Emoji package generation method and related equipment

Abstract

The embodiment of the invention provides an expression package generation method and related equipment. The emoticon generation method comprises the steps that in response to uploading of a target picture, use state information and user historical data are acquired, and the use state information comprises a current use scene, a current track and a current emotion; the historical data of the user comprises the use frequency and use scene of each emoji package by the user and emoji package data generated by the user; converting the target picture by using state information and user historical data to generate an undetermined expression package; obtaining user content adjustment information; and according to the user content adjustment information, adjusting the to-be-determined emoji package to obtain a target emoji package. According to the technical scheme provided by the embodiment of the invention, the finally generated expression package is more personalized, efficient adaptability can be kept in various use scenes, and the user experience is improved.

Description

Technical Field

[0001] The present application relates to the field of computer and communication technology, and in particular to an emoticon package generation method and related equipment. Background Art

[0002] The traditional emoticon package generation method mainly relies on user operation. Since the level of emoticon package production by each user is uneven, the quality of the emoticon packages finally obtained is also uneven, which is difficult to meet the needs of users. Summary of the Invention

[0003] The embodiments of the present application provide an emoticon package generation method and related equipment, which can overcome the problems of traditional emoticon package generation methods in meeting user needs, at least to a certain extent.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by practice of the present application.

[0005] According to one aspect of an embodiment of the present application, a method for generating an emoticon package is provided, comprising: in response to uploading a target image, obtaining usage status information and user history data, the usage status information including a current usage scenario, a current trajectory, and a current emotion; the user history data including the user's usage frequency of each emoticon package, the usage scenario, and the emoticon package data generated by the user; converting the target image using the usage status information and the user history data to generate a pending emoticon package; obtaining user content adjustment information; and adjusting the pending emoticon package according to the user content adjustment information to obtain a target emoticon package.

[0006] According to one aspect of an embodiment of the present application, an emoticon package generation device is provided, which includes: a target image upload module for obtaining usage status information and user history data in response to the uploading of a target image, the usage status information including the current usage scenario, the current trajectory and the current emotion; the user history data including the user's usage frequency of each emoticon package, the usage scenario and the emoticon package data generated by the user; a target image conversion module for converting the target image through the usage status information and the user history data to generate a pending emoticon package; a content adjustment information module for obtaining user content adjustment information; and a pending emoticon package adjustment module for adjusting the pending emoticon package according to the user content adjustment information to obtain a target emoticon package.

[0007] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the emoticon package generation method as described in the above embodiment is implemented.

[0008] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the emoticon package generation method as described in the above embodiment.

[0009] According to one aspect of an embodiment of the present application, a computer program product is provided, comprising one or more computer programs, which, when executed by one or more processors, implement the steps of the emoticon package generation method as described in the above embodiment.

[0010] In the technical solutions provided in some embodiments of this application, by acquiring and analyzing usage status information and user history data, it is possible to generate a target emoticon package that meets the user's current needs and preferences. Through further adjustments, the user can obtain a personalized and precise target emoticon package. Ultimately, the user-generated emoticon package is not only more personalized but also maintains efficient adaptability in various usage scenarios, improving the user experience.

[0011] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings are incorporated into and constitute a part of the specification, illustrating embodiments consistent with the present application and, together with the specification, explaining the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0013] Figure 1 A schematic diagram shows an exemplary system architecture to which the technical solutions of the embodiments of the present application can be applied.

[0014] Figure 2 A flow chart of an emoticon package generation method provided in an embodiment of the present application is shown.

[0015] Figure 3 Shown according to Figure 2 A specific implementation flowchart of step S200 in the emoticon package generation method shown in the corresponding embodiment.

[0016] Figure 4 Shown according to Figure 2 Another specific implementation flowchart of step S200 in the emoticon package generation method shown in the corresponding embodiment.

[0017] Figure 5 Shown according to Figure 2 A specific implementation flowchart of step S400 in the emoticon package generation method shown in the corresponding embodiment.

[0018] Figure 6 A flow chart of another emoticon package generation method provided in an embodiment of the present application is shown.

[0019] Figure 7 A structural diagram of an emoticon package generation device provided in an embodiment of the present application is shown.

[0020] Figure 8 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0021] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art.

[0022] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner.In the following description, many specific details are provided so as to provide a full understanding of the embodiments of the present application. However, it will be appreciated by those skilled in the art that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps etc. can be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0023] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0024] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0025] Figure 1 A schematic diagram shows an exemplary system architecture to which the technical solutions of the embodiments of the present application can be applied.

[0026] like Figure 1 As shown, the system architecture may include terminal devices (such as Figure 1 101, tablet computer 102, and portable computer 103, which may also be a desktop computer, etc.), network 104, and server 105. Network 104 is a medium for providing a communication link between the terminal device and server 105. Network 104 can include various connection types, such as wired communication links, wireless communication links, etc.

[0027] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as needed. For example, the server 105 may be a server cluster consisting of multiple servers.

