Broadcast television transmission method and network system

Abstract

The invention discloses a radio and television transmission method and a network system, and relates to the technical field of computer networks and communication, and the method comprises the steps: S1, dynamically generating and displaying a candidate word list containing a plurality of candidate words based on pinyin or coding information input by a user; s2, adjusting the arrangement sequence of the candidate word list in real time according to the input operation of a user; s3, when the number of the candidate words exceeds a preset threshold value, automatically dividing and scrolling to display a candidate word page, and reducing page turning operation of a user; s4, receiving a selection instruction of the user, and sending the selected candidate word as final input content to the target application program; according to the broadcast television transmission method and the network system, the security and integrity of user privacy can be ensured in the input data transmission process, the input data is effectively prevented from being leaked or tampered in the transmission process, and a safe and reliable use guarantee is provided for a user.

Description

Technical Field

[0001] The present invention relates to the field of computer network and communication technology, and in particular to a broadcast television transmission method and a network system. Background Art

[0002] In modern computer applications, Chinese character input is one of the basic needs of Chinese computer users. Since there are tens of thousands of Chinese characters and there is no direct correspondence between them and the 26 English letters on the keyboard, users need to use Chinese input software running on the operating system to input Chinese characters into the computer. Chinese input software uses certain encoding rules to match the characters input on the keyboard with Chinese characters to achieve the function of Chinese character input.

[0003] The current mainstream Chinese input software usually displays matching candidate Chinese characters or phrases through the candidate word window after the user enters the code. However, the number of entries displayed in the candidate word window is limited, and users often need to turn pages multiple times when they need to select lower priority candidate words. When there are a large number of candidate words corresponding to a certain code, this page turning operation may greatly increase the user's input time, resulting in low input efficiency. For example, when entering long sentences or special words, users may have to turn pages continuously to find the required words. This limitation makes the existing Chinese input software have certain deficiencies in improving user input speed and optimizing input experience. Summary of the invention

[0004] The purpose of the present invention is to provide a broadcast television transmission method and a network system to solve the problems existing in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: a broadcast television transmission method, the method comprising:

[0006] S1. Based on the pinyin or encoding information input by the user, dynamically generate and display a candidate word list containing multiple candidate words;

[0007] S2. adjusting the arrangement order of the candidate word list in real time according to the user's input operation;

[0008] S3. When the number of candidate words exceeds a preset threshold, the candidate word pages are automatically divided and scrolled to reduce the page turning operation of the user, including dividing the candidate words into multiple pages according to the maximum number of words displayed per page. The specific formula is: A = B / N;

[0009] Where A represents the number of pages, B represents the number of all candidate words currently generated, and N represents the maximum number of candidate words displayed per page;

[0010] By moving the window position, paged scrolling display is realized, user scrolling instructions are listened to, and candidate words of the new page are dynamically loaded to achieve smooth transition;

[0011] S4. Receive the user's selection instruction, and send the selected candidate word as the final input content to the target application.

[0012] Preferably, S1 includes treating the pinyin or code input by the user as a query and retrieving all candidate words. The specific formula is:

[0013] Q(w)={d|w∈d};

[0014] Where Q(w) represents the set of candidate words that match the pinyin or encoding input by the current user, w represents the pinyin or encoding information input by the user, and d represents the candidate word document;

[0015] Score and sort the candidate words and select the most relevant candidate words. The specific formula is:

[0016] TF-IDF(t,d)=TF(t,d)·IDF(t);

[0017] Among them, TF-IDF(t, d) represents the importance score of candidate word t in document d, TF(t, d) represents the frequency of candidate word t in document d, IDF(t) represents the inverse document frequency of candidate word t, t represents the candidate word, and d represents the candidate word document;

[0018]

[0019] Among them, C represents the total number of documents in the candidate word corpus, n t Represents the number of documents for the current candidate word t, where t represents the candidate word.

[0020] Preferably, S2 includes calculating the probability of the candidate word being selected, and the specific formula is:

[0021] P(t∣U)=P(U∣t)×P(t) / P(U);

[0022] Among them, t represents the candidate word, U represents the user's input or selection behavior, P(t|U) represents the probability that candidate word t is selected under the condition that user operation U occurs, P(U|t) represents the probability that user operation U occurs under the condition that candidate word w has been generated, P(t) represents the initial probability or prior probability of candidate word t, and P(U) represents the overall probability of all user operations.

