Live broadcast control method, device, equipment and storage medium

Abstract

The present disclosure provides a live broadcast control method, device, equipment and storage medium. The present disclosure relates to the field of computer technology, in particular to the fields of data processing, artificial intelligence, deep learning, smart e-commerce, etc., and can be applied to application scenarios such as smart assistants, virtual assistants, and smart e-commerce. The method includes: obtaining user interaction information in the live broadcast room; performing intent recognition on the user interaction information to obtain the user's intention; the user's intention includes the identifier of the first product that the user requires to be explained, and the user's focus on the first product; obtaining the product details of the first product based on the user's intention; generating a live broadcast script for the first product based on the product details and focus; using the live broadcast script of the first product to modify the live broadcast room script, and playing the modified live broadcast room script. The present disclosure can enhance the user's experience in the live broadcast room.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, in particular to data processing, artificial intelligence, deep learning, smart e-commerce and other fields, and can be applied to application scenarios such as smart assistants, virtual assistants, and smart e-commerce. Background Art

[0002] In recent years, with the rapid development of artificial intelligence (AI), the application of digital human technology in live product broadcasting has matured. However, current digital human broadcast rooms rely primarily on pre-set scripts to introduce and explain the products being broadcast. However, the digital human host is unable to respond to unexpected situations during the live broadcast, such as user questions about unavailable products. This results in poor interactivity between the digital human host and the user, impacting the viewing experience. Therefore, how to update the live broadcast script in real time based on user intent within the digital human broadcast room is a challenge that needs to be addressed. Summary of the Invention

[0003] The present disclosure provides a live broadcast control method, apparatus, device, and storage medium.

[0004] According to one aspect of the present disclosure, a live broadcast control method is provided, comprising:

[0005] Obtain user interaction information in the live broadcast room;

[0006] Performing intent recognition on the user interaction information to obtain a user intent; the user intent includes an identifier of the first product that the user requests to be explained, and the user's focus on the first product;

[0007] Obtain product details of the first product based on the user intent;

[0008] Generate a live broadcast script for the first product based on the product details and focus points;

[0009] Use the live broadcast script of the first product to modify the live broadcast room script and play the modified live broadcast room script.

[0010] According to another aspect of the present disclosure, a live broadcast control device is provided, comprising:

[0011] The first acquisition module is used to obtain user interaction information in the live broadcast room;

[0012] an intention recognition module for performing intention recognition on the user interaction information to obtain a user intention; the user intention includes an identifier of the first product that the user requests to be explained, and the user's focus on the first product;

[0013] A second acquisition module is used to acquire product details of the first product based on the user intention;

[0014] A generation module, configured to generate a live broadcast script for the first product based on the product details and focus points;

[0015] The modification module is used to modify the live broadcast room script using the live broadcast script of the first product and play the modified live broadcast room script.

[0016] According to another aspect of the present disclosure, there is provided an electronic device, comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform any method in the embodiments of the present disclosure.

[0020] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute any method according to the embodiments of the present disclosure.

[0021] According to another aspect of the present disclosure, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the computer program implements any one of the methods according to the embodiments of the present disclosure.

[0022] The present invention identifies user intentions based on user interaction information, generates a live broadcast script for the products that the user is interested in based on the user intentions, and then realizes the modification of the live broadcast script, which can enhance the user's sense of participation and experience.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0025] Figure 1 is a flowchart of an implementation of a live broadcast control method 100 according to an embodiment of the present disclosure;

[0026] Figure 2 is a flowchart of a method 200 for adjusting a live broadcast script according to an embodiment of the present disclosure;

[0027] Figure 3 is a structural diagram of a live broadcast control device 300 according to an embodiment of the present disclosure;

[0028] Figure 4 is a structural diagram of a live broadcast control device 400 according to an embodiment of the present disclosure;

[0029] Figure 5 A schematic block diagram of an example electronic device 500 is shown, which may be used to implement embodiments of the present disclosure. DETAILED DESCRIPTION

[0030] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0031] The “and / or” in the embodiments of the present disclosure indicates that there may be three relationships. For example, A and / or B may indicate three situations: A exists alone, A and B exist at the same time, and B exists alone. The term “at least one” herein indicates any combination of at least two of any one or more of a plurality of. For example, at least one of A, B, and C may indicate any one or more elements selected from the set consisting of A, B, and C. The terms “first” and “second” herein refer to and distinguish between multiple similar technical terms, and do not mean to limit the order or to limit the meaning to only two. For example, the first feature and the second feature refer to two categories / two features. The first feature may be one or more, and the second feature may also be one or more.

