Nursing processing method and device, storage medium and electronic equipment

Abstract

The embodiment of the invention discloses a nursing processing method and device, a storage medium and electronic equipment, and the method comprises the steps that a server obtains a story association instruction sent by intelligent nursing equipment, and obtains a target nursing video collected by the intelligent nursing equipment based on the story association instruction, based on the target nursing video and the story association instruction, a nursing processing large model is adopted to perform story association processing to obtain target association story content, the target association story content is sent to the intelligent nursing device, and the target association story content is used for the intelligent nursing device to determine target story voice and output the target story voice. Therefore, the function of telling stories according to the voice indication of the user and the nursing video related to the user is realized, the nursing interaction function of the intelligent nursing equipment is enriched, and the nursing interestingness of the intelligent nursing equipment is increased.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a nursing processing method, device, storage medium, and electronic device. Background Art

[0002] With the development of technologies such as the Internet of Things, artificial intelligence, and cloud computing, smart cameras have gradually transformed from traditional security monitoring devices into multifunctional, intelligent home assistants, becoming widely integrated into people's daily lives. In related technologies, smart cameras, through built-in sensors, high-definition lenses, and artificial intelligence technology, can achieve real-time video monitoring, abnormal behavior detection, intelligent recognition (such as facial recognition and object detection), and remote alarm functions. In addition to security functions, smart cameras are gradually being integrated into other aspects of family life. For example, in areas such as infant monitoring, pet care, and elderly care, smart cameras can monitor family members' activities in real time and provide feedback. They can also communicate with remote caregivers in real time through built-in voice dialogue functions. Therefore, how to enrich the interactive functions of smart cameras in the care field is a technical problem that needs to be solved urgently. Summary of the Invention

[0003] The embodiments of the present application provide a nursing processing method, device, computer storage medium, and electronic device. The technical solution is as follows:

[0004] In a first aspect, an embodiment of the present application provides a nursing processing method, applied to a server, the method comprising:

[0005] Obtaining a story association instruction sent by a smart nursing device, and obtaining a target nursing video collected by the smart nursing device based on the story association instruction, wherein the story association instruction is generated by the smart nursing device based on the story association voice after collecting the story association voice for the family nursing scenario;

[0006] Based on the target nursing video and the story association instruction, a nursing processing model is used to perform story association processing to obtain target association story content;

[0007] The target associative story content is sent to the smart nursing device, and the target associative story content is used by the smart nursing device to determine the target story voice and output the target story voice.

[0008] In a certain possible implementation, the story association processing is performed based on the target nursing video and the story association instruction using a nursing processing macro model to obtain target association story content, including:

[0009] Based on the target care video, the target person's age is identified and processed to obtain the target person's age;

[0010] Based on the target person's age, the story association instruction and the target nursing video, story association prompt words are generated, and the story association processing is performed based on the nursing processing model using the story association prompt words to obtain the target association story content.

[0011] In a certain possible implementation, generating story association prompt words based on the target person's age, the story association instruction, and the target nursing video includes:

[0012] Determining preset story association prompt information corresponding to the age of the target person, and determining a story element extraction rule for the target nursing video based on the story association instruction;

[0013] Story association prompt words are generated based on the preset story association prompt information, the story element extraction rules and the target nursing video.

[0014] In a possible implementation, the story association prompt words are used to perform story association processing based on the nursing processing model to obtain target association story content, including:

[0015] Inputting the story association prompt words and the target care video into the care processing model;

[0016] The target nursing video is subjected to story material recognition processing by the nursing processing macromodel to obtain story material data, the story material data is subjected to story element extraction processing by the nursing processing macromodel to obtain story association element information, and the target association story content is obtained by performing story association processing based on preset story association prompt information and story association element information by the nursing processing macromodel;

[0017] The target associative story content is outputted through the nursing processing model.

[0018] In a certain possible implementation manner, the performing story association processing based on the preset story association prompt information and the story association element information by the nursing processing macro model to obtain target association story content includes:

[0019] The nursing processing model determines the target story style based on the preset story association prompt information, determines the target story framework based on the story association element information, and performs associative reasoning on the story framework based on the target story style to obtain the target associative story content.

[0020] In a second aspect, an embodiment of the present application provides a nursing processing method, which is applied to an intelligent nursing device, and the method includes:

[0021] Collecting story association voice for family care scenarios, and generating story association instructions based on the story association voice;

[0022] Collecting a target nursing video based on the story association instruction, sending the story association instruction and the target nursing video to a server, wherein the story association instruction and the target nursing video are used by the server to perform story association processing based on a nursing processing large model to obtain target association story content;

[0023] receiving the target associative story content sent by the server;

[0024] A target story voice is determined based on the target associative story content, and the target story voice is output.

[0025] In a possible implementation, collecting the target care video based on the story association instruction includes:

[0026] Acquire a story association instruction text corresponding to the story association voice based on the story association instruction, and determine a story material provision method based on the story association instruction text;

[0027] Determine a target collection duration based on the story material provision method, and determine a target collection time period based on the collection moment of the story-associated voice and the target collection duration;

[0028] A family care video for the family care scenario is obtained, and a target care video in the target collection time period is extracted from the family care video.

[0029] In a possible implementation, determining the target story voice based on the target associative story content includes:

[0030] determining a target virtual human voice from preset virtual human voices;

[0031] The target story voice is obtained by using the target virtual human voice to perform voice generation processing based on the target associative story content.

[0032] In a third aspect, an embodiment of the present application provides a nursing processing device, applied to a server, comprising:

[0033] a data acquisition module for acquiring a story association instruction sent by a smart nursing device, and acquiring a target nursing video collected by the smart nursing device based on the story association instruction, wherein the story association instruction is generated by the smart nursing device based on the story association voice collected for a family nursing scenario;

[0034] A story association module is used to perform story association processing based on the target nursing video and the story association instruction using a nursing processing large model to obtain target association story content;

[0035] The data sending module is used to send the target associative story content to the smart nursing device, and the target associative story content is used by the smart nursing device to determine the target story voice and output the target story voice.