[0023] Preferably, S4 includes:

[0024] Generate a Huffman tree based on the frequency of candidate words and assign the optimal code to each candidate word. The specific formula is:

[0025] Where D represents the total transmission length of the compressed candidate word data, y represents the total number of candidate words, i represents the index number of the candidate word, and f i represents the frequency of candidate word i, l i Indicates the encoding length of candidate word i;

[0026] The encoded candidate words are sent to the target application through the communication interface. The target application decodes the received candidate words and inserts the candidate words selected by the user into the specified text box.

[0027] A broadcast television transmission network system adopts the broadcast television transmission method, and the system comprises:

[0028] An input module, for receiving pinyin or encoding information input by a user, and dynamically generating a candidate word list containing a plurality of candidate words;

[0029] A sorting module connected to the input module is used to adjust the order of the candidate word list in real time according to the user's input operation;

[0030] A paging display module connected to the sorting module is used to automatically divide and scroll the candidate word pages when the number of candidate words exceeds a preset threshold, so as to reduce the user's page turning operations;

[0031] The data transmission module connected to the paging display module is used to receive the user's selection instruction and send the selected candidate word as the final input content to the target application.

[0032] Preferably, the input module further includes a speech recognition unit for receiving the user's speech input and converting the speech signal into corresponding pinyin or coding information through a built-in speech analysis algorithm, wherein the speech analysis algorithm includes speech feature extraction, acoustic modeling and language modeling steps, and supports speech input of Mandarin and other multiple dialects.

[0033] Preferably, the sorting module includes a user preference learning unit, which establishes personalized sorting rules by analyzing the user's historical input records and candidate word selection frequencies; the user preference learning unit also dynamically updates the priority ranking of the candidate word list.

[0034] Preferably, the paging display module is provided with a touch operation function, which includes sliding switching, long pressing to delete and double-clicking to select operations on the candidate word page; the paging display module supports automatic adjustment of the number of candidate words displayed on a single page according to the screen size and user habits.

[0035] Preferably, the data transmission module adopts an encrypted transmission protocol, including a combined encryption mechanism based on symmetric encryption and asymmetric encryption, to ensure the data security of the candidate words selected by the user during the transmission process; the data transmission module supports efficient data compression and decompression technology.

[0036] Preferably, the candidate word list has a multilingual support function, specifically including a built-in multilingual vocabulary library and a language switching unit, which can automatically load candidate words in the corresponding language according to the user's language preference; the multilingual vocabulary library contains bilingual Chinese and English, minority languages ​​and international common language vocabulary, and also supports the import and update of user-defined vocabulary libraries to meet input requirements in different language environments.

[0037] It can be seen from the above technical solution that the present invention has the following beneficial effects:

[0038] The broadcasting and television transmission method and network system dynamically generates and displays a candidate word list containing multiple candidate words based on pinyin or coding information input by the user, adjusts the arrangement order of the candidate word list in real time according to the user's input operation, and automatically divides and scrolls the candidate word page when the number of candidate words exceeds a preset threshold, thereby reducing the user's page turning operation, receiving the user's selection instruction, and sending the selected candidate word as the final input content to the target application, so that the user can quickly locate the target word, significantly reducing the time required for selecting the candidate word after inputting the code, especially in the scenario of long sentence input or special word input, can effectively avoid frequent page turning operations, so that the user can still complete the word selection with fewer operations when the number of candidate words is large, thereby reducing the tediousness of the input process The overall user experience is improved. The sorting module can dynamically adjust the order of candidate words according to the user's input habits and historical operation data, so that high-frequency words are presented first, which greatly reduces the difficulty of users finding target words, realizes personalized and intelligent input functions, and further meets the personalized needs of different users. The system design of the present invention has strong compatibility and scalability, can be used in combination with a variety of input modes, and supports word library switching in a multi-language environment. It is widely applicable to different scenario requirements of ordinary users, professional users and multi-language users. The encrypted transmission mechanism adopted by the data transmission module can ensure the security and integrity of user privacy during the input data transmission process, effectively prevent the leakage or tampering of input data during the transmission process, and provide users with safe and reliable use protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a flow chart of the method of the present invention;

[0040] Figure 2 It is a schematic diagram of the connection of the system modules of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] like Figure 1-Figure 2 As shown, the present invention provides a technical solution: a broadcast television transmission method, the method comprising:

[0043] S1. Based on the pinyin or encoding information input by the user, dynamically generate and display a candidate word list containing multiple candidate words;

[0044] S2. adjusting the arrangement order of the candidate word list in real time according to the user's input operation;

[0045] S3. When the number of candidate words exceeds a preset threshold, the candidate word pages are automatically divided and scrolled to reduce the page turning operation of the user, including dividing the candidate words into multiple pages according to the maximum number of words displayed per page. The specific formula is: A = B / N;

[0046] Where A represents the number of pages, B represents the number of all candidate words currently generated, and N represents the maximum number of candidate words displayed per page;

[0047] By moving the window position, paged scrolling display is realized, user scrolling instructions are listened to, and candidate words of the new page are dynamically loaded to achieve smooth transition;

[0048] S4. Receive the user's selection instruction, and send the selected candidate word as the final input content to the target application.

[0049] The above method is based on the pinyin or encoding information input by the user, dynamically calculates the list of candidate words, and adopts a real-time adjustment arrangement method to ensure that the order of candidate words is highly matched with the user's input intention. The number of pages is dynamically adjusted by the formula A=B / N, and the candidate words are divided into multiple pages for display, thereby reducing the user's scrolling burden. The paging scrolling adopts a smooth transition method, uses the window position movement technology, monitors the user's scrolling instructions, and dynamically loads and displays the candidate words of the next page or the previous page, avoiding interface freezes or display interruptions, and improving the user experience. Finally, the user quickly determines and inputs the target candidate word into the target application by clicking or other selection operations. By dynamically generating a candidate word list and adjusting the arrangement order in real time, the user input efficiency can be significantly improved, repeated operations can be avoided, and the paging scrolling function can be introduced to effectively reduce the page turning operations caused by too many candidate words, improve the user experience, and adopt a smooth transition paging scrolling method to ensure smooth interface display and avoid freezes caused by untimely information loading. The method is suitable for a variety of input scenarios, such as text input methods, search functions of smart TVs, etc., and has good scalability.

[0050] S1 includes treating the pinyin or code input by the user as a query and retrieving all candidate words. The specific formula is:

[0051] Q(w)={d|w∈d};

[0052] Where Q(w) represents the set of candidate words that match the pinyin or encoding input by the current user, w represents the pinyin or encoding information input by the user, and d represents the candidate word document;

[0053] Score and sort the candidate words and select the most relevant candidate words. The specific formula is:

[0054] TF-IDF(t,d)=TF(t,d)·IDF(t);

[0055] Among them, TF-IDF(t, d) represents the importance score of candidate word t in document d, TF(t, d) represents the frequency of candidate word t in document d, IDF(t) represents the inverse document frequency of candidate word t, t represents the candidate word, and d represents the candidate word document;

[0056]

[0057] Among them, C represents the total number of documents in the candidate word corpus, n t Represents the number of documents for the current candidate word t, where t represents the candidate word.

[0058] In this embodiment, the user's input (pinyin or encoding) is regarded as a query word, and all possible candidate word sets Q (w) are obtained by matching the candidate word documents in the corpus. The candidate words are scored by calculating the TF-IDF value, where TF represents the frequency of occurrence of the candidate word in a certain document, which is used to reflect the local importance of the candidate word in the document; IDF represents the rarity of the candidate word in the entire corpus, which is used to reduce the score of the candidate word with high frequency but less information. Finally, by sorting the candidate word set by TF-IDF value, the candidate word that best meets the user's intention is selected to ensure that the generated candidate word list has high relevance and accuracy. Sorting the candidate words according to relevance can effectively improve the matching accuracy of the candidate words and avoid interference from irrelevant words. The calculation of the IDF value is based on the frequency of occurrence of the candidate words in the corpus, which can dynamically reflect the characteristic changes of the corpus, ensure the real-time and adaptability of the candidate word scoring, and reduce the weight of the candidate words with high frequency but less information to ensure that the top-ranked candidate words have higher discrimination and information value. Only the query input by the user needs to be scored and sorted. The calculation process is efficient and suitable for input scenarios with high real-time requirements.