[0032] In recent years, thanks to rapid advances in artificial intelligence, the application of digital human technology in livestreaming product promotions has matured. However, the functional applications of digital human livestreams still have certain limitations. This is primarily due to the digital human's primary focus on introducing a single product and its inability to flexibly respond to diverse user needs. Specifically, when users inquire about unavailable products during a livestream, the digital human often struggles to adjust its explanation immediately, limiting its ability to provide users with a richer, more dynamic, and more personalized viewing and shopping experience. Therefore, optimizing the livestream script within the digital human livestream based on user intent and needs is a pressing issue.

[0033] In order to solve the above problems, the embodiments of the present disclosure propose a live broadcast control method and device. Among them, the live broadcast control method and device proposed in the embodiments of the present disclosure can be applied to electronic devices such as mobile phones, computers, intelligent voice interaction devices, smart home appliances, car terminals, game consoles, e-book readers, multimedia playback devices, wearable devices, etc. The electronic device obtains user interaction information in the live broadcast room, and performs intent recognition on the user interaction information to obtain the user intention. According to the user intention, the product details of the user-inquired product are obtained, and a live broadcast script for the inquired product is generated based on the product details. The live broadcast room script is modified using the product live broadcast script, and finally the modified live broadcast room script is played. Alternatively, the live broadcast control method and device proposed in the embodiments of the present disclosure can also be applied to a cloud server. After obtaining the user interaction information, the user intention is recognized, and a live broadcast script for the product is generated according to the user intention. The live broadcast script is fed back to the terminal device. The terminal device modifies the live broadcast room script according to the live broadcast script and plays the modified live broadcast room script.

[0034] Figure 1 1 is a flowchart of an implementation of a live broadcast control method 100 according to an embodiment of the present disclosure, including:

[0035] S110, obtaining user interaction information in the live broadcast room;

[0036] S120: performing intent recognition on the user interaction information to obtain a user intent; the user intent includes an identifier of the first product that the user requests explanation of, and the user's focus on the first product;

[0037] S130: Obtain product details of the first product based on the user's intention;

[0038] S140: Generate a live broadcast script for the first product based on the product details and focus points;

[0039] S150. Use the live broadcast script of the first product to modify the live broadcast room script, and play the modified live broadcast room script.

[0040] In the disclosed embodiment, user intent is identified to obtain the user intent consisting of the identifier of a first product and the user's focus on the first product, where the first product includes products not yet available during the live broadcast. The user intent is used to obtain detailed information about the first product. Based on the detailed information and focus on the first product, a live broadcast script explaining the first product is generated, and the live broadcast room is modified using the generated live broadcast script.

[0041] The live broadcast control method proposed in the embodiment of the present disclosure identifies user intentions based on user interaction information, generates a live broadcast script for the products that the user is interested in based on the user intentions, and then realizes the modification of the live broadcast room script. This method can enhance the user's sense of participation and experience.

[0042] In some implementations, performing intent recognition on user interaction information to obtain user intent includes:

[0043] Input each user interaction information into a pre-trained intent recognition model, and the intent recognition model outputs a first intent corresponding to each user interaction information; the first intent includes the product identifier and the product focus;

[0044] Based on the identifiers of the products included in the first intent, grouping the multiple first intents to obtain multiple intent groups, each intent group including multiple first intents, and each intent group corresponding to an identifier of a product;

[0045] For each intent group, when the number of first intents in the intent group is greater than or equal to a preset threshold, the user intent corresponding to the intent group is determined.

[0046] In the embodiment of the present disclosure, the intent recognition model can be obtained through pre-training, wherein the model training method is:

[0047] (1) Data collection: Collect a large amount of user interaction information with user intent. This interaction information can come from actual live broadcast scenarios or be obtained through simulation methods. The collected user interaction information is labeled with intent, that is, the intent category expressed by each interaction information is clearly defined. Intent categories can be defined based on actual application scenarios, such as querying product information, requesting product explanations, etc.

[0048] (2) Data preprocessing: remove irrelevant characters, emoticons, etc. from user interaction information to ensure the purity of text data. Segment the text data so that subsequent models can better understand and process the text data. Convert the segmented text into a numerical form. Usually, word embedding technology can be used, such as the word text to vector method (Word to Vector, Word2Vec), global vector word embedding (Global Vectors for Word Representation, GloVe) or bidirectional encoder representation method (Bidirectional Encoder Representations from Transformers, BERT), etc., to convert the text into a vector form that the model can process.

[0049] (3) Select an appropriate intent recognition model based on task requirements and data characteristics. Common models include Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Transformer models, etc. At the same time, select an appropriate model architecture, including input layer, hidden layer, and output layer.