[0036] Optionally, the story association module includes:

[0037] A person recognition unit is used to perform person age recognition processing based on the target care video to obtain the target person's age;

[0038] The association processing unit is used to generate story association prompt words based on the target person's age, the story association instruction and the target nursing video, and use the story association prompt words to perform story association processing based on the nursing processing model to obtain the target association story content.

[0039] Optionally, the associative processing unit includes:

[0040] A first information determination subunit is configured to determine preset story association prompt information corresponding to the age of the target person, and determine a story element extraction rule for the target nursing video based on the story association instruction;

[0041] The second information determination subunit is used to generate story association prompt words based on the preset story association prompt information, the story element extraction rules and the target nursing video.

[0042] Optionally, the associative processing unit includes:

[0043] A first association processing sub-unit is used to input the story association prompt words and the target nursing video into the nursing processing large model;

[0044] a second association processing subunit, configured to perform story material recognition processing on the target nursing video using the nursing processing macromodel to obtain story material data, perform story element extraction processing on the story material data using the nursing processing macromodel to obtain story association element information, and perform story association processing based on preset story association prompt information and story association element information using the nursing processing macromodel to obtain target association story content;

[0045] The third associative processing sub-unit is used to output the target associative story content through the nursing processing large model.

[0046] Optionally, the second associative processing subunit is specifically configured to:

[0047] The nursing processing model determines the target story style based on the preset story association prompt information, determines the target story framework based on the story association element information, and performs associative reasoning on the story framework based on the target story style to obtain the target associative story content.

[0048] In a fourth aspect, an embodiment of the present application provides a nursing processing device, which is applied to an intelligent nursing device, and the device includes:

[0049] An instruction generation module, configured to collect story association voices for family care scenarios and generate story association instructions based on the story association voices;

[0050] A data sending module is used to collect a target nursing video based on the story association instruction, and send the story association instruction and the target nursing video to a server, where the story association instruction and the target nursing video are used by the server to perform story association processing based on a nursing processing large model to obtain target association story content;

[0051] A data receiving module, configured to receive the target associative story content sent by the server;

[0052] A data output module is used to determine a target story voice based on the target associative story content, and output the target story voice.

[0053] Optionally, the data sending module includes:

[0054] A first data collection unit is configured to obtain a story association instruction text corresponding to the story association voice based on the story association instruction, and determine a story material provision method based on the story association instruction text;

[0055] A second data collection unit is configured to determine a target collection duration based on the story material provision method, and determine a target collection time period based on the collection moment of the story-associated voice and the target collection duration;

[0056] The third data acquisition unit is used to obtain a family care video for the family care scenario, and extract a target care video in the target acquisition time period from the family care video.

[0057] Optionally, the data output module includes:

[0058] A first data output unit, configured to determine a target virtual human voice from preset virtual human voices;

[0059] The second data output unit is used to use the target virtual human voice to perform voice generation processing based on the target associative story content to obtain the target story voice.

[0060] In a fifth aspect, an embodiment of the present application provides a computer storage medium, which has multiple instructions, and the instructions are suitable for being loaded by a processor and executing the above method.

[0061] In a sixth aspect, an embodiment of the present application provides an electronic device, which may include: a memory and a processor; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the memory and executing the above method.

[0062] The beneficial effects of the technical solutions provided in the embodiments of the present application include at least:

[0063] In the nursing processing method provided in the embodiment of the present application, the server obtains a story association instruction sent by the intelligent nursing device, obtains a target nursing video collected by the intelligent nursing device based on the story association instruction, uses the nursing processing large model to perform story association processing based on the target nursing video and the story association instruction to obtain the target association story content, and sends the target association story content to the intelligent nursing device. The target association story content is used by the intelligent nursing device to determine the target story voice and output the target story voice. In this way, the server generates the target association story content based on the target nursing video and story association instruction collected by the intelligent nursing device through the powerful text processing capabilities of the large model, so that the intelligent nursing device can output the target story voice according to the target association story content, realizes the function of telling stories according to the user's voice instructions and nursing videos related to the user, enriches the nursing interaction function of the intelligent nursing device, and increases the nursing interest of the intelligent nursing device. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0065] Figure 1 This is a flow chart of a nursing treatment method provided in an embodiment of the present application;

[0066] Figure 2 This is a flow chart of another nursing treatment method provided in an embodiment of the present application;

[0067] Figure 3 This is a flow chart of another nursing treatment method provided in an embodiment of the present application;

[0068] Figure 4 This is a flow chart of another nursing treatment method provided in an embodiment of the present application;

[0069] Figure 5 This is a structural diagram of a nursing processing device provided in an embodiment of the present application;

[0070] Figure 6 This is a structural diagram of a nursing processing device provided in an embodiment of the present application;

[0071] Figure 7 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0072] In order to make the purpose, features, and advantages of the embodiments of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of this application.

[0073] In the description of this application, it should be understood that the terms "first", "second", etc. are used for descriptive purposes only and should not be understood to indicate or imply relative importance. In the description of this application, it should be noted that, unless otherwise expressly specified and limited, "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances. In addition, in the description of this application, unless otherwise specified, "multiple" refers to two or more. "and / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0074] The present application is described in detail below with reference to specific embodiments.

[0075] In one embodiment, Figure 1 As shown, a nursing processing method is proposed. The method can be implemented by a computer program and can be run on a nursing processing device based on the von Neumann architecture. The computer program can be integrated into an application or run as an independent tool application.

[0076] Specifically, the execution subject of the nursing processing method is a server, and the method includes:

[0077] S101, obtaining a story association instruction sent by an intelligent nursing device, and obtaining a target nursing video collected by the intelligent nursing device based on the story association instruction.

[0078] Among them, the story association instruction is generated based on the story association voice after the smart care device collects the story association voice for the home care scenario.