[0028] The user can use the terminal device to interact with the server 105 through the network 104 to receive or send messages, etc. The server 105 can be a server that provides various services. For example, the user uses the terminal device 103 (or the terminal device 101 or 102) to upload a target image to the server 105. In response to the upload of the target image, the server 105 can obtain usage status information and user history data, wherein the usage status information includes the current usage scenario, current trajectory, and current emotion; the user history data includes the user's usage frequency of each emoticon package, the usage scenario, and the emoticon package data generated by the user; the target image is converted by using the usage status information and user history data to generate a pending emoticon package; user content adjustment information is obtained; and the pending emoticon package is adjusted according to the user content adjustment information to obtain the target emoticon package.

[0029] It should be noted that the emoticon package generation method provided in the embodiment of the present application is generally executed by the server 105, and accordingly, the emoticon package generation device is generally set in the server 105. However, in other embodiments of the present application, the terminal device may also have similar functions as the server, thereby executing the emoticon package generation solution provided in the embodiment of the present application.

[0030] The following is a detailed description of the implementation details of the technical solution of the embodiment of the present application:

[0031] Figure 2 A flowchart of a method for generating an emoticon package according to an embodiment of the present application is shown. The method for generating an emoticon package can be executed by a server, which can be Figure 1 Refer to the server shown in . Figure 2 As shown, the expression package generation method at least includes:

[0032] S100, in response to uploading the target image, obtaining usage status information and user history data, wherein the usage status information includes the current usage scenario, current trajectory, and current emotion; the user history data includes the user's usage frequency of each emoticon package, the usage scenario, and the emoticon package data generated by the user.

[0033] S200, converting the target image by using the state information and user history data to generate a pending emoticon package.

[0034] S300: Obtain user content adjustment information.

[0035] S400: Adjust the pending emoticon package according to the user content adjustment information to obtain a target emoticon package.

[0036] In this embodiment, by acquiring and analyzing usage status information and user history data, a target emoticon package tailored to the user's current needs and preferences can be generated. Through further adjustments, the user can obtain a personalized and precise target emoticon package. Ultimately, the user-generated emoticon package is not only more personalized but also highly adaptable to various usage scenarios, enhancing the user experience.

[0037] In S100, the user uploads a target image as the basis for generating an emoticon package. The system then constructs the user's immediate needs by identifying the current usage scenario (e.g., chat application, social media), current trajectory (the user's recent interactions or activities), and current emotion (e.g., determining the user's emotional state through voice, text, or facial recognition). Simultaneously, by analyzing the user's past usage history, data such as the emoticons the user has used, their frequency of use, and usage scenarios are obtained to better understand the user's preferred emoticon types and frequently used scenarios.

[0038] In S200, intelligent processing is performed based on the user's usage status and historical data, combined with the target image. For example, the user's emotional state (e.g., happy, sad) can be analyzed and appropriate expressions or effects (e.g., smiling, crying, etc.) can be selected based on this emotion. Based on this, a preliminary expression package, called the pending expression package, is generated for further adjustment by the user.

[0039] Specifically, in some embodiments, the specific implementation of step S200 can be found in Figure 3 . Figure 3 is based on Figure 2 The detailed description of step S200 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, step S200 may include the following steps:

[0040] S210 , filtering out emoticon package templates from the emoticon package data generated by the user according to the usage status information.

[0041] S220: Convert the target image into a pending emoticon package according to the emoticon package template.

[0042] In this embodiment, by analyzing user historical data and usage status information, emoticon package generation can better meet user needs, improving user satisfaction and engagement. Specifically, by screening suitable emoticon package templates and converting target images into pre-selected emoticon packages, the tedious process of designing from scratch is avoided, speeding up emoticon package generation. Emoticon packages generated based on user historical data and status information are more closely aligned with users' actual needs, thereby increasing their relevance and frequency of use.

[0043] This embodiment can flexibly adjust the generation method of the emoticon package according to the user's specific status and historical data, meet the needs of different situations, and improve the adaptability of the emoticon package.

[0044] In S210 , the user's current needs and scenarios are analyzed using usage status information. For example, usage status information may include data such as the user's current emotional state, daily activities, time, and location. Based on this information, suitable emoticon templates are selected from the user's previously generated emoticon data. These templates are frequently used in the user's history or best match the user's current status. For example, if the user is celebrating their birthday, an emoticon template related to the celebration can be selected.

[0045] Specifically, in some embodiments, the specific implementation of step S210 can refer to the following embodiments. Figure 3 The detailed description of step S210 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, step S210 may include the following steps:

[0046] A style type parameter is determined according to the current usage scenario, the current trajectory, and the usage scenario of each emoticon package by the user.

[0047] An emotion type parameter is determined according to the current emotion and the frequency of use of each emoticon package by the user.

[0048] According to the style type parameter and the emotion type parameter, an emoticon package template is screened out from the emoticon package data generated by the user.

[0049] In this embodiment, by analyzing the current scene, trajectory, emotion, and other information, the most suitable emoticon template is intelligently determined, thereby improving the accuracy and efficiency of emoticon generation and saving user operation time. Combining the user's usage scenario, emotions, and behavioral history, emoticon templates that meet user needs can be more accurately selected, avoiding the generation of a large number of irrelevant templates. Based on user preferences, emotions, frequency, and other information, the generated emoticons are more personalized, matching the user's usage habits and emotional expression needs, and improving user satisfaction.

