translated, the source language, the target language, and the content to be translated.

6. The translation system according to claim 5, characterized in that, The candidate translation server is also used to determine that the translation task passes the verification if the first verification code and the second verification code are consistent. If the first checksum and the second checksum are inconsistent, the translation task is determined to have failed the verification.

7. The translation system according to claim 1, characterized in that, The wearable device is also used to filter out audio interference information in the voice data to obtain filtered voice data, and to compress the filtered voice data before transmitting it to the mobile terminal.

8. The translation system according to claim 2, characterized in that, Each candidate translation server is used to process the translation task, obtain the translation result, and send the translation result to the load balancing server, so that the load balancing server sends the translation result to the application software; The application software is also used to obtain the translation results sent by the load balancing server and feed the translation results back to the wearable device.

9. The translation system according to claim 2, characterized in that, Each of the candidate translation servers is further configured to convert the speech data into textual content to be translated through automatic language recognition, and after performing semantic segmentation, grammatical error correction, and punctuation addition on the textual content, translate the textual content into the target language content.

10. The translation system according to claim 1, characterized in that, The translation task includes content to be translated, which includes one or more of the following: voice data, text data, and image data. The text data is the text content to be translated input by the user through the application software, and the image data is the image content to be translated input by the user through the application software. The mobile terminal is also used to feed back the translation result to the user in a target format, which includes one or more of text, audio, and image formats.

11. The translation system according to claim 2, characterized in that, The translation server cluster is used to process several translation tasks simultaneously through several candidate translation servers to obtain the translation results of each translation task; The translation server cluster is also used to upload the total translation tasks of all the candidate translation servers to the load balancing server.

12. A translation method, characterized in that, include: The user's voice data is collected by wearing a device, and the voice data is processed and sent to the mobile terminal. The translation result is obtained by translating the voice data processed by the mobile terminal. The mobile terminal includes application software, a load balancing server, and a translation server cluster, wherein the translation server cluster includes several translation servers; The load balancing server is used to determine, based on the several translation tasks generated by the application software and the device status of each translation server in the translation server cluster, to distribute each translation task to the corresponding translation server for execution.

13. A wearable device, characterized in that, The wearable device includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the translation method of claim 12.

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