[0050] (4) Divide the labeled user interaction information data into a training set, a validation set, and a test set, and set the training parameters, including the learning rate, batch size, and number of training rounds. Use the training set data to train the model, and optimize the model parameters through the backpropagation algorithm so that the model can accurately identify the intent in the user interaction information. Use the validation set data to evaluate the model during the training process, and adjust the model parameters or structure based on the evaluation results to improve the model performance.

[0051] (5) Deploy the trained model to the actual application scenario, use the deployed model to identify the intention of user interaction information, and perform corresponding processing or response based on the recognition results.

[0052] In the disclosed embodiment, the intent recognition model identifies and outputs multiple corresponding first intents based on multiple pieces of user interaction information. These first intents include product identifiers, typically product names, brand names, model numbers, and product nicknames, which are used to refer to specific products in the market. Furthermore, the first intent incorporates the user's concerns about the product, which may involve multiple aspects such as product performance characteristics (such as processor speed and screen resolution), functional characteristics (such as waterproof rating and user experience), appearance design (such as color and material), price range, user reviews, and after-sales service.

[0053] In the embodiment of the present disclosure, first intents with the same product identifier will be grouped together to form an intent group. Each intent group clearly points to a specific product and includes multiple focus points on the product.

[0054] For example, N user interaction information is input into the intent recognition model, and after processing by the intent recognition model, N first intentions are obtained. Among them, these N first intentions may cover different products and concerns. Among the N first intentions, they may include: Product A + Focus 1, Product A + Focus 2, Product A + Focus 3, Product B + Focus 1... In order to effectively utilize these first intentions, the N first intentions are grouped according to the product identifier mentioned in each first intention. Specifically, by traversing these N first intentions, the product identifier mentioned in each first intention is identified, and the first intentions with the same product identifier are grouped into the same group. According to this logic, all first intentions that mention Product A (such as "Product A + Focus 1", "Product A + Focus 2", "Product A + Focus 3", etc.) will be grouped together, and the product identifier corresponding to this intent group is "Product A".

[0055] Similarly, the remaining first intents are processed using the same product identification grouping strategy, ultimately resulting in M ​​intent groups. Each intent group revolves around a specific product and contains multiple first intents. These intents, from different perspectives or focus points, collectively describe the user's interest and needs for the product.

[0056] When further processing and analyzing the intent grouping driven by product identification, a preset threshold is introduced as a judgment basis to ensure that the selected intent grouping can effectively reflect the user's actual intention. Specifically, for each intent grouping, the number of first intentions contained therein is counted and compared with the preset threshold. This comparison process determines which intent groups can be regarded as valid and important carriers of user intent. If the number of first intentions in an intent grouping is greater than or equal to the preset threshold, it means that the first intentions in the intent grouping are relatively concentrated and there is a high demand for a specific product. The user intention can be determined based on the corresponding first intention in the intent grouping.

[0057] In addition, the setting of the preset threshold needs to be flexibly adjusted according to the actual situation. On the one hand, a threshold that is too high may cause some valid intent groups that should have been identified to be missed; on the other hand, a threshold that is too low may introduce too much noise and irrelevant information, affecting the accuracy and effectiveness of determining the user's intention. Therefore, the present disclosure calculates the average value of the number of first intentions in each group (that is, the ratio of the number of first intentions to the number of intent groups) and uses this as a preliminary threshold. In order to more accurately reflect the concentration of user intentions, it is necessary to further analyze the distribution of the number of intentions and adjust the preliminary threshold to set a preset threshold that can effectively filter noise data and accurately capture the real needs of users.

[0058] By inputting user interaction information into a pre-trained intent recognition model, the model can parse user intent and group it according to product identifiers. Subsequently, by setting a preset threshold, it can filter out user intent groups that have a sufficient number of first intents for a specific product (i.e., a number greater than the preset threshold). This helps accurately identify user intent for a product, thereby providing feedback to users and improving the user experience.

[0059] In some implementations, determining the user intent corresponding to the intent group includes:

[0060] Determine the identifier of the product corresponding to the intent group as the identifier of the first product that the user requests to be explained, which is included in the user intent;

[0061] Cluster the focus points of the products included in multiple first intentions in the intent group to obtain multiple cluster centers, each cluster center corresponds to a focus point, and the focus points corresponding to the multiple cluster centers are used as the user's focus points on the first product included in the user intent.

[0062] In the embodiment of the present disclosure, the identifier of the product corresponding to the intent group is used as the identifier of the product that needs to be explained in the user's intent, that is, the identifier of the first product. When further exploring the details of the user's intent, it is necessary to conduct an in-depth analysis of the multiple first intentions in each intent group to obtain the categories of focus points in each intent group. These focus points may involve multiple aspects such as the characteristics, functions, and materials of the product. In order to systematically understand and summarize these focus points, the focus points are processed through a clustering algorithm.