[0079] It's understood that smart care devices refer to smart cameras installed in a home environment. Specifically, they can be installed in spaces like living rooms and bedrooms. In addition to capturing video, these devices also have voice communication capabilities, capturing the user's voice and responding accordingly. For example, a smart care device could capture a user's voice inquiries about the temperature or weather and respond with temperature data or weather information.

[0080] The story association instruction refers to an instruction for instructing the server to perform story association processing to generate associative story content.

[0081] Target care videos are videos of family care scenarios captured by smart care devices after generating story association instructions. For example, a family care scenario might be a parent caring for a child, and the target care video would be a dynamic image of the parent caring for the child.

[0082] In some embodiments, the server receives a story association instruction sent by the smart nursing device, and receives a target nursing video collected by the smart nursing device based on the story association instruction and sent by the smart nursing device.

[0083] S102, based on the target nursing video and the story association instruction, a nursing processing model is used to perform story association processing to obtain target association story content.

[0084] It is understood that the large-scale model for nursing processing can directly use multimodal large language models (MLLMs), or it can be a large language model obtained by training the MLLM for story association scenarios. Multimodal large language models can process various types of data, including text, images, video, and audio, and can perform data conversion and processing between different modalities.

[0085] The target associative story content refers to the story content in text form obtained by the nursing processing model extracting story materials from the target nursing video and performing story associative processing based on the story materials.

[0086] In some embodiments, step S102 may be performed as follows: determining the age of the care recipient through the target care video, performing story association processing according to the age of the care recipient, story association instructions and the target care video through the care processing model to obtain the target association story content.

[0087] S103, sending the target associative story content to the smart nursing device, where the target associative story content is used by the smart nursing device to determine the target story voice and output the target story voice.

[0088] In some embodiments, after the server obtains the target associative story content, it sends the target associative story content to the smart nursing device, so that the smart nursing device can determine the target story voice according to the target associative story content and output the target story voice.

[0089] In an embodiment of the present application, the server obtains a story association instruction sent by the smart nursing device, obtains a target nursing video collected by the smart nursing device based on the story association instruction, uses a nursing processing large model to perform story association processing based on the target nursing video and the story association instruction to obtain a target association story content, and sends the target association story content to the smart nursing device. The target association story content is used by the smart nursing device to determine the target story voice and output the target story voice. In this way, the server generates the target association story content based on the target nursing video and story association instruction collected by the smart nursing device through the powerful text processing capabilities of the large model, so that the smart nursing device can output the target story voice according to the target association story content, realizing the function of telling stories according to the user's voice instructions and nursing videos related to the user, enriching the nursing interaction function of the smart nursing device, and increasing the nursing interest of the smart nursing device.

[0090] See Figure 2 , Figure 2 It is a flow chart of another embodiment of a nursing treatment method proposed in this application.

[0091] Specifically, the execution subject of the nursing processing method is a server, and the method includes:

[0092] S201, obtaining a story association instruction sent by the intelligent nursing device, and obtaining a target nursing video collected by the intelligent nursing device based on the story association instruction.

[0093] Specifically, the implementation of step S201 can be found in Figure 1 The description of the relevant steps in the illustrated embodiment will not be repeated in detail here.

[0094] S202: Perform age recognition processing on the target person based on the target care video to obtain the target person's age.

[0095] The target person age refers to the age of the care recipient identified from the target care video. For example, the care recipient is usually a child, and the target person age is the specific age of the child.

[0096] In some embodiments, executing step S202 may specifically include: intercepting a facial image of a reference person from the target care video, performing facial detection processing on the facial image of the reference person to obtain the age of the reference person, and determining the target person's age that is less than or equal to the preset age in the reference person's age. Specifically, when performing facial detection processing on the facial image of the reference person to obtain the reference age, the facial image of the reference person can be face matched with the preset facial image to obtain a face matching result. If the face matching result indicates that there is a first facial image that matches the facial image of the reference person in the preset facial image, the age of the person corresponding to the first facial image is used as the reference person's age; if the face matching result indicates that there is no preset facial image that matches the facial image of the reference person, then age detection processing is performed on the facial image of the reference person to obtain the reference person's age. The preset facial image can be uploaded to the server by the user in advance on the user end, and the age of the person corresponding to the preset facial image can be set by the user in advance on the user end and uploaded to the server.

[0097] It is understandable that the facial image of the reference person captured from the target care video may include the facial image of the caregiver and the facial image of the person being cared for. The person being cared for may be a younger child. By comparing the preset age with the age of the reference person, the age of the person being cared for, that is, the age of the target person, can be determined.

[0098] S203, generating story association prompt words based on the target person's age, story association instructions and target care video, and performing story association processing based on the care processing model using the story association prompt words to obtain target association story content.

[0099] It can be understood that the story association prompt word includes task description information that instructs the large model to perform story association processing to generate associative story content.

[0100] In some embodiments, the step of generating story association prompt words based on the target person's age, story association instructions, and target care video may specifically include the following steps:

[0101] A1: Determine the preset story association prompt information corresponding to the target person's age, and determine the story element extraction rules for the target care video based on the story association instructions;

[0102] A2: Generate story association prompt words based on preset story association prompt information, story element extraction rules and target care video.

[0103] In step A1, the preset story association prompt information includes multi-dimensional story association requirements adapted to the target person's age. For example, the preset story association prompt information may include a story difficulty level adapted to the target person's age, a story length limit, the story's significance, story word requirements, story interaction requirements, and story emotions. It is understood that story difficulty levels can include various levels, such as beginner, moderate, difficult, and difficult, and different story difficulty levels can be set for children of different age groups based on expert experience. The story length limit can specify the total number of words in the story. The story's significance can include, but is not limited to, educational enlightenment, emotional resonance, cultural heritage, personal growth, social cohesion, and the like. Story word requirements can include, but are not limited to, the use of reduplicated words or simple vocabulary. Story interaction requirements can specify whether the story has an interactive process with the listener or does not require an interactive process. Story emotions can include optimism, objectivity, and neutrality, and the like.