[0050] Specifically, we first capture the user's current usage scenario (such as chatting, social media sharing, etc.) and the user's current trajectory (such as geographic location, activity status, etc.) to infer the emoticon style that the user may need (such as formal, humorous, warm, etc.), and convert it into style type parameters as the basis for screening templates.

[0051] Next, the system analyzes the user's current emotional state (e.g., happy, angry, sad, etc.). It also analyzes the user's past emojis to understand how often they use different emojis (e.g., whether they use happy emojis more frequently). Based on this data, it generates emotion type parameters to further help select emoji templates that meet the current emotional needs.

[0052] Finally, by combining style and emotion parameters, taking into account the current usage scenario, emotional state, and historical user preferences, the most appropriate emoji template is selected from the user's generated emoji data. This allows users to quickly obtain emoji templates that meet their needs, reducing screening time and improving response speed and accuracy.

[0053] At S220 , the target image is converted based on the selected emoticon template. For example, if the target image is a selfie, it can be adjusted and modified based on the emoticon template, adding elements such as cartoon images, text, and emoticons, ultimately generating a pending emoticon package. This process essentially combines the target image with the template to form a personalized emoticon package that reflects the user's personality and current needs.

[0054] Specifically, in some embodiments, the specific implementation of step S220 can refer to the following embodiments. Figure 3 The detailed description of step S220 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, step S220 may include the following steps:

[0055] The target image is converted according to the emoticon package template to generate a first preliminary emoticon package.

[0056] A user preference parameter is obtained according to the frequency of use of each emoticon package by the user.

[0057] The first preliminary emoticon package is adjusted according to the user preference parameters to obtain a pending emoticon package.

[0058] In this embodiment, by adjusting the emoticon package template based on the user's preferences and further optimizing and adjusting the preliminary emoticon package after it is generated, the final pending emoticon package is ensured to better align with the user's emotions and usage habits. This improves the accuracy of the generated emoticon package, more precisely meets the user's needs, and enhances the targeted nature of the generated content, ultimately increasing user satisfaction and providing a higher user experience. At the same time, by incorporating the user's usage frequency and preferences, the emoticon package generation process becomes more personalized. The user's preference history provides a more precise basis for adjusting the generated emoticon package, making the generated emoticon package more adaptable.

[0059] Specifically, the target image is first converted according to the emoticon template selected by the user. The target image can be a user-provided picture, a selfie, or other image. Through the role of the template, the target image is converted into a preliminary emoticon package.

[0060] Next, we analyze the frequency of past emoji usage by the user to identify their preferences in different contexts. For example, a user might more frequently use emojis that depict happy, humorous, or angry emotions. Based on this information, we generate a user preference parameter, reflecting the user's inclination towards different emotions, styles, or themes.

[0061] After obtaining user preference parameters, the initially generated emoji package is adjusted. For example, if a user frequently uses humorous emojis, the initial package can be adjusted to reflect this preference by adding more exaggerated expressions or elements, or by adjusting details like color and style to better suit the user's aesthetic tastes and needs. This adjustment ultimately results in a finalized emoji package that meets the user's preferences.

[0062] Specifically, in other embodiments, the specific implementation of step S200 can be found in Figure 4 . Figure 4 is based on Figure 2 The detailed description of step S200 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, step S200 may include the following steps:

[0063] S250: Convert the target image according to the emoticon package data generated by the user to obtain a second preliminary emoticon package.

[0064] S260: Adjust parameters of the second preliminary emoticon package according to the usage status information and the user history data to obtain the pending emoticon package.

[0065] In this embodiment, by analyzing usage status information (such as the user's current mood, activity, and scene) and historical data (such as the user's past emoticon usage records) in real time, the content of the preliminary emoticon package is dynamically adjusted to better suit the current user's needs and context. This allows for a more accurate understanding of the user's preferences and context, resulting in an emoticon package that is more closely aligned with the user's individual needs, enhancing the personalization of the generated results. Furthermore, by adjusting the parameters of the preliminary emoticon package, manual intervention can be reduced, the speed of emoticon package generation can be increased, and the relevance and quality of the generated content can be guaranteed.

[0066] In S250, a preliminary emoticon package is generated by templating the target image (such as a selfie or other image). Specifically, the user's previously generated emoticon package data can be referenced and used as a reference to ensure that the style and content of the preliminary emoticon package are consistent with the user's past preferences. For example, if the user has previously generated many humorous emoticons, they may be inclined to generate a fun and exaggerated preliminary emoticon package.

[0067] In S260, the initial emoji package is optimized and adjusted based on the current usage status information and the user's historical data. Usage status information may include the user's current mood, activity (such as sending messages, participating in social activities, etc.), and environmental factors. Historical data includes the type, frequency, and emotional preferences of emoji packages previously generated and used by the user. After combining this information, the parameters of the preliminary emoji package are adjusted, such as fine-tuning the color, expression, background, etc., so that the final pending emoji package better meets the user's current needs and emotional state.