[0063] During the clustering process, the algorithm categorizes all first intents within an intent group based on the similarity between their focus points, forming multiple clusters. Points within each cluster have a high degree of similarity, while points between different clusters are relatively independent. After clustering, each cluster is abstracted into a cluster center, which represents the core characteristics of all focus points within the cluster. For example, three users have the following focus points on the same pair of sneakers:

[0064] (1) User 1 asks how heavy the sneakers are;

[0065] (2) User 2 asks how much the sneakers weigh;

[0066] (3) User 3 asks whether these sneakers are breathable.

[0067] For the above three points of interest, the points of interest of user 1 and user 2 can be clustered into one category, with the center point of the cluster being "the weight of the sports shoes." In addition, the points of interest of user 3 can be clustered into one category, with the center point of the cluster being "the breathability of the sports shoes."

[0068] In the embodiment of the present disclosure, the focus points corresponding to the multiple cluster centers can be identified as the user's focus points on the first product in the user's intention. These focus points provide important basis for subsequent personalized recommendations, product introductions, question answers, etc.

[0069] By using this method, the livestreaming room can focus on the specific product that the user is interested in or needs to learn about by identifying the product identifier corresponding to the intent group as the identifier of the first product requested by the user. Furthermore, cluster analysis is performed on the product focus points mentioned in multiple first intents within the intent group to form multiple clear focus cluster centers. This can summarize the user's main interests in the first product and improve the efficiency of understanding user intent.

[0070] In some implementations, obtaining product details of a first product based on user intent includes:

[0071] Based on the identifier of the first product included in the user intention, product details of the first product are searched from a pre-stored product library.

[0072] In the disclosed embodiment, the product library is a large and orderly data set that stores detailed information about all products on sale on the platform, including product names, prices, specifications, etc. This information is organized and categorized to ensure that it can be quickly retrieved and called when needed.

[0073] Based on the identifier of the first product included in the user's intent, if the first product is not available in the current live broadcast, the system will execute a search algorithm within the product library. This algorithm can quickly traverse the entire database to find a product that matches the given first product identifier. Once a match is found, the system will further verify the validity and completeness of the product to extract accurate product details.

[0074] By adopting the above method, by quickly searching and obtaining detailed information of the first product from the pre-saved product library based on the identifier of the first product included in the user's intention, the efficiency of searching for product details is achieved, and the speed and convenience of obtaining information are improved.

[0075] In some implementations, generating a live broadcast script for the first product based on product details and focus includes:

[0076] Extract product description information corresponding to the focus point from product details;

[0077] Determine the type of the first product based on the identifier of the first product; and search for a live broadcast script template corresponding to the type;

[0078] Generate a live broadcast script for the first product based on the product introduction information and the live broadcast script template corresponding to the type.

[0079] In the embodiment of the present disclosure, based on the user's focus on the first product, product introduction information matching the user's focus is extracted by analyzing various contents in the product details.

[0080] Based on the identifier of the first product, the type of the first product is determined through a database or a product information management system. The type of product may cover multiple dimensions, such as clothing (such as tops, pants, cotton-padded clothes, etc.), electronics (such as mobile phones, computers, home appliances, etc.), and food (vegetables, fruits, fresh produce, etc.). After determining the type of the first product, a live broadcast script template that matches the product type can be searched in a database used to store the correspondence between product types and live broadcast script templates.

[0081] A live broadcast script for the first product is generated based on the introduction information of the first product and a live broadcast script template corresponding to the first product type. The live broadcast script template provides a basic product explanation framework. The live broadcast script template can be personalized based on the introduction information of the first product to make it more closely aligned with the actual live broadcast situation.

[0082] For example, during a livestream sales event, some users raised concerns about a cotton and linen shirt, including "fabric material," "design features," and "color options." Based on these three concerns, we can extract the corresponding product description information from the product details:

[0083] (1) Fabric material: Made of high-quality cotton and linen blended fabric, light and breathable, comfortable to wear, suitable for spring and summer.

[0084] (2) Design features: Simple yet fashionable design, exquisitely tailored neckline and cuffs, smooth body, easy to match with various bottoms.

[0085] (3) Color selection: We offer a variety of fresh and elegant colors for you to choose from, including white, light blue, light pink, etc.

[0086] Based on the "cotton and linen shirt" tag, the product category is determined to be "Fashion Apparel - Shirts." The livestream script template library then searches for a template corresponding to this category. This template includes information on fabrics, styles, and matching suggestions. Based on the extracted product information and the found livestream script template, a livestream script for "cotton and linen shirts" is generated.