[0104] Story element extraction rules are rules used to instruct the macro model on how to extract story elements. Story elements can include themes, characters, environments, objects, and so on. These rules may include, but are not limited to, extracting story elements from cloth books, home environments, picture books, cards, user voice prompts, and objects displayed by the user.

[0105] When executing step A1, the preset story association prompt information corresponding to the target person's age is determined, which can be specifically: obtaining a preset mapping relationship between age and story association prompt information, the preset mapping relationship can store at least one reference age group and reference story association prompt information corresponding to the reference age group, each reference story association prompt information can include at least one of the story difficulty level, story length limit, story meaning, story vocabulary requirements, and story interaction requirements, the target age group of the target person's age in the preset mapping relationship can be determined, the target story association prompt information corresponding to the target age group is determined from the preset mapping relationship, and the target story association prompt information is determined as the preset story association prompt information corresponding to the target person's age.

[0106] When executing step A1, the story element extraction rules for the target nursing video are determined based on the story association instructions. Specifically, the story association instruction text is obtained from the story association instruction, the story element keyword extraction processing is performed on the story association instruction text to obtain the target story element keywords, and the story element extraction rules for the target nursing video are determined based on the target story element keywords.

[0107] When executing step A2, a first prompt word that establishes a connection with the target nursing video is determined, and the first prompt word, preset story association prompt information and story element extraction rules are summarized according to a preset prompt word generation format to obtain a story association prompt word.

[0108] In some embodiments, the step of performing story association processing based on the nursing processing model using story association prompts to obtain target association story content may specifically include the following steps:

[0109] The story association prompt words and the target nursing video are input into the nursing processing big model; the target nursing video is subjected to story material recognition processing by the nursing processing big model to obtain story material data; the story material data is subjected to story element extraction processing by the nursing processing big model to obtain story association element information; the target association story content is obtained by performing story association processing based on the preset story association prompt information and story association element information by the nursing processing big model; the target association story content is output by the nursing processing big model.

[0110] Specifically, the target nursing video is subjected to story material recognition processing by the nursing processing big model to obtain story material data. This can be understood as follows: the nursing processing big model extracts the target story material video or target story material image including story material from the target nursing video according to the story element extraction rules indicated by the preset story association prompt information in the story association prompt words, and determines the target story material video as story material data, or determines the target story material image as story material data.

[0111] Specifically, the supervising processing model extracts story elements from the story material data to obtain story association element information. This can be understood as follows: if the story material data is a target story material video, the supervising processing model extracts key story material video frames from the target story material video and performs object recognition on the key story material video frames to obtain story association element information. If the story material data is a target story material image, the supervising processing model performs object recognition on the target story material image to obtain story association element information.

[0112] Specifically, the target associative story content is obtained by performing story association processing based on the preset story association prompt information and story association element information through the care processing large model. This can be understood as follows: the target story style is determined based on the preset story association prompt information, the target story framework is determined based on the story association element information, and the target associative story content is obtained by performing associative reasoning on the story framework based on the target story style. It can be understood that the care processing large model can determine the preset story association prompt information and story association element information from the story association prompt words. The care processing large model can determine the target story style based on the story difficulty level, the meaning of the story, the story word requirements, and the story interaction requirements in the preset story association prompt information. The target story style refers to the overall language characteristics, emotional tone, expression method, rhythm, character creation, and other characteristics used in narrating the story; then, the care processing large model performs story framework construction processing based on the story association element information to obtain the target story framework. The target story framework includes the basic plot of the story, character relationships, timeline, story climax, story ending, etc.

[0113] S204: Send the target associative story content to the smart nursing device. The target associative story content is used by the smart nursing device to determine the target story voice and output the target story voice.

[0114] Specifically, the implementation of step S204 can be found in Figure 2 The description of the relevant steps in the illustrated embodiment will not be repeated in detail here.

[0115] In an embodiment of the present application, a server obtains a story association instruction sent by a smart nursing device, obtains a target nursing video collected by the smart nursing device based on the story association instruction, performs character age recognition processing based on the target nursing video to obtain the target character age, generates story association prompts based on the target character age, story association instructions, and target nursing video, uses the story association prompts to perform story association processing based on a nursing processing large model to obtain target association story content, and sends the target association story content to the smart nursing device. The target association story content is used by the smart nursing device to determine the target story voice and output the target story voice. Thus, the server can generate an association story content that matches the target character age identified from the target nursing video based on the powerful text processing capabilities of the large model through the story association instruction and the target nursing video related to the user collected by the smart nursing device, thereby enabling the smart nursing device to output a story voice based on the association story content that matches the target face age, thereby realizing the function of telling stories based on the user's voice instructions and the nursing video related to the user, enriching the nursing interaction function of the smart nursing device, and increasing the nursing interest of the smart nursing device.

[0116] See Figure 3 , Figure 3 This is a flow chart of another embodiment of a nursing treatment method proposed in this application.

[0117] Specifically, the execution subject of the nursing processing method is the intelligent nursing device, and the method includes:

[0118] S301, collecting story association voice for family care scenarios, and generating story association instructions based on the story association voice.

[0119] The family care scenario refers to a situation where a caregiver provides care for a care recipient in a home environment. For example, if the caregiver is a father or mother and the care recipient is a 3-year-old child, the family care scenario could be a father or mother looking after the 3-year-old child in the living room.

[0120] The story association voice can be understood as the voice in which the caregiver wakes up the smart care device and instructs the smart care device to perform story association processing to generate the content of the associative story.

[0121] The story association instruction is an instruction generated by the smart care device to instruct the server to perform story association processing to generate an association story.

[0122] In some embodiments, after being in the awakened state, the smart care device collects story association voice for the home care scenario, performs speech-to-text processing on the story association voice to obtain story association instruction text, and generates story association instructions based on the story association instruction text.

[0123] Specifically, when the smart care device collects the device wake-up voice, the smart care device is in the wake-up state. For example, the wake-up voice can be a voice including the preset name corresponding to the smart care device.