[0059] S2 includes calculating the probability of the candidate word being selected, and the specific formula is:

[0060] P(t∣U)=P(U∣t)×P(t) / P(U);

[0061] Among them, t represents the candidate word, U represents the user's input or selection behavior, P(t|U) represents the probability that candidate word t is selected under the condition that user operation U occurs, P(U|t) represents the probability that user operation U occurs under the condition that candidate word w has been generated, P(t) represents the initial probability or prior probability of candidate word t, and P(U) represents the overall probability of all user operations.

[0062] In this embodiment, the user's input or selection behavior is quantitatively analyzed by introducing a probability model, and the ranking of candidate words is dynamically adjusted to improve the accuracy and efficiency of user input. The posterior probability P(t|U) of candidate word t under the condition of user input or selection behavior U is calculated using Bayes' theorem. The posterior probability P(t|U) of each candidate word is updated in real time, and the order of the candidate word list is adjusted so that the candidate word most likely to be selected by the user is ranked in the front. This method can continuously optimize the relevance of the candidate word list according to the user's dynamic input or selection behavior. The ranking of candidate words is dynamically adjusted through a probability model, which significantly improves the accuracy and response speed of user input, reduces unnecessary additional operations, and dynamically updates the ranking of candidate words according to the user's operation behavior and historical preferences, making the candidate word list more intelligent and personalized. By combining the conditional probability of user operation and the initial probability of candidate words, it can adapt to the operation habits and input modes of different users, improve the universality of the method, and use the posterior probability to calculate the priority of candidate words to ensure that the final selected candidate words are highly matched with the user's intentions and reduce the error rate.

[0063] S4 includes generating a Huffman tree according to the frequency of occurrence of candidate words and assigning the optimal code to each candidate word. The specific formula is:

[0064] Where D represents the total transmission length of the compressed candidate word data, y represents the total number of candidate words, i represents the index number of the candidate word, and f i represents the frequency of candidate word i, l i Indicates the encoding length of candidate word i;

[0065] The encoded candidate words are sent to the target application through the communication interface. The target application decodes the received candidate words and inserts the candidate words selected by the user into the specified text box.

[0066] According to the frequency of occurrence of candidate words f i , assign shorter encoding length l to candidate words with higher frequency i, while the candidate words with lower frequency are assigned longer encoding lengths, thereby optimizing the encoding efficiency of the candidate words. The encoded candidate words are sent to the target application through the communication interface. On the target application side, the candidate word data is restored using a decoding algorithm, and the candidate word selected by the user is inserted into the specified text box to complete the input operation. Compressing the candidate word data can significantly reduce the total length of the candidate word transmission data and improve the data transmission efficiency. It is particularly suitable for scenarios with limited bandwidth. The encoding length is dynamically adjusted according to the actual frequency of occurrence of the candidate word to ensure the flexibility of the encoding and the optimization of the transmission efficiency. The data compression and decoding processes have low computational complexity and can maintain real-time and smoothness during user input and candidate word selection. This method is suitable for a variety of data transmission scenarios, including the transmission of input method candidate words, text input of smart devices, and the transmission of candidate results of speech recognition, etc., and has good scalability.

[0067] A broadcast television transmission network system adopts the broadcast television transmission method, and the system comprises:

[0068] An input module, for receiving pinyin or encoding information input by a user, and dynamically generating a candidate word list containing a plurality of candidate words;

[0069] A sorting module connected to the input module is used to adjust the order of the candidate word list in real time according to the user's input operation;

[0070] A paging display module connected to the sorting module is used to automatically divide and scroll the candidate word pages when the number of candidate words exceeds a preset threshold, so as to reduce the user's page turning operations;

[0071] The data transmission module connected to the paging display module is used to receive the user's selection instruction and send the selected candidate word as the final input content to the target application.