[0087] By using the above method, the product introduction information corresponding to the focus point is extracted from the product details, and the live broadcast script template is searched according to the product type. Finally, the live broadcast script is generated according to the product introduction information, which improves the efficiency of live broadcast script generation.

[0088] In some embodiments, the live broadcast script includes live broadcast scripts for multiple products;

[0089] Use the live broadcast script of the first product to modify the live broadcast script, including:

[0090] Determine the attention level of the first product;

[0091] Determine the frequency of explaining the first product based on the level of attention paid to the first product;

[0092] According to the frequency of explanation of the first product, add the live broadcast script of the first product to the live broadcast room script.

[0093] In some implementations, determining the attention level of the first product includes:

[0094] Determine the user intent corresponding to the first product;

[0095] Determine an intent group corresponding to the user intent corresponding to the first product;

[0096] The number of first intents included in the intent group is determined, and the attention level of the first product is determined based on the number of first intents.

[0097] In the embodiment of the present disclosure, the live broadcast script of the first product is used to modify the live broadcast room script. First, the attention level of the first product must be determined. With respect to the attention level of the first product, the user intent corresponding to the first product is first determined, and then the intent group corresponding to the user intent is determined. The attention level of the first product is determined based on the number of first intents in the intent group. If the number of first intents for the first product is greater, it means that the market has greater interest and demand for the product, and its attention level is also higher. Conversely, if the number of first intents is small, it may mean that the product has limited appeal in the market.

[0098] After determining the level of attention for the first product, the frequency of its explanation during the live broadcast needs to be planned based on this level of attention. If the attention for the first product is high, then it should become the highlight of the live broadcast, and accordingly, the frequency of explanations should be set relatively high; if the attention is moderate, then it can be interspersed with other products to ensure that the audience can maintain a certain level of attention to the first product while learning about other products; if the attention is low, the frequency of explanations can be set relatively low. After clarifying the frequency of explanations for the first product, the content and time schedule of the live broadcast script for the first product will be planned in the live broadcast script based on this frequency, so that the live broadcast script can be modified.

[0099] Using this method, the frequency of explanations for the first product is determined based on its popularity, ensuring that the livestream content focuses on products of interest to users, increasing their appeal. Furthermore, adding livestream scripts for products of interest to users through detailed introductions and demonstrations helps viewers gain a more comprehensive understanding of the product's characteristics, thereby improving sales conversion rates.

[0100] In some embodiments, further comprising:

[0101] Determine the commodity value of each commodity in the live broadcast room based on the live broadcast data;

[0102] Determine the frequency of live broadcast scripts for each product based on its value;

[0103] Adjust the live broadcast script based on the frequency of explanations.

[0104] In order to accurately grasp the value of each product in the live broadcast room, it is necessary to comprehensively collect and analyze various data during the live broadcast process. These data include the number of viewers, audience stay time, product click-through rate, conversion rate, sales volume, etc.

[0105] Data on the number of viewers and duration of viewer engagement can provide a preliminary assessment of the livestream's popularity and audience interest in the content, indirectly reflecting the product's appeal to viewers. If a product significantly attracts viewers to stay and watch during its presentation, then its potential value within the livestream is relatively high.

[0106] Product click-through rate and conversion rate are direct indicators of product performance in livestreams. CTR reflects viewers' interest and curiosity in a product, while conversion rate is key to converting this interest into actual purchases. By comparing the CTR and conversion rates of different products, we can clearly see which products are most popular with viewers and thus determine their value.

[0107] Sales volume is also a crucial factor in assessing a product's value. High sales volume not only reflects high sales volume but also demonstrates its popularity in the market. By combining sales volume with cost data, we can calculate a product's profit margin and further confirm its commercial value.

[0108] After assessing the value of each item in the livestream, the frequency of each item's livestream script explanation is determined and adjusted based on this value. For items with higher value, the frequency of explanations can be increased. High-value items often have unique selling points, broad market demand, and higher profit margins, so they should be given more exposure during the livestream. For items with moderate value, the frequency of explanations is flexibly adjusted based on their performance in the livestream and market feedback, ensuring that they are neither too long nor too brief, fully showcasing their characteristics and advantages while retaining the audience's attention. For items with lower value or poor market performance, the frequency of explanations is appropriately reduced to avoid wasting livestream time and audience resources. Finally, the livestream script is adjusted based on the frequency of explanations.

[0109] Figure 2 It is a flowchart of the implementation of the live broadcast script adjustment method 200 according to an embodiment of the present disclosure.

[0110] like Figure 2 As shown, the live broadcast script adjustment method mainly includes four stages: live broadcast script and product information transmission, pre-broadcast strategy, on-air strategy and on-air architecture construction.