[0068] Specifically, in other embodiments, the specific implementation of step S260 can refer to the following embodiments. Figure 4 The detailed description of step S260 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, step S260 may include the following steps:

[0069] A style type parameter is determined according to the current usage scenario, the current trajectory, and the usage scenario of each emoticon package by the user.

[0070] An emotion type parameter is determined according to the current emotion and the frequency of use of each emoticon package by the user.

[0071] The parameters of the second preliminary emoticon package are adjusted according to the style type parameter and the emotion type parameter to obtain the pending emoticon package.

[0072] In this embodiment, by deeply mining the user's historical data and current status information, fully understanding and applying the user's historical preferences, emotional state, usage scenarios and other information, it is possible to accurately capture the user's emotions and scenario needs when generating emoticon packages, thereby achieving more personalized and contextualized emoticon package generation. The generated emoticon packages are more in line with the user's actual needs, thereby improving the user's usage experience, and the user will feel more personalized care.

[0073] At the same time, by using style type parameters and emotion type parameters for precise adjustment, the generated emoticon package can better reflect the user's emotional needs, improve the relevance and adaptability of the emoticon package, and avoid the output of stereotyped emoticon packages.

[0074] Specifically, the style type parameters can be determined by analyzing the current usage scenario (for example, the user is chatting, sending emails, or interacting on social media, etc.), the user's current trajectory (such as geographic location, activity type, etc.), and the user's previous emoticon usage preferences in different scenarios (for example, using formal emoticons in work situations, using humorous emoticons in social situations, etc.).

[0075] For example, if a user is currently chatting with a friend and has historically preferred to use light-hearted and humorous emoticons, an emoticon that matches the humorous style is generated for the user.

[0076] For the emotion type parameter, the emotion type parameter can be determined by analyzing the user's current emotional state (for example, the user may be in an emotional state such as happy, sad, or angry) and the frequency with which the user used emoticons in different emotional states in the past (for example, the user may frequently use certain emoticons when happy).

[0077] For example, if the user is feeling excited, an emoticon with a joyful or enthusiastic emotion is automatically generated for the user.

[0078] Combining the style and emotion parameters obtained in the previous two steps, adjust the parameters of the initially generated emoji package to ensure that its style and emotion match. Adjustments can include color, expression, background, text, and emoji form, so that the generated emoji package can truly and accurately convey the user's emotions and fit the current context.

[0079] For example, if the user is currently in an excited mood and interacting with friends, the emoticon may appear in lively and bright colors, with happy and exaggerated expressions, and the background may also be related to the social occasion.

[0080] In S300, after the pending emoticon package is generated, the user may provide adjustment information. These adjustments may include modifying the details, text, effects, colors, etc. of the emoticon package to make the emoticon package more in line with the user's personalized needs.

[0081] For example, a user may want to modify the tone of an emoji, or add specific text or stickers to an image.

[0082] In S400 , the information is adjusted based on the content provided by the user, and the pending emoticon package is further processed and optimized, including image processing, text editing, color tone modification, etc., until a target emoticon package that meets the user's requirements is finally generated.

[0083] The final generated target emoticon package will be personalized according to user needs to meet usage requirements in different scenarios.

[0084] Specifically, in some embodiments, the specific implementation of step S400 can refer to the following embodiments. Figure 2 The detailed description of step S400 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, the content adjustment information includes a content adjustment instruction, and step S400 may include the following steps:

[0085] Determine content adjustment parameters according to the content adjustment instruction.

[0086] The pending emoticon package is adjusted according to the content adjustment parameters to obtain a target emoticon package.

[0087] In this embodiment, through the precise setting of content adjustment instructions and content adjustment parameters, the generated target emoticon package can better meet the user's personalized needs, making the final emoticon package more personalized, contextualized, and emotionally accurate. The introduction of content adjustment information ensures that the emoticon package not only meets the user's needs in terms of style and mood, but can also be optimized based on real-time user feedback and historical data to better adapt to the user's usage scenarios and emotional state.

[0088] At the same time, through clear content adjustment instructions and adjustment parameters, the content of the emoticon package can be flexibly adjusted according to different needs, which not only improves the flexibility of emoticon package generation, but also improves accuracy and reduces effect deviations caused by improper adjustments.

[0089] Specifically, content adjustment information is first received. This content adjustment information includes specific adjustment instructions given by the user when using the emoticon package (for example, requesting the emoticon package to have brighter colors, more exaggerated expressions, or to be more in line with a certain emotion). Based on these content adjustment instructions, the specific parameters that need to be adjusted are determined through preset rules or algorithms. For example, if the user wants the emoticon package to have a more humorous expression, the shape of the emoticon package's eyes, mouth, and other parts can be adjusted according to the instructions, or some dynamic effects such as blinking or smiling mouth can be added.

[0090] Then, based on the determined content, the parameters are adjusted to make specific adjustments to the emoticon package. These adjustments may include modifications to the emoticon package's color, expression details, background elements, fonts, dynamic effects, and other aspects.

[0091] For example, if the user wants the emotion expressed by the pending emoticon package to be clearer, the facial expression of the emoticon package can be adjusted (such as changing the expression from neutral to happy or angry), or text content, labels, animation effects, etc. that are suitable for the situation can be added to the emoticon package to make it meet the user's needs.