[0124] S302, based on the story association instruction, the target nursing video is collected, and the story association instruction and the target nursing video are sent to the server. The story association instruction and the target nursing video are used by the server to perform story association processing based on the nursing processing model to obtain the target association story content.

[0125] In some embodiments, the target nursing video is collected based on the story association instruction, which can be specifically: determining the story association instruction text corresponding to the story association voice based on the story association instruction, determining the video collection duration according to the story association instruction text, determining the collection moment of the story association voice, and determining the target nursing video according to the collection moment of the story association voice and the video collection duration. The target nursing video is a nursing video within the target time period determined based on the collection moment of the story association voice and the video collection duration.

[0126] Specifically, the server uses the nursing processing model to perform story association processing based on the story association instruction and the target nursing video to obtain the target association story content. For details, please refer to Figure 1 or Figure 2 The description of the relevant parts in the illustrated embodiment will not be repeated in detail here.

[0127] S303: Receive the target associative story content sent by the server.

[0128] S304, determining a target story voice based on the target associative story content, and outputting the target story voice.

[0129] In some embodiments, text-to-speech processing may be performed on the target associative story content to obtain a target story voice. After the target story voice is generated, the target story voice is output.

[0130] In an embodiment of the present application, the intelligent nursing device collects story association voices for family nursing scenarios, generates story association instructions based on the story association voices, collects target nursing videos based on the story association instructions, sends the story association instructions and the target nursing videos to the server, and the story association instructions and the target nursing videos are used by the server to perform story association processing based on the nursing processing large model to obtain target association story content. The intelligent nursing device receives the target association story content sent by the server, determines the target story voice based on the target association story content, and outputs the target story voice. Thus, the intelligent nursing device collects story association voices to generate story association instructions, and sends the collected target nursing videos and story association instructions to the server, can perform story association processing through the server to obtain target association story content, can generate target story voice based on the target association story content, and outputs the target story voice, thereby realizing the function of telling stories according to the user's voice instructions and nursing videos related to the user, enriching the nursing interaction function of the intelligent nursing device, and increasing the storytelling function of the intelligent nursing device to increase the nursing interest. In addition, the smart care device generates the target associative story content through the server, which does not require the consumption of computing power resources of the smart care device. Therefore, there is no need to deploy hardware resources with higher computing power on the smart care device, thus saving the hardware cost of the smart care device.

[0131] See Figure 4 , Figure 4 This is a flow chart of another embodiment of a nursing treatment method proposed in this application.

[0132] Specifically, the execution subject of the nursing processing method is the intelligent nursing device, and the method includes:

[0133] S401, collecting story association voice for family care scenarios, and generating story association instructions based on the story association voice.

[0134] Among them, the family care scenario refers to the situation in which the caregiver takes care of the person being cared for in a home environment.

[0135] The story association voice can be understood as the voice in which the caregiver wakes up the smart care device and instructs the smart care device to perform story association processing to generate the content of the associative story.

[0136] The story association instruction is an instruction generated by the smart care device to instruct the server to perform story association processing to generate an association story.

[0137] In some embodiments, after being in the awakened state, the smart care device collects story association voice for the home care scenario, performs speech-to-text processing on the story association voice to obtain story association instruction text, and generates story association instructions based on the story association instruction text.

[0138] Specifically, when the smart care device collects the device wake-up voice, the smart care device is in the wake-up state. For example, the wake-up voice can be a voice including the preset name corresponding to the smart care device.

[0139] S402, obtaining a story association instruction text corresponding to the story association voice based on the story association instruction, and determining a story material providing method based on the story association instruction text.

[0140] It is understandable that the story association instruction text is obtained after the intelligent care device performs voice-to-text processing on the story association voice, so the story association instruction text can be obtained from the story association instruction.

[0141] Specifically, the smart care device can extract story material keywords from the story association instruction text to obtain target story material keywords, and then determine the method for providing story material based on the target story material keywords. Specifically, the story material provisioning methods may include: displaying story material based on picture books, displaying story material based on cloth books, displaying story material based on cards, displaying story material based on user voice prompts, or not displaying story material at all.

[0142] For example, the story association instruction text may be "Please determine the story material based on the picture book I show you, and then tell a story." The target story material keywords extracted from the story association instruction text may include "display," "picture book," and "story material." Then, it can be determined that the story material provision method is to display the story material based on the picture book.

[0143] S403: Determine a target collection duration based on the story material provision method, and determine a target collection time period based on the story-associated voice collection moment and the target collection duration.

[0144] Specifically, the target collection duration corresponding to the story material provision method can be queried from the preset mapping relationship between material provision methods and collection durations. It is understood that the preset mapping relationship between material provision methods and collection durations may include a mapping relationship between at least one reference story material provision method and a reference collection duration corresponding to the reference story material provision method. The reference collection duration corresponding to each reference story material provision method may be set based on expert experience.

[0145] Specifically, the collection time of the story-associated voice can be used as the target starting point, and the target time after the collection time of the story-associated voice that is separated from the collection time by the target collection time length can be used as the target end point. The target collection time period is determined based on the target starting point and the target end point.

[0146] S404: Acquire a family care video for a family care scenario, and extract a target care video in a target collection time period from the family care video.

[0147] It is understandable that the smart care device can continue to collect care videos in home care scenarios, and the care videos can be uploaded to the cloud by the smart care device for storage. Therefore, the home care videos of the target date can be obtained from the server. The target date is the date corresponding to the collection time of the story association voice.

[0148] It can be understood that when the story material providing method is to display the story material based on a picture book, the target care video may include a dynamic video of the caregiver displaying the picture book to the smart care device; when the story material providing method is to display the story material based on a cloth book, the target care video may include a dynamic video of the caregiver displaying the cloth book to the smart care device; when the story material providing method is to display the story material based on a card, the target care video may include a dynamic video of the caregiver displaying the card to the smart care device; when the story material providing method is to display the story material based on user voice prompts, the target care video may include a dynamic picture of the caregiver speaking the voice captured by the smart care device; when the story material providing method is not to display the story material, the target care video may include a dynamic picture of the caregiver and the environment in which the caregiver and the person being cared for are located captured by the smart care device.