[0111] S210. Users and merchants transmit live broadcast scripts and information about products for sale.

[0112] S220, pre-broadcast strategy, is used to determine the status of the live broadcast script, including:

[0113] S221, determining whether the live broadcast script is added or modified;

[0114] S222. If the live broadcast room script has not been added or modified, the live broadcast room script is directly used; if the live broadcast room script has been added or modified, the on-air strategy is adopted to automatically adjust the script.

[0115] S230, the on-air strategy, is used to automatically adjust the live broadcast script added or modified by the user, including adjusting the default explanation order and real-time adjustment. Adjusting the default explanation order includes the following steps:

[0116] S231: Entering the cold start phase of the live broadcast, the set live broadcast script is used. For example, the user initially sets the live broadcast script as follows: each of the four products A, B, C, and D is explained once. When the page view (PV) of the live broadcast room is less than the threshold (shown as x in the figure), it means that the live broadcast is still in the data accumulation stage, and the set live broadcast script is used throughout the live broadcast.

[0117] The PV threshold x can be set based on historical data. Understanding the average number of visits to the live broadcast of the product being sold can help set a threshold that is neither conservative nor too aggressive.

[0118] S232. When PV is greater than x, the live broadcast script adjustment period begins, that is, the new product ranking and frequency are determined based on the value of the products. This process is essentially to adjust the frequency of explanation of the live broadcast script of each product. Among them, products with high value may be given a higher frequency of explanation for their live broadcast scripts, that is, more time is arranged to explain the live broadcast script of the product during the entire live broadcast. Continuing with the previous example, through value evaluation, the ratio of the number of explanations of the four products A, B, C, and D is 3:2:1:0, that is, A has the highest value, and the frequency of explanation of A's live broadcast script is the highest during the live broadcast; B and C have a medium value, and the frequency of explanation of B and C's live broadcast scripts is medium during the live broadcast; D has the lowest value, and D's live broadcast script is not explained during the live broadcast.

[0119] Real-time product adjustment includes the following steps:

[0120] S233: The user requests an explanation of a certain product, for example, the user comments: "Let me talk about product D."

[0121] S234: Determine whether the number of people in the current live broadcast room is less than the threshold number (shown as n in the figure);

[0122] S235. If the current number of people in the live broadcast room is less than n, then the live broadcast script for the product requested by the user is inserted in real time. After explaining the requested product, the live broadcast continues according to the adjusted default live broadcast room script. Continuing with the previous example, after explaining A, the live broadcast script for D is inserted in real time. After explaining D, the live broadcast continues according to the adjusted live broadcast room script.

[0123] S236. If the number of people in the live broadcast room is greater than n, the default explanation order is used.

[0124] When the livestream room is small, every user request can have a significant impact on the livestream content. Therefore, if the number of people in the room is below a threshold n, the digital human host can flexibly respond to user requests, inserting explanations of the requested products in real time. When the room is large, if every user request is responded to in real time, the livestream content may become disorganized, affecting the overall rhythm and efficiency of the livestream. Therefore, setting a threshold n serves as a boundary. When the number of people in the room exceeds this threshold, the digital human host can use the default explanation order to ensure the consistency and stability of the livestream content.

[0125] The number threshold n can be adjusted accordingly based on the size of the livestream. For example, in a small livestream, due to the relatively small audience base, each user request may have a significant impact on the livestream content. Therefore, the threshold n can be appropriately increased to better meet user needs. In contrast, in a large livestream, due to the large audience base, responding to frequent user requests may disrupt the livestream rhythm, so the threshold n can be appropriately lowered.

[0126] S240. Adjust the structure of the live broadcast script in progress according to the adjustment strategy of the live broadcast script:

[0127] S241. Based on the example of S232, after adjusting the explanation frequency of the live broadcast script according to the value of the product, the live broadcast script can be adjusted to: ABABAC;

[0128] S242. According to the example of S235, combined with the default live broadcast script adjusted in step S241, after inserting the live broadcast script for D in real time, the live broadcast script can be updated in real time to: ADBABAC;

[0129] S243. After explaining D's live broadcast script, restore the adjusted default live broadcast script: ABABAC.

[0130] By using the above method, the value of each product in the live broadcast room is determined by combining live broadcast data, and the explanation frequency of each product in the live broadcast script is adjusted accordingly. This can ensure that high-value products receive more exposure and explanation time, thereby improving the pertinence and effectiveness of the explanation. At the same time, it can also provide feedback on users' product explanation requests, thereby improving users' experience of watching live broadcasts.