[0092] Through the above adjustments, the final target emoticon package can better meet the user's emotional needs, usage scenarios and personalized requirements.

[0093] Specifically, in some embodiments, the specific implementation of step S400 can be found in Figure 5 . Figure 5 is based on Figure 2 The detailed description of step S400 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, the content adjustment information includes audio information, and step S400 may include the following steps:

[0094] S410: parse the audio information and determine audio parameters.

[0095] S420: Determine content adjustment parameters according to the audio parameters.

[0096] S430: Adjust the pending emoticon package according to the content adjustment parameters to obtain a target emoticon package.

[0097] In this embodiment, by analyzing audio information and adjusting the emoticon package in combination with audio parameters, the expression of the emoticon package is not limited to static visual effects, but can also reflect the emotion and tone of the audio. This fusion technology makes the performance of the emoticon package more suitable for actual usage scenarios and improves the emotional expression effect of the emoticon package. At the same time, by analyzing the audio information, the facial expressions, dynamic effects, etc. of the emoticon package can be adjusted according to the emotional changes in the audio, so that the emoticon package is highly consistent with the audio content sent by the user. For example, when the audio information contains emotions such as happiness, anger, or sadness, the emoticon package can automatically adjust to expressions that match these emotions, thereby more accurately conveying the user's emotions.

[0098] In addition to visual adjustments, the introduction of audio information allows emojis to express emotions in a more multi-dimensional way, breaking through the limitations of traditional static emojis. This multimodal expression method can provide a richer and more personalized user experience.

[0099] At S410 , audio information is received and analyzed, including features such as the audio's voice content, intonation, rhythm, volume, and speaking speed. By utilizing natural language processing (NLP), speech recognition, and sentiment analysis technologies, key information from the audio can be extracted, and audio parameters can be derived based on this information. For example, if the audio contains a pleasant tone, the system may identify features such as a high pitch and a fast rhythm.

[0100] Specifically, in some embodiments, the specific implementation of step S410 can refer to the following embodiments. Figure 5 The detailed description of step S410 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, the audio parameters include audio emotion, audio style, text emotion, and text style. Step S410 may include the following steps:

[0101] The audio information is analyzed to obtain audio emotion and audio style.

[0102] It is determined whether the audio information includes voice information.

[0103] If voice information is included, the voice information is converted into voice text.

[0104] Parse the speech text to obtain text emotion and text style.

[0105] In this embodiment, audio emotion and audio style provide more detailed guidance for emoticon generation, enabling the generated emoticons to accurately express the emotions expressed in speech. Text emotion and text style further enhance the adaptability of emoticons in scenarios where text and speech are combined. Emotional and style analysis of audio and text helps generate emoticons that better align with the user's tone and emotions, improving their expressiveness and applicability in social interactions.

[0106] Specifically, audio information is first received, and audio analysis techniques (such as sentiment analysis and speech recognition) are used to extract audio emotions (such as happiness, anger, sadness, etc.) and audio styles (such as formal, friendly, and passionate, etc.). When parsing the audio information, it is also possible to determine whether the audio contains speech content. If there is no speech in the audio (for example, only background music or noise), relevant parameters only need to be extracted based on other audio features (such as rhythm, volume, etc.). If the audio contains speech, the next step of speech conversion processing is continued.

[0107] If the audio contains spoken content, the audio needs to be converted to text. This conversion is typically accomplished through speech recognition technology. Converting speech to text facilitates further analysis of the text's sentiment and style, ensuring that the language information in the audio can be further processed and analyzed.

[0108] After conversion to text, sentiment analysis and style analysis are performed on the speech text. Specifically, natural language processing (NLP) techniques can be used to analyze the sentiment (e.g., positive, negative, etc.) and style (e.g., humorous, formal, informal, etc.) of the text content. This not only captures the emotional information in the audio but also provides a richer emotional dimension to the text content.

[0109] For example, if the content of the voice text is sarcastic or humorous, the system will analyze this as the style of the text and, combined with the audio emotion, generate a suitable emoticon package.

[0110] In step S420, content adjustment parameters are determined based on the extracted audio parameters. For example, if the audio parameters indicate that the speech content has a pleasant emotion (such as high frequency and fast speaking speed), the facial expression of the emoticon package is adjusted to a smile or a happy expression, and the dynamic effect may be displayed as a jump or fast animation.

[0111] These audio parameters are converted into specific content adjustment instructions (such as changes in expression, color, dynamic effects, etc.) to ensure that the emotions of the emoticons are consistent with those of the audio.

[0112] Specifically, in some embodiments, the specific implementation of step S420 can refer to the following embodiments. Figure 5The detailed description of step S420 in the emoticon package generation method shown in the corresponding embodiment, in the emoticon package generation method, step S420 may include the following steps:

[0113] A first adjustment parameter is obtained according to the audio emotion and the audio style.

[0114] A second adjustment parameter is obtained according to the text sentiment and the text style.

[0115] A content adjustment parameter is determined according to the first adjustment parameter, the second adjustment parameter, and the speech text.