[0149] S405, sending the story association instruction and the target nursing video to the server, the story association instruction and the target nursing video are used by the server to perform story association processing based on the nursing processing model to obtain the target association story content.

[0150] Specifically, the server uses the nursing processing model to perform story association processing based on the story association instruction and the target nursing video to obtain the target association story content. For details, please refer to Figure 1 or Figure 2The description of the relevant parts in the illustrated embodiment will not be repeated in detail here.

[0151] S406: Receive the target associative story content sent by the server.

[0152] S407, determining a target story voice based on the target associative story content, and outputting the target story voice.

[0153] In some embodiments, determining a target story voice based on a target associative story content may specifically include: determining a target virtual human voice from a preset virtual human voice; and using the target virtual human voice to perform voice generation processing based on the target associative story content to obtain a target story voice.

[0154] It is understood that a virtual voice library can be pre-built, storing multiple preset virtual voices, each capable of expressing different emotions and tones. A target virtual voice can be determined from the preset virtual voices based on a user-defined voice pattern. Alternatively, the emotional tone and story style of the target associative story content can be determined, and a target virtual voice that matches the emotional tone and story style of the story can be determined from the preset virtual voices.

[0155] It is understandable that the target story voice can be voice data that is consistent with the target virtual human voice audio and has the target associative story content. Optionally, a speech generation model can be used to perform text-to-speech processing on the target virtual human voice and the target associative story content to obtain the target story voice.

[0156] It is understandable that after generating the target story voice, the smart care device outputs the target story voice.

[0157] In an embodiment of the present application, the intelligent care device collects story association voice for a family care scenario, generates story association instructions based on the story association voice, obtains story association instruction text corresponding to the story association voice based on the story association instruction, determines a story material provision method based on the story association instruction text, determines a target collection duration based on the story material provision method, determines a target collection time period based on the collection moment of the story association voice and the target collection duration, obtains a family care video for a family care scenario, extracts a target care video within the target collection time period from the family care video, sends the story association instruction and the target care video to a server, uses the story association instruction and the target care video for the server to perform story association processing based on a large care processing model to obtain target association story content, receives the target association story content sent by the server, determines a target story voice based on the target association story content, and outputs the target story voice. In this way, the intelligent nursing device generates story association instructions by collecting story association voices, and collects target nursing videos of target collection duration, and sends the story association instructions and target nursing videos to the server, so that the server can determine the effective story material of the target nursing video of a certain duration and can generate target association story content that meets the story association instructions based on the story material. Then, the intelligent nursing device can generate the target story voice according to the target association story content and output the target story voice, realizing the function of telling stories according to the user's voice instructions and nursing videos related to the user, enriching the nursing interaction function of the intelligent nursing device, and increasing the nursing interest of the intelligent nursing device to tell stories. In addition, the intelligent nursing device generates the target association story content through the server, without consuming the computing power resources of the intelligent nursing device to generate it, so there is no need to deploy hardware resources with higher computing power on the intelligent nursing device, saving the hardware cost of the intelligent nursing device.

[0158] The following will be combined Figure 5 , the nursing processing device provided in the embodiment of the present application is introduced in detail. It should be noted that, Figure 5 The nursing processing device shown is used to execute the present application Figures 1 and 2 For the convenience of explanation, only the part related to the embodiment of the present application is shown. For the specific technical details not disclosed, please refer to the present application. Figures 1 and 2 The embodiment shown.

[0159] See Figure 5 , which shows a schematic diagram of the structure of the nursing processing device according to an embodiment of the present application. The nursing processing device 1 can be implemented as all or part of the device through software, hardware, or a combination of both. According to some embodiments, the nursing processing device 1 includes a data acquisition module 11, a story association module 12, and a data sending module 13, which are specifically used to:

[0160] A data acquisition module 11 is configured to acquire a story association instruction sent by a smart nursing device and acquire a target nursing video collected by the smart nursing device based on the story association instruction, wherein the story association instruction is generated by the smart nursing device based on the story association voice collected for a family nursing scenario;

[0161] A story association module 12 is configured to perform story association processing based on the target nursing video and the story association instruction using a nursing processing macro model to obtain target association story content;

[0162] The data sending module 13 is used to send the target associative story content to the smart nursing device. The target associative story content is used by the smart nursing device to determine the target story voice and output the target story voice.

[0163] Optionally, the story association module 12 includes:

[0164] A person recognition unit is used to perform person age recognition processing based on the target care video to obtain the target person's age;

[0165] The association processing unit is used to generate story association prompt words based on the target person's age, the story association instruction and the target nursing video, and use the story association prompt words to perform story association processing based on the nursing processing model to obtain the target association story content.

[0166] Optionally, the associative processing unit includes:

[0167] A first information determination subunit is configured to determine preset story association prompt information corresponding to the age of the target person, and determine a story element extraction rule for the target nursing video based on the story association instruction;

[0168] The second information determination subunit is used to generate story association prompt words based on the preset story association prompt information, the story element extraction rules and the target nursing video.

[0169] Optionally, the associative processing unit includes:

[0170] A first association processing sub-unit is used to input the story association prompt words and the target nursing video into the nursing processing large model;

[0171] a second association processing subunit, configured to perform story material recognition processing on the target nursing video using the nursing processing macromodel to obtain story material data, perform story element extraction processing on the story material data using the nursing processing macromodel to obtain story association element information, and perform story association processing based on preset story association prompt information and story association element information using the nursing processing macromodel to obtain target association story content;

[0172] The third associative processing sub-unit is used to output the target associative story content through the nursing processing large model.

[0173] Optionally, the second associative processing subunit is specifically configured to:

[0174] The nursing processing model determines the target story style based on the preset story association prompt information, determines the target story framework based on the story association element information, and performs associative reasoning on the story framework based on the target story style to obtain the target associative story content.