[0131] The present disclosure also provides a live broadcast control device. Figure 3 3 is a structural diagram of a live broadcast control device 300 according to an embodiment of the present disclosure, including:

[0132] The first acquisition module 310 is used to obtain user interaction information in the live broadcast room;

[0133] The intention recognition module 320 is used to perform intention recognition on the user interaction information to obtain the user intention; the user intention includes the identifier of the first product that the user wants to be explained and the user's focus on the first product;

[0134] A second acquisition module 330 is configured to acquire product details of the first product based on the user's intention;

[0135] A generating module 340 is configured to generate a live broadcast script for the first product based on the product details and focus points;

[0136] The modification module 350 is used to modify the live broadcast room script using the live broadcast script of the first product and play the modified live broadcast room script.

[0137] In some embodiments, the intent recognition module 320 is configured to:

[0138] Each user interaction information is input into a pre-trained intent recognition model, and the intent recognition model outputs a first intent corresponding to each user interaction information; the first intent includes the product identifier and the product focus;

[0139] Based on the identifiers of the products included in the first intent, grouping the multiple first intents to obtain multiple intent groups, each intent group including multiple first intents, and each intent group corresponding to an identifier of a product;

[0140] For each intent group, when the number of first intents in the intent group is greater than or equal to a preset threshold, the user intent corresponding to the intent group is determined.

[0141] In some embodiments, the intent recognition module 320 is configured to:

[0142] Determine the identifier of the product corresponding to the intent group as the identifier of the first product that the user requests to be explained, which is included in the user intent;

[0143] Cluster the focus points of the products included in multiple first intentions in the intent group to obtain multiple cluster centers, each cluster center corresponds to a focus point, and the focus points corresponding to the multiple cluster centers are used as the user's focus points on the first product included in the user intent.

[0144] In some embodiments, the second acquisition module 330 is configured to search for product details of the first product from a pre-stored product library based on the identifier of the first product included in the user intention.

[0145] In some embodiments, the generation module 340 is configured to:

[0146] Extract product description information corresponding to the focus point from product details;

[0147] Determine the type of the first product based on the identifier of the first product; and search for a live broadcast script template corresponding to the type;

[0148] Generate a live broadcast script for the first product based on the product introduction information and the live broadcast script template corresponding to the type.

[0149] In some embodiments, the live broadcast script includes live broadcast scripts for multiple products;

[0150] The modification module 350 is used to:

[0151] Determine the attention level of the first product;

[0152] Determine the frequency of explaining the first product based on the level of attention paid to the first product;

[0153] According to the frequency of explanation of the first product, add the live broadcast script of the first product to the live broadcast room script.

[0154] In some embodiments, the modification module 350 is configured to:

[0155] Determine the user intent corresponding to the first product;

[0156] Determine an intent group corresponding to the user intent corresponding to the first product;

[0157] The number of first intents included in the intent group is determined, and the attention level of the first product is determined based on the number of first intents.

[0158] Figure 4 4 is a structural diagram of a live broadcast control device 400 according to an embodiment of the present disclosure. In some implementations, the device further includes:

[0159] A first determining module 460 is configured to determine the commodity value of each commodity in the live broadcast room based on the live broadcast data;

[0160] The second determining module 470 is configured to determine the frequency of explaining the live broadcast script of each product based on the product value of each product;

[0161] The adjustment module 480 is used to adjust the live broadcast script based on the explanation frequency. The specific functions and examples of each module and submodule of the device of the embodiment of the present disclosure can be found in the relevant description of the corresponding steps in the above method embodiment, which will not be repeated here.

[0162] In the technical solution disclosed herein, the acquisition, storage and application of personal information of users involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0163] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0164] Figure 5A schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0165] like Figure 5 As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. Various programs and data required for the operation of the device 500 can also be stored in the RAM 503. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0166] Various components in the device 500 are connected to the I / O interface 505, including an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a magnetic disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0167] The computing unit 501 can be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above, such as the detection method. For example, in some embodiments, the detection method can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the detection method described above can be performed. Alternatively, in other embodiments, the computing unit 501 can be configured to perform the detection method in any other appropriate manner (e.g., by means of firmware).

[0168] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0169] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0170] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0171] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0172] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0173] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0174] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not limited herein.