[0116] In this embodiment, emoticon packages are no longer static, but are dynamically adjusted based on the real-time emotional and stylistic changes in the audio and text. This means that each generated emoticon package is tailored to the specific communication context and can be highly matched. This embodiment ensures the multi-dimensional expression of emoticons in terms of visuals, emotions, and tone through dual analysis of audio and text emotions and styles. Personalized emoticon packages can better match the user's emotional expressions, thereby enhancing the emotional connection and sense of authenticity when interacting with the machine.

[0117] Specifically, the audio data (such as emotion, tone, speaking speed, etc.) is analyzed to extract the emotional features of the audio (such as happiness, excitement, sadness, etc.) and the audio style features (such as formality, friendliness, playfulness, etc.). Based on the above analysis results, the first adjustment parameters are generated. These parameters will be used in the subsequent generation of emoticons to adjust the emotions and tone they express. For example, if the audio emotion is happy, the first adjustment parameters may make the emoticon appear more lively and bright.

[0118] The speech-to-text conversion is analyzed and natural language processing (NLP) techniques are used to extract the text's sentiment (e.g., positive, negative) and style (e.g., humorous, serious, etc.). This analysis of the text's sentiment and style generates a second adjustment parameter that influences the expression of the emoticon. For example, if the text's sentiment is humorous, the second adjustment parameter will adjust the emoticon's visual presentation to make it more humorous.

[0119] Finally, the analysis results of the audio and text are integrated. By combining the first and second adjustment parameters, the emotional and stylistic characteristics of the audio and text can be more comprehensively reflected, and the content adjustment parameter is ultimately calculated. This parameter can dynamically adjust the specific content of the emoticon package, such as its expression, action, color, and background, to ensure that it matches the audio and text in terms of emotion and style.

[0120] In S430 , parameters are adjusted based on the content obtained from the audio analysis, and specific adjustments are made to the pending emoticon package, which may include facial expressions, dynamic effects, colors, and backgrounds.

[0121] Among them, facial expressions are to change the facial expressions of emoticons (such as smiling, frowning, etc.); dynamic effects are to add animation effects according to the audio rhythm (such as fast flashing, jumping, etc.); color and background are to adjust the color and background of emoticons to enhance emotional expression (such as using brighter tones to express happy emotions, or using dark tones to express sad emotions).

[0122] Ultimately, the adjusted emoji package (target emoji package) can highly match the audio information both visually and emotionally, enabling it to better coordinate with the user's audio content.

[0123] Please refer to Figure 6 In some implementations of this embodiment, the emoticon package generation method is applied to a blockchain network, which includes multiple electronic devices, each of which is a blockchain node.

[0124] After S400, the emoticon package generation method may further include:

[0125] S500: Pack the target emoticon package and the target image into a block.

[0126] S600: Synchronize the block to each blockchain node through the blockchain network.

[0127] In this embodiment, the data after the emoticon package is generated (target emoticon package and target image) will be packaged into a block and synchronized to all blockchain nodes through the blockchain network to achieve data consistency across devices. The data between each blockchain node can be synchronized in real time to ensure that users on different devices can see the same target emoticon package. The immutability of the blockchain effectively protects the content and image data of the emoticon package after it is generated. The target emoticon package generated by the user will be packaged into a block and stored on multiple blockchain nodes, thereby ensuring that the data is not tampered with at any time in the network. All emoticon package data (including the target emoticon package, target image and its generation process) are recorded on the blockchain, which can be traced back to the specific time of generation, generator and other information, thereby improving the transparency of the generation process.

[0128] In S500, the generated target emoticon package and the original target image are packaged into a block. A block is a data unit in the blockchain that contains information related to the emoticon package data and the image.

[0129] Specifically, each block will contain the metadata of the emoticon package (such as style, emotion, template type, etc.), the content of the generated target emoticon package, and user-related historical data (such as preferences, adjustment instructions, etc.).

[0130] In S600, the block containing the target emoji package and target image is synchronized to each blockchain node via the blockchain network. Once the generated emoji package is packaged, it is not only stored on a single device or server, but is also shared and stored across multiple electronic devices via the blockchain network. Each electronic device in the blockchain network, acting as a blockchain node, receives a copy of this block. These nodes verify the block according to the blockchain protocol to ensure its legitimacy and consistency, and then synchronize it to each node's local storage. Each node in the blockchain performs decentralized verification of this data, ensuring the security, immutability, and reliability of the emoji package content. Once the block is synchronized to all nodes, the target emoji package can be shared across multiple devices.

[0131] It should be noted that the above-mentioned user historical data may include the above-mentioned blockchain data.

[0132] The following describes an embodiment of the device of the present application, which can be used to execute the emoticon package generation method in the above embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the emoticon package generation method in the above embodiment of the present application.

[0133] Figure 7 A block diagram of an emoticon package generating device according to an embodiment of the present application is shown.

[0134] Reference Figure 7 As shown, according to an embodiment of the present application, an emoticon package generating device 700 includes a target image uploading module 710 , a target image conversion module 720 , a content adjustment information module 730 , and a pending emoticon package adjustment module 740 .