[0175] In the nursing processing device provided in the embodiment of the present application, the server obtains the story association instruction sent by the intelligent nursing device, obtains the target nursing video collected by the intelligent nursing device based on the story association instruction, uses the nursing processing large model to perform story association processing based on the target nursing video and the story association instruction to obtain the target association story content, and sends the target association story content to the intelligent nursing device. The target association story content is used by the intelligent nursing device to determine the target story voice and output the target story voice. In this way, the server generates the target association story content based on the target nursing video and story association instruction collected by the intelligent nursing device through the powerful text processing capability of the large model, so that the intelligent nursing device can output the target story voice according to the target association story content, realizes the function of telling stories according to the user's voice instructions and nursing videos related to the user, enriches the nursing interaction function of the intelligent nursing device, and increases the nursing interest of the intelligent nursing device.

[0176] The following will be combined Figure 6 , the nursing processing device provided in the embodiment of the present application is introduced in detail. It should be noted that, Figure 6 The nursing processing device shown is used to execute the present application Figures 3 and 4 For the convenience of explanation, only the part related to the embodiment of the present application is shown. For the specific technical details not disclosed, please refer to the present application. Figures 3 and 4 The embodiment shown.

[0177] See Figure 6, which shows a schematic diagram of the structure of the nursing processing device according to an embodiment of the present application. The nursing processing device 2 can be implemented as all or part of the device through software, hardware, or a combination of both. According to some embodiments, the nursing processing device 2 includes an instruction generation module 21, a data sending module 22, a data receiving module 23, and a data output module 24, which are specifically used to:

[0178] An instruction generation module 21 is used to collect story association voice for family care scenarios and generate story association instructions based on the story association voice;

[0179] A data sending module 22 is used to collect a target nursing video based on the story association instruction, and send the story association instruction and the target nursing video to a server. The story association instruction and the target nursing video are used by the server to perform story association processing based on a nursing processing model to obtain target association story content;

[0180] A data receiving module 23 is configured to receive the target associative story content sent by the server;

[0181] The data output module 24 is configured to determine a target story voice based on the target associative story content, and output the target story voice.

[0182] Optionally, the data sending module 22 includes:

[0183] A first data collection unit is configured to obtain a story association instruction text corresponding to the story association voice based on the story association instruction, and determine a story material provision method based on the story association instruction text;

[0184] A second data collection unit is configured to determine a target collection duration based on the story material provision method, and determine a target collection time period based on the collection moment of the story-associated voice and the target collection duration;

[0185] The third data acquisition unit is used to obtain a family care video for the family care scenario, and extract a target care video in the target acquisition time period from the family care video.

[0186] Optionally, the data output module 24 includes:

[0187] A first data output unit, configured to determine a target virtual human voice from preset virtual human voices;

[0188] The second data output unit is used to use the target virtual human voice to perform voice generation processing based on the target associative story content to obtain the target story voice.

[0189] In the care processing device provided in the embodiment of the present application, the intelligent care device collects story association voices for family care scenarios, generates story association instructions based on the story association voices, collects target care videos based on the story association instructions, sends the story association instructions and the target care videos to the server, and the story association instructions and the target care videos are used by the server to perform story association processing based on the care processing large model to obtain target association story content. The intelligent care device receives the target association story content sent by the server, determines the target story voice based on the target association story content, and outputs the target story voice. Thus, the intelligent care device collects story association voices to generate story association instructions, and sends the collected target care videos and story association instructions to the server. It can perform story association processing through the server to obtain target association story content, can generate target story voice based on the target association story content, and output the target story voice, thereby realizing the function of telling stories according to the user's voice instructions and the care videos related to the user, enriching the care interaction function of the intelligent care device, and increasing the care interest of the intelligent care device to tell stories. In addition, the smart care device generates the target associative story content through the server, which does not require the consumption of computing power resources of the smart care device. Therefore, there is no need to deploy hardware resources with higher computing power on the smart care device, thus saving the hardware cost of the smart care device.

[0190] Please refer to Figure 7 , which shows a schematic diagram of the structure of an electronic device provided by an exemplary embodiment of the present application. Specifically, the electronic device may be the server or intelligent nursing device described in the above embodiments. The electronic device in the embodiment of the present application may include one or more of the following components: a processor 110, a memory 120, an input device 130, an output device 140, and a bus 150. The processor 110, the memory 120, the input device 130, and the output device 140 may be connected via the bus 150.

[0191] The processor 110 may include one or more processing cores. The processor 110 utilizes various interfaces and circuits to connect various components within the electronic device. It executes instructions, programs, code sets, or instruction sets stored in the memory 120, as well as accesses data stored in the memory 120, to perform various functions of the electronic device and process data. Optionally, the processor 110 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 110 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily handles the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 110 and may be implemented separately via a communications chip.

[0192] The memory 120 may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory 120 includes a non-transitory computer-readable storage medium. The memory 120 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the following various method embodiments, etc. The operating system may be an Android system, including a system deeply developed based on the Android system, an iOS system developed by Apple, including a system deeply developed based on the iOS system, or other systems.

[0193] In order for the operating system to distinguish the specific application scenarios of third-party applications, it is necessary to open up data communication between third-party applications and the operating system so that the operating system can obtain the current scenario information of third-party applications at any time, and then perform targeted system resource adaptation based on the current scenario.

[0194] The input device 130 is used to receive input commands or data and includes, but is not limited to, a keyboard, a mouse, a camera, a microphone, or a touch-sensitive device. The output device 140 is used to output commands or data and includes, but is not limited to, a display device and a speaker. In one example, the input device 130 and the output device 140 may be combined, and the input device 130 and the output device 140 may be a touch-sensitive display.

[0195] The touch display screen can be designed as a full screen, a curved screen or a special-shaped screen. The touch display screen can also be designed as a combination of a full screen and a curved screen, or a combination of a special-shaped screen and a curved screen, which is not limited in the embodiments of the present application.