[0072] The input module receives the user's pinyin or encoding input and generates a candidate word list as the initial output of the system. The sorting module adjusts the order of candidate words in real time based on user operations and dynamic scoring methods to ensure that the candidate words most likely to be selected by the user are always ranked in the front. The paging display module monitors the total number of candidate word lists. When it exceeds the preset threshold, it is automatically divided into multiple pages, and the user's page turning operation is reduced through smooth scrolling or other paging display methods. The data transmission module sends the selected content to the target application through efficient encoding and transmission methods based on the candidate words finally selected by the user, and completes the final processing of the user input. The system is modularly designed, with clear tasks between modules and a unified data structure for interaction, ensuring the optimal efficiency of dynamic generation, sorting, paging display and transmission of candidate words. The synergy between the input module and the sorting module can dynamically adapt to the input mode and corpus characteristics of different users; the combination of the paging display module and the data transmission module ensures the fluency and efficiency of the system when processing a large number of candidate words. From input to the final candidate word selection, each module has clear functions and cooperates with each other, ensuring the smoothness and efficiency of the input process. The sorting module and the paging display module can be dynamically adjusted according to user operations, reducing the user's operating burden and improving real-time response capabilities. Each module adopts a modular design, and the function of any module can be expanded or replaced according to needs. For example, more complex sorting algorithms or compression algorithms can be used to meet the needs of different scenarios. The data transmission module uses Huffman coding to compress candidate word data, reducing the amount of network transmission data and improving data transmission efficiency. It is particularly suitable for network environments with limited bandwidth.

[0073] The input module further includes a speech recognition unit for receiving the user's speech input and converting the speech signal into corresponding pinyin or encoding information through a built-in speech analysis algorithm, wherein the speech analysis algorithm includes speech feature extraction, acoustic modeling and language modeling steps, and supports speech input of Mandarin and other dialects.

[0074] The user inputs the voice signal through the voice recognition unit. The system first extracts the features of the voice and obtains the key parameters as the model input; then the voice signal is mapped into a phoneme sequence through acoustic modeling; finally, accurate pinyin or encoding information is generated through language modeling combined with the context. The system supports input of multiple languages ​​and dialects, and achieves compatibility between different languages ​​by expanding the corpus and training multilingual acoustic models. For example, based on the Mandarin corpus, voice data of dialects such as Cantonese and Wu are introduced to improve the recognition rate of users of different languages. Speech feature extraction, acoustic modeling, and language modeling work together to ensure that the parsing process of voice signals from physical characteristics to language structure is efficient and accurate. This multi-stage process can adapt to a variety of environments and user input conditions through training and optimization. The system is compatible with Mandarin and multiple dialects, meeting the input needs of different user groups and expanding the scope of application of the system. Through speech feature extraction and multi-model collaborative modeling, the system can accurately parse speech input in complex environments and reduce the misrecognition rate. The optimized speech recognition algorithm can complete input parsing under low-latency conditions to ensure the smoothness and response speed of the user input process. Compared with traditional keyboard or handwriting input, voice input is more natural and is particularly suitable for scenarios such as smart TVs or remote controls where keyboard operation is not convenient. After supporting dialect input, the application scope of the system in different language environments can be expanded, such as users with different language habits in the south and north.

[0075] The sorting module includes a user preference learning unit, which establishes personalized sorting rules by analyzing the user's historical input records and the selection frequency of candidate words; the user preference learning unit also dynamically updates the priority sorting of the candidate word list.

[0076] User preference learning process: The user preference learning unit will continuously record the user's historical input behavior, including the candidate words selected and unselected each time the input is made, as well as the frequency and context of the candidate word selection. Based on this data, the system extracts the regular characteristics of user preferences through statistics and modeling, such as: selection preference: which words are selected more frequently by users; context relevance: whether the user's choice has a specific association with the context or input position in different input scenarios; time dimension analysis: whether there is a time-related selection preference, such as the frequency of selecting certain candidate words is higher in a specific time period.

[0077] Establishment of personalized sorting rules: Based on user preference data, the user preference learning unit generates personalized sorting rules, such as: Weight adjustment: According to the selection frequency of candidate words, higher weights are given to words selected with high frequency, so that they are prioritized in sorting; History matching: When the user enters similar pinyin or encoding again, the words that were historically preferred will get a higher sorting priority; Context matching: Combined with the context, higher weights are assigned to candidate words that are more in line with the current input scenario.

[0078] Dynamic priority update: The user preference learning unit will dynamically update the candidate word sorting rules after each user selection operation. For example, when a user selects a candidate word multiple times, its priority will be automatically increased; for candidate words that have not been selected for a long time, their weight will gradually decrease and may eventually be removed from the high-priority candidate list.

[0079] Real-time response: After the user enters pinyin or code, the user preference learning unit will quickly call the personalized sorting rules, generate a sorted candidate word list and provide real-time feedback to the user to ensure the accuracy and real-time nature of the sorting results.