[0135] Among them, the target image upload module 710 is used to obtain usage status information and user history data in response to the upload of the target image, and the usage status information includes the current usage scenario, current trajectory and current emotion; the user history data includes the user's usage frequency of each emoticon package, the usage scenario and the emoticon package data generated by the user; the target image conversion module 720 is used to convert the target image through usage status information and user history data to generate a pending emoticon package; the content adjustment information module 730 is used to obtain user content adjustment information; the pending emoticon package adjustment module 740 is used to adjust the pending emoticon package according to the user content adjustment information to obtain the target emoticon package.

[0136] Screening In some feasible embodiments of the present application, the target image conversion module 720 specifically includes: a template screening submodule, used to filter out emoticon package templates from the emoticon package data generated by the user according to the usage status information; and a picture conversion submodule, used to convert the target image into a pending emoticon package according to the emoticon package template.

[0137] In some feasible embodiments of the present application, the template screening submodule specifically includes: a style type parameter unit, used to determine the style type parameters based on the current usage scenario, the current trajectory and the user's usage scenario of each emoticon package; an emotion type parameter unit, used to determine the emotion type parameters based on the current emotion and the user's usage frequency of each emoticon package; an emoticon package template screening unit, used to filter out emoticon package templates from the emoticon package data generated by the user based on the style type parameters and the emotion type parameters.

[0138] In some feasible embodiments of the present application, the image conversion submodule specifically includes: a first preliminary emoticon package generation unit, used to convert the target image according to the emoticon package template to generate a first preliminary emoticon package; an emoticon package usage frequency analysis unit, used to obtain user preference parameters based on the user's usage frequency of each emoticon package; a first preliminary emoticon package adjustment unit, used to adjust the first preliminary emoticon package according to the user preference parameters to obtain a pending emoticon package.

[0139] In some feasible embodiments of the present application, the target image conversion module 720 specifically includes: a second preliminary emoticon package generation submodule, used to convert the target image according to the emoticon package data generated by the user to obtain a second preliminary emoticon package; a second preliminary emoticon package adjustment submodule, used to adjust the parameters of the second preliminary emoticon package according to the usage status information and the user historical data to obtain the pending emoticon package.

[0140] In some feasible embodiments of the present application, the second preliminary emoticon package adjustment submodule specifically includes: a style type determination unit, used to determine the style type parameters based on the current usage scenario, the current trajectory and the user's usage scenario of each emoticon package; an emotion type determination unit, used to determine the emotion type parameters based on the current emotion and the user's usage frequency of each emoticon package; and a final parameter adjustment unit, used to adjust the parameters of the second preliminary emoticon package based on the style type parameters and the emotion type parameters to obtain the pending emoticon package.

[0141] In some feasible embodiments of the present application, the content adjustment information includes content adjustment instructions, and the pending emoticon package adjustment module 740 specifically includes: a content adjustment parameter submodule, used to determine the content adjustment parameters according to the content adjustment instructions; and a pending emoticon package adjustment submodule, used to adjust the pending emoticon package according to the content adjustment parameters to obtain a target emoticon package.

[0142] In some feasible embodiments of the present application, the content adjustment information includes audio information, and the pending emoticon package adjustment module 740 specifically includes: an audio information parsing submodule, used to parse the audio information and determine audio parameters; a content adjustment parameter submodule, used to determine content adjustment parameters based on the audio parameters; and an emoticon package adjustment submodule, used to adjust the pending emoticon package based on the content adjustment parameters to obtain a target emoticon package.

[0143] In some feasible embodiments of the present application, the audio parameters include audio emotion, audio style, text emotion, and text style; the audio information analysis submodule specifically includes: an audio information analysis unit, used to analyze the audio information to obtain audio emotion and audio style; a voice information determination unit, used to determine whether the audio information contains voice information; a voice information conversion unit, used to convert the voice information into voice text if it contains voice information; and a voice-text analysis unit, used to analyze the voice text to obtain text emotion and text style.

[0144] In some feasible embodiments of the present application, the content adjustment parameter submodule specifically includes: a first adjustment parameter unit, used to obtain a first adjustment parameter based on the audio emotion and the audio style; a second adjustment parameter unit, used to obtain a second adjustment parameter based on the text emotion and the text style; a content adjustment parameter unit, used to determine the content adjustment parameter based on the first adjustment parameter, the second adjustment parameter and the speech text.

[0145] In some feasible embodiments of the present application, the emoticon package generation method is applied to a blockchain network, which includes multiple electronic devices, each of which is a blockchain node; the emoticon package generation device also includes: a block packaging module, which is used to package the target emoticon package and the target image into a block; and a node synchronization module, which is used to synchronize the block to each blockchain node through the blockchain network.

[0146] In this embodiment, by acquiring and analyzing usage status information and user history data, a target emoticon package tailored to the user's current needs and preferences can be generated. Through further adjustments, the user can obtain a personalized and precise target emoticon package. Ultimately, the user-generated emoticon package is not only more personalized but also highly adaptable to various usage scenarios, enhancing the user experience.

[0147] Figure 8 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown.