[0196] In addition, those skilled in the art will appreciate that the structures of the smart home devices shown in the above figures do not limit the smart home devices. Smart home devices may include more or fewer components than shown, or may combine certain components or arrange the components differently. For example, smart home devices may also include radio frequency circuits, input units, sensors, audio circuits, wireless fidelity (WiFi) modules, power supplies, Bluetooth modules, and other components, which will not be described in detail here.

[0197] In some embodiments, Figure 7 The processor 110 in the electronic device shown may be used to call the program of the nursing processing method stored in the memory 120 and specifically perform the following operations:

[0198] Obtaining a story association instruction sent by a smart nursing device, and obtaining a target nursing video collected by the smart nursing device based on the story association instruction, wherein the story association instruction is generated by the smart nursing device based on the story association voice after collecting the story association voice for the family nursing scenario;

[0199] Based on the target nursing video and the story association instruction, a nursing processing model is used to perform story association processing to obtain target association story content;

[0200] The target associative story content is sent to the smart nursing device, and the target associative story content is used by the smart nursing device to determine the target story voice and output the target story voice.

[0201] In yet other embodiments, Figure 7 The processor 110 in the electronic device shown may be used to call a program of another nursing processing method stored in the memory 120 and specifically perform the following operations:

[0202] Collecting story association voice for family care scenarios, and generating story association instructions based on the story association voice;

[0203] Collecting a target nursing video based on the story association instruction, sending the story association instruction and the target nursing video to a server, wherein the story association instruction and the target nursing video are used by the server to perform story association processing based on a nursing processing large model to obtain target association story content;

[0204] receiving the target associative story content sent by the server;

[0205] A target story voice is determined based on the target associative story content, and the target story voice is output.

[0206] An embodiment of the present application further provides a computer-readable storage medium storing at least one instruction, wherein the at least one instruction is used to be executed by a processor to implement the nursing processing method as described in the above embodiments.

[0207] An embodiment of the present application further provides a computer program product, which stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the nursing processing method described in the above embodiments.

[0208] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0209] The above description is merely an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A nursing treatment method, characterized in that: Applied to a server, the method includes: Obtaining a story association instruction sent by a smart nursing device, and obtaining a target nursing video collected by the smart nursing device based on the story association instruction, wherein the story association instruction is generated by the smart nursing device based on the story association voice after collecting the story association voice for the family nursing scenario; Based on the target nursing video and the story association instruction, a nursing processing model is used to perform story association processing to obtain target association story content; The target associative story content is sent to the smart nursing device, and the target associative story content is used by the smart nursing device to determine the target story voice and output the target story voice.

2. The method according to claim 1, characterized in that The step of performing story association processing based on the target nursing video and the story association instruction using a nursing processing large model to obtain target association story content includes: Based on the target care video, the target person's age is identified and processed to obtain the target person's age; Based on the target person's age, the story association instruction and the target nursing video, story association prompt words are generated, and the story association processing is performed based on the nursing processing model using the story association prompt words to obtain the target association story content.

3. The method according to claim 2, characterized in that The generating of story association prompt words based on the target person's age, the story association instruction, and the target nursing video includes: Determining preset story association prompt information corresponding to the age of the target person, and determining a story element extraction rule for the target nursing video based on the story association instruction; Story association prompt words are generated based on the preset story association prompt information, the story element extraction rules and the target nursing video.

4. The method according to claim 2, characterized in that The method of using the story association prompt words to perform story association processing based on the nursing processing model to obtain target association story content includes: Inputting the story association prompt words and the target care video into the care processing model; The target nursing video is subjected to story material recognition processing by the nursing processing macromodel to obtain story material data, the story material data is subjected to story element extraction processing by the nursing processing macromodel to obtain story association element information, and the target association story content is obtained by performing story association processing based on preset story association prompt information and story association element information by the nursing processing macromodel; The target associative story content is outputted through the nursing processing model.

5. The method according to claim 4, characterized in that The step of performing story association processing based on the preset story association prompt information and the story association element information by the nursing processing large model to obtain target association story content includes: The nursing processing model determines the target story style based on the preset story association prompt information, determines the target story framework based on the story association element information, and performs associative reasoning on the story framework based on the target story style to obtain the target associative story content.

6. A nursing treatment method, characterized in that: Applied to intelligent nursing equipment, the method includes: Collecting story association voice for family care scenarios, and generating story association instructions based on the story association voice; Collecting a target nursing video based on the story association instruction, sending the story association instruction and the target nursing video to a server, wherein the story association instruction and the target nursing video are used by the server to perform story association processing based on a nursing processing large model to obtain target association story content; receiving the target associative story content sent by the server; A target story voice is determined based on the target associative story content, and the target story voice is output.

7. A nursing treatment device, characterized in that: Applied to a server, the device includes: a data acquisition module for acquiring a story association instruction sent by a smart nursing device, and acquiring a target nursing video collected by the smart nursing device based on the story association instruction, wherein the story association instruction is generated by the smart nursing device based on the story association voice collected for a family nursing scenario; A story association module is used to perform story association processing based on the target nursing video and the story association instruction using a nursing processing large model to obtain target association story content; The data sending module is used to send the target associative story content to the smart nursing device, and the target associative story content is used by the smart nursing device to determine the target story voice and output the target story voice.

8. A nursing treatment device, characterized in that: Applied to intelligent nursing equipment, the device includes: An instruction generation module, configured to collect story association voices for family care scenarios and generate story association instructions based on the story association voices; A data sending module is used to collect a target nursing video based on the story association instruction, and send the story association instruction and the target nursing video to a server, where the story association instruction and the target nursing video are used by the server to perform story association processing based on a nursing processing large model to obtain target association story content; A data receiving module, configured to receive the target associative story content sent by the server; A data output module is used to determine a target story voice based on the target associative story content, and output the target story voice.

9. A computer storage medium, characterized in that The computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 5 or 6.

10. An electronic device, characterized in that: include: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method according to any one of claims 1 to 5 or 6.

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