[0080] The system performs personalized optimization based on the user's historical records and selection behaviors, making the sorting results more in line with the user's actual needs and improving the user experience. The user preference learning unit can update the sorting rules in real time according to the user's operations, ensuring that the system can continue to adapt to the user's input habits and preference changes. The sorting module reduces the number of user searches or page turns through personalized rule adjustments, thereby improving input efficiency. It is particularly suitable for scenarios that require fast and accurate input. The user preference learning unit is not only suitable for a single user, but can also provide sorting optimization solutions for group behavior patterns through multi-user analysis, such as supporting personalized configuration in multi-person usage scenarios of smart TVs.

[0081] The paging display module is provided with a touch operation function, which includes sliding switching, long pressing to delete, and double-clicking to select operations on the candidate word page; the paging display module supports automatic adjustment of the number of candidate words displayed on a single page according to the screen size and user habits.

[0082] Implementation of touch operation function: Users can switch left and right candidate word pages by sliding horizontally on the touch screen. The paging display module updates the candidate word display page in real time by monitoring the sliding direction and speed of the touch input, and ensures a smooth transition of the candidate word list during the switching process. When the user long presses a candidate word, the paging display module triggers a delete operation to remove the candidate word from the current list, and dynamically updates the candidate word list and paging structure to ensure the integrity of the number and order of displayed candidate words. If the user double-clicks a candidate word, the paging display module immediately marks the word as selected content and sends it to the target application through the data transmission module to complete the input operation.

[0083] Automatically adjust the number of candidate words displayed on a single page: The paging display module dynamically calculates the number of candidate words that can be displayed on a single page based on the resolution, aspect ratio, and display orientation (horizontal or vertical) of the device screen. For example: reduce the number of candidate words on small-screen devices to ensure font size and readability, and increase the number of displayed words on large-screen devices to reduce page turning operations. The paging display module dynamically adjusts the number of candidate words displayed on a single page by recording the user's operating behavior (such as the number of page turns and word selection speed). For example: if the user is accustomed to turning pages quickly, the system can reduce the number of candidate words displayed on a single page; if the user tends to select within one page, the system will increase the number of candidate words displayed on a single page to meet the demand.

[0084] Touch operations such as sliding to switch, long pressing to delete, and double-clicking to select are in line with the user's natural operating habits. The interaction method is intuitive and simple, which improves the user's operating experience; it supports dynamic adjustment of the number of single-page displays, reduces frequent page turning operations, and optimizes the efficiency of user selection; it automatically adapts to the screen size and resolution to ensure that the system has consistent display effects on different devices (such as mobile phones, tablets, and smart TVs), which improves the universality of the system; it dynamically optimizes display settings based on user operating habits to meet the personalized needs of different users; touch operations respond in real time to ensure that users can quickly select candidate words during the input process and reduce the sense of delay; it supports multiple operating functions (such as deleting, selecting, etc.), providing users with higher operating freedom and flexibility; it is suitable for a variety of touch devices (such as smart phones, touch tablets, TV remote controls with touch functions, etc.), and can maintain efficient and smooth interactive performance in different usage scenarios.

[0085] The data transmission module adopts an encrypted transmission protocol, including a combined encryption mechanism based on symmetric encryption and asymmetric encryption, to ensure the data security of the candidate words selected by the user during the transmission process; the data transmission module supports efficient data compression and decompression technology.

[0086] Implementation of the combined encryption mechanism: During the data transmission process, the system first uses asymmetric encryption (such as the RSA algorithm) to exchange keys. The specific implementation is: the data transmission module generates a symmetric encryption key; the key is encrypted and transmitted using the public key of the target application; the target application uses the private key to decrypt and obtain the symmetric key to establish a secure communication channel. Symmetric encryption: After completing the key exchange, the data transmission module uses a symmetric encryption algorithm (such as the AES algorithm) to encrypt the candidate word data. Symmetric encryption is efficient and has low computational cost, which is suitable for real-time data transmission scenarios and ensures data confidentiality.

[0087] Data compression and decompression: The data transmission module compresses the candidate word data using an efficient compression algorithm (such as Huffman coding or Deflate algorithm) before encryption to reduce the amount of data transmission. On the target application side, after receiving the encrypted compressed data, the data transmission module first decrypts the data and then decompresses the compressed data to ensure the integrity and availability of the candidate word content.