[0148] It should be noted that Figure 8The computer system of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0149] like Figure 8 As shown, the computer system includes a central processing unit (CPU) 1801, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1802 or the program loaded from the storage part 1808 into the random access memory (RAM) 1803, such as executing the method described in the above embodiment. Various programs and data required for system operation are also stored in the RAM 1803. The CPU 1801, ROM 1802 and RAM 1803 are connected to each other via a bus 1804. An input / output (I / O) interface 1805 is also connected to the bus 1804.

[0150] The following components are connected to the I / O interface 1805: an input section 1806 including a keyboard, a mouse, and the like; an output section 1807 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and speakers; a storage section 1808 including a hard disk; and a communication section 1809 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 1809 performs communication processing via a network such as the Internet. A drive 1810 is also connected to the I / O interface 1805 as needed. Removable media 1811, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 1810 as needed, so that computer programs read from the removable media can be installed in the storage section 1808 as needed.

[0151] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 1809, and / or installed from a removable medium 1811. When the computer program is executed by the central processing unit (CPU) 1801, the various functions defined in the system of the present application are executed.

[0152] It should be noted that the computer-readable medium shown in the embodiments of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a 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 above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0153] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0154] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0155] As another aspect, the present application further provides a computer-readable medium, which may be included in the electronic device described in the above embodiments, or may exist independently without being incorporated into the electronic device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device implements the method described in the above embodiments.

[0156] This specification also provides a computer program product, which stores at least one instruction, and the at least one instruction is loaded and executed by the processor as described above. Figures 1 to 6 The method of the embodiment shown, the specific execution process can be found in Figures 1 to 6 The detailed description of the illustrated embodiment will not be repeated here.

[0157] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the application, the features and functions of two or more modules or units described above can be concretized in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0158] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0159] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of this application and include common knowledge or customary techniques in the art that are not disclosed herein.

[0160] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for generating an emoticon package, characterized in that: The expression package generation method comprises: In response to the upload of the target image, usage status information and user history data are obtained, wherein the usage status information includes the current usage scenario, current trajectory, and current emotion; the user history data includes the user's usage frequency of each emoticon package, the usage scenario, and the emoticon package data generated by the user; By using the state information and the user's historical data, the target image is converted to generate a pending emoticon package; Obtain user content adjustment information; The pending emoticon package is adjusted according to the user content adjustment information to obtain a target emoticon package.

2. The emoticon package generating method according to claim 1, wherein: The converting of the target image by using the state information and the user history data to generate a pending emoticon package specifically includes: Filtering emoticon package templates from the emoticon package data generated by the user according to the usage status information; The target image is converted into a pending emoticon package according to the emoticon package template.

3. The expression package generation method according to claim 2, wherein: The step of filtering out an emoticon package template from the emoticon package data generated by the user according to the usage status information specifically includes: Determining a style type parameter according to the current usage scenario, the current trajectory, and the user's usage scenario of each emoticon package; Determining an emotion type parameter according to the current emotion and the frequency of use of each emoticon package by the user; According to the style type parameter and the emotion type parameter, an emoticon package template is screened out from the emoticon package data generated by the user.

4. The expression package generation method according to claim 2, wherein: The step of converting the target image into a pending emoticon package according to the emoticon package template specifically includes: Converting the target image according to the emoticon package template to generate a first preliminary emoticon package; Obtaining user preference parameters based on the user's usage frequency of each emoticon package; The first preliminary emoticon package is adjusted according to the user preference parameters to obtain a pending emoticon package.

5. The expression package generation method according to claim 1, wherein: The converting of the target image by using the state information and the user history data to generate a pending emoticon package specifically includes: Converting the target image according to the emoticon package data generated by the user to obtain a second preliminary emoticon package; According to the usage status information and the user history data, the parameters of the second preliminary emoticon package are adjusted to obtain the pending emoticon package.

6. The expression package generation method according to claim 5, wherein: The step of adjusting parameters of the second preliminary emoticon package according to the usage status information and the user history data to obtain the pending emoticon package specifically includes: Determining a style type parameter according to the current usage scenario, the current trajectory, and the user's usage scenario of each emoticon package; Determining an emotion type parameter according to the current emotion and the frequency of use of each emoticon package by the user; The parameters of the second preliminary emoticon package are adjusted according to the style type parameter and the emotion type parameter to obtain the pending emoticon package.

7. An emoticon package generating device, characterized in that: The emoticon package generating device comprises: A target image upload module is configured to obtain usage status information and user history data in response to the upload of the target image, wherein the usage status information includes the current usage scenario, current trajectory, and current emotion; the user history data includes the user's usage frequency of each emoticon package, the usage scenario, and the emoticon package data generated by the user; A target image conversion module is used to convert the target image by using the state information and user history data to generate a pending emoticon package; Content adjustment information module, used to obtain user content adjustment information; The pending emoticon package adjustment module is used to adjust the pending emoticon package according to the user content adjustment information to obtain a target emoticon package.

8. A computer-readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the emoticon package generation method according to any one of claims 1 to 6 is implemented.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the emoticon package generation method according to any one of claims 1 to 6.

10. A computer program product comprising one or more computer programs, characterized in that When the one or more computer programs are executed by one or more processors, the steps of the emoticon package generation method according to any one of claims 1 to 6 are implemented.

Images