[0175] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A live broadcast control method, comprising: Obtain user interaction information in the live broadcast room; Inputting each of the user interaction information into a pre-trained intent recognition model, and having the intent recognition model output a first intent corresponding to each of the user interaction information; The first intent includes a product identifier and a focus of the product; based on the product identifiers included in the first intents, multiple first intents are grouped to obtain multiple intent groups, each of the intent groups includes multiple first intents, and each of the intent groups corresponds to a product identifier; For each of the intention groups, if the number of first intentions in the intention group is greater than or equal to a preset threshold, determining the identifier of the product corresponding to the intention group as the identifier of the first product that the user requests to be explained, which is included in the user intention; Clustering the focus points of the products included in the multiple first intentions in the intention group to obtain multiple cluster centers, each of the cluster centers corresponding to a focus point, and using the focus points corresponding to the multiple cluster centers as the user's focus points for the first product included in the user intention; Obtaining product details of the first product based on the user intention; Generate a live broadcast script for the first product based on the product details and the focus points; Use the live broadcast script of the first product to modify the live broadcast room script and play the modified live broadcast room script.

2. The method according to claim 1, wherein The acquiring product details of the first product based on the user intention includes: Based on the identifier of the first product included in the user intention, product details of the first product are searched from a pre-stored product library.

3. The method according to claim 1, wherein Generating a live broadcast script for the first product based on the product details and the focus includes: Extracting product introduction information corresponding to the focus point from the product details according to the focus point; Determining the type of the first product based on the identifier of the first product; and searching for a live broadcast script template corresponding to the type; Based on the product introduction information and the live broadcast script template corresponding to the type, generate a live broadcast script for the first product.

4. The method according to claim 1, wherein The live broadcast script includes live broadcast scripts for multiple products; The method of modifying the live broadcast script using the live broadcast script of the first product includes: Determining the attention level of the first product; determining a frequency of explaining the first product based on the level of attention paid to the first product; According to the frequency of explanation of the first product, a live broadcast script of the first product is added to the live broadcast room script.

5. The method according to claim 4, wherein The determining the attention level of the first product includes: Determining a user intent corresponding to the first product; Determine an intent group corresponding to the user intent corresponding to the first product; Determine the number of first intentions included in the intention group, and determine the attention level of the first product according to the number of the first intentions.

6. The method according to claim 4, further comprising: Determine the commodity value of each commodity in the live broadcast room based on the live broadcast data; Determining the frequency of explaining the live broadcast script for each of the products based on the product value; Adjust the live broadcast script based on the explanation frequency.

7. A live broadcast control device, comprising: The first acquisition module is used to obtain user interaction information in the live broadcast room; an intention recognition module, configured to input each of the user interaction information into a pre-trained intention recognition model, and have the intention recognition model output a first intention corresponding to each of the user interaction information; The first intent includes a product identifier and a focus of the product; based on the product identifiers included in the first intents, multiple first intents are grouped to obtain multiple intent groups, each of the intent groups includes multiple first intents, and each of the intent groups corresponds to a product identifier; For each of the intention groups, if the number of first intentions in the intention group is greater than or equal to a preset threshold, determining the identifier of the product corresponding to the intention group as the identifier of the first product that the user requests to be explained, which is included in the user intention; Clustering the focus points of the products included in the multiple first intentions in the intention group to obtain multiple cluster centers, each of the cluster centers corresponding to a focus point, and using the focus points corresponding to the multiple cluster centers as the user's focus points for the first product included in the user intention; A second acquisition module, configured to acquire product details of the first product based on the user intention; A generation module, configured to generate a live broadcast script for the first product based on the product details and the focus points; The modification module is used to modify the live broadcast room script using the live broadcast script of the first product and play the modified live broadcast room script.

8. The device according to claim 7, wherein The second acquisition module is configured to search for product details of the first product from a pre-stored product library based on the identifier of the first product included in the user intention.

9. The device according to claim 7, wherein The generation module is used to: Extracting product introduction information corresponding to the focus point from the product details according to the focus point; Determining the type of the first product based on the identifier of the first product; and searching for a live broadcast script template corresponding to the type; Based on the product introduction information and the live broadcast script template corresponding to the type, generate a live broadcast script for the first product.

10. The device according to claim 7, wherein The live broadcast script includes live broadcast scripts for multiple products; The modification module is used to: Determining the attention level of the first product; determining a frequency of explaining the first product based on the level of attention paid to the first product; According to the frequency of explanation of the first product, a live broadcast script of the first product is added to the live broadcast room script.

11. The device according to claim 10, wherein The modification module is used to: Determining a user intent corresponding to the first product; Determine an intent group corresponding to the user intent corresponding to the first product; Determine the number of first intentions included in the intention group, and determine the attention level of the first product according to the number of the first intentions.

12. The apparatus according to claim 10, further comprising: A first determining module is used to determine the commodity value of each commodity in the live broadcast room according to the live broadcast data; A second determining module is configured to determine the frequency of explaining the live broadcast script of each of the commodities based on the commodity value of each of the commodities; An adjustment module is used to adjust the live broadcast script based on the explanation frequency.

13. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

14. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

15. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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