[0088] Secure transmission process: The data transmission module uses secure communication protocols (such as TLS protocol) and encryption mechanisms to encrypt and protect communication data during the data transmission process to prevent middleman attacks or data theft. The combination of encryption and compression ensures data security and optimizes transmission efficiency.

[0089] The combined encryption mechanism combines the advantages of symmetric encryption and asymmetric encryption to ensure the security of data transmission and the reliability of key management; the TLS protocol is used to further enhance the security of the transmission link and prevent data from being stolen or tampered with; data compression technology significantly reduces the transmission volume of candidate word data and optimizes bandwidth utilization, which is particularly suitable for scenarios with limited network environments; the low computational overhead of symmetric encryption ensures the real-time performance of the system and is suitable for the high-efficiency requirements of radio and television transmission networks; the mechanism is applicable to a variety of scenarios, not only to ensure the security of candidate word transmission, but also to be extended to other types of sensitive data transmission; the encryption mechanism prevents the candidate words entered by the user from being illegally accessed or stolen during transmission, effectively protecting user privacy.

[0090] The candidate word list has a multi-language support function, specifically including a built-in multi-language vocabulary library and a language switching unit, which can automatically load candidate words in the corresponding language according to the user's language preference; the multi-language vocabulary library contains bilingual Chinese and English, minority languages ​​and international common language vocabulary, and also supports the import and update of user-defined vocabulary libraries to meet input needs in different language environments.

[0091] The system has preset vocabulary libraries that support Chinese and English, minority languages ​​(such as Tibetan, Uyghur, Mongolian), international languages ​​(such as French, etc.), German, Japanese, and Korean. The vocabulary library contains common words, phrases, proper nouns, and context-related words to ensure the comprehensiveness and accuracy of user input in a multilingual environment. The system allows users to import custom vocabulary libraries through external files (such as CSV or JSON format). Users can update or expand the vocabulary library according to personal needs, such as adding industry terms, proper nouns, or regional vocabulary, to improve input flexibility and applicability. The system automatically identifies the current language through the characters, voice, or historical input habits entered by the user, and loads the corresponding vocabulary library. For example, when the user enters pinyin, the system loads the Chinese vocabulary library; when the user enters English words, the system automatically switches to the English vocabulary library. Users can manually switch languages ​​through interface options, such as selecting Chinese, English, or other minority languages. After the language is switched, the candidate word list will be refreshed to the candidate words of the corresponding language in real time. The system supports the simultaneous display of multilingual candidate words in the candidate word list, which is convenient for users to quickly select target words in a mixed Chinese and English or multilingual environment. When the user switches languages ​​or imports a new vocabulary, the system dynamically loads the vocabulary data of the corresponding language to avoid repeated startup or delay. The system uses the online update function to regularly synchronize the latest language vocabulary, such as updating new words in minority languages ​​or new terms in international languages, to ensure the timeliness of the vocabulary.

[0092] Through the built-in multilingual vocabulary, the system can support user input in multiple language environments, meet the needs of users of different languages ​​at home and abroad, especially support minority languages, expand the application scope of the system, support the import and update of user-defined vocabulary, enable the system to adapt to specific scenarios (such as professional terminology input or dialect input), enhance the personalization and applicability of the system, and combine automatic language detection and manual switching to simplify user operations in multilingual environments and improve input efficiency and experience. The online update and real-time loading functions ensure that the system vocabulary can keep pace with language changes and user needs, and avoid obsolescence or omissions of language vocabulary. It is suitable for mixed Chinese and English input, cross-language communication (such as tourism, foreign trade), and the promotion and protection of minority languages, and has a broad application prospect.

[0093] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A broadcast television transmission method, characterized in that: The method comprises: S1. Based on the pinyin or encoding information input by the user, dynamically generate and display a candidate word list containing multiple candidate words; S2. adjusting the arrangement order of the candidate word list in real time according to the user's input operation; S3. When the number of candidate words exceeds a preset threshold, the candidate word pages are automatically divided and scrolled to reduce the page turning operation of the user, including dividing the candidate words into multiple pages according to the maximum number of words displayed per page. The specific formula is: A = B / N; Where A represents the number of pages, B represents the number of all candidate words currently generated, and N represents the maximum number of candidate words displayed per page; By moving the window position, paged scrolling display is realized, user scrolling instructions are listened to, and candidate words of the new page are dynamically loaded to achieve smooth transition; S4. Receive the user's selection instruction, and send the selected candidate word as the final input content to the target application.

2. A broadcast television transmission method according to claim 1, characterized in that: S1 includes treating the pinyin or code input by the user as a query and retrieving all candidate words. The specific formula is: Q(w)={d|w∈d}; Where Q(w) represents the set of candidate words that match the pinyin or encoding input by the current user, w represents the pinyin or encoding information input by the user, and d represents the candidate word document; Score and sort the candidate words and select the most relevant candidate words. The specific formula is: TF-IDF(t,d)=TF(t,d)·IDF(t); Among them, TF-IDF(t, d) represents the importance score of candidate word t in document d, TF(t, d) represents the frequency of candidate word t in document d, IDF(t) represents the inverse document frequency of candidate word t, t represents the candidate word, and d represents the candidate word document; Among them, C represents the total number of documents in the candidate word corpus, n t Represents the number of documents for the current candidate word t, where t represents the candidate word.

3. A broadcast television transmission method according to claim 1, characterized in that: S2 includes calculating the probability of the candidate word being selected, and the specific formula is: P(t∣U)=P(U∣t)×P(t) / P(U); Among them, t represents the candidate word, U represents the user's input or selection behavior, P(t|U) represents the probability that candidate word t is selected under the condition that user operation U occurs, P(U|t) represents the probability that user operation U occurs under the condition that candidate word w has been generated, P(t) represents the initial probability or prior probability of candidate word t, and P(U) represents the overall probability of all user operations.

4. A broadcast television transmission method according to claim 1, characterized in that: The S4 includes: Generate a Huffman tree based on the frequency of candidate words and assign the optimal code to each candidate word. The specific formula is: Where D represents the total transmission length of the compressed candidate word data, y represents the total number of candidate words, i represents the index number of the candidate word, and f i represents the frequency of candidate word i, l i Indicates the encoding length of candidate word i; The encoded candidate words are sent to the target application through the communication interface. The target application decodes the received candidate words and inserts the candidate words selected by the user into the specified text box.

5. A broadcasting and television transmission network system, using the broadcasting and television transmission method according to any one of claims 1 to 4, characterized in that: The system comprises: An input module, for receiving pinyin or encoding information input by a user, and dynamically generating a candidate word list containing a plurality of candidate words; A sorting module connected to the input module is used to adjust the order of the candidate word list in real time according to the user's input operation; A paging display module connected to the sorting module is used to automatically divide and scroll the candidate word pages when the number of candidate words exceeds a preset threshold, so as to reduce the user's page turning operations; The data transmission module connected to the paging display module is used to receive the user's selection instruction and send the selected candidate word as the final input content to the target application.

6. A broadcasting and television transmission network system according to claim 5, characterized in that: The input module further includes a speech recognition unit for receiving the user's speech input and converting the speech signal into corresponding pinyin or coding information through a built-in speech analysis algorithm, wherein the speech analysis algorithm includes speech feature extraction, acoustic modeling and language modeling steps, and supports speech input of Mandarin and other dialects.

7. A broadcasting and television transmission network system according to claim 5, characterized in that: The sorting module includes a user preference learning unit, which establishes personalized sorting rules by analyzing the user's historical input records and the selection frequency of candidate words; the user preference learning unit also dynamically updates the priority sorting of the candidate word list.

8. A broadcasting and television transmission network system according to claim 5, characterized in that: The paging display module is provided with a touch operation function, which includes sliding switching, long pressing to delete, and double-clicking to select operations on the candidate word page; the paging display module supports automatic adjustment of the number of candidate words displayed on a single page according to the screen size and user habits.

9. A broadcasting and television transmission network system according to claim 5, characterized in that: The data transmission module adopts an encrypted transmission protocol, including a combined encryption mechanism based on symmetric encryption and asymmetric encryption, to ensure the data security of the candidate words selected by the user during the transmission process; the data transmission module supports efficient data compression and decompression technology.

10. A broadcasting and television transmission network system according to claim 5, characterized in that: The candidate word list has a multi-language support function, specifically including a built-in multi-language vocabulary library and a language switching unit, which can automatically load candidate words in the corresponding language according to the user's language preference; the multi-language vocabulary library contains bilingual Chinese and English, minority languages ​​and international common language vocabulary, and also supports the import and update of user-defined vocabulary libraries to meet input requirements in different language environments.

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