Control method and device of intelligent toy, electronic equipment and storage medium

Abstract

The application provides a control method of an intelligent toy, which comprises: acquiring current image data when the intelligent toy is in a feedable state; performing image recognition processing on the current image data to determine the type of target feed food in the current image; determining whether the type of the target feed food matches the type of required feed food in a feeding stage of the intelligent toy based on the type of the target feed food, different feeding stages corresponding to different types of required feed food; and controlling the intelligent toy to perform feeding interaction with a user if the type of the target feed food matches the type of required feed food in the feeding stage of the intelligent toy. The application additionally increases the interactivity between the user and the companion toy through the interaction event of feeding the intelligent toy, increases the interestingness of the companion process, and improves the companion experience.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence, and more particularly to a control method, device, electronic device, and storage medium for an intelligent toy. Background Technology

[0002] Current smart toys offer children storytelling abilities and simple voice command interaction, imparting knowledge during the interaction. However, because these smart toys rely on simple voice command interaction and are based on a fixed database, they output fixed content corresponding to the voice commands. Their functionality is relatively limited. Since children grow and their needs for smart toys vary at different developmental stages, toys based on fixed databases do not maintain their appeal for long. Therefore, existing smart toys primarily rely on fixed databases and output fixed content corresponding to voice commands, failing to dynamically adjust their output according to the child's development. Furthermore, their interaction is limited to question-and-answer formats, resulting in a simplistic interaction method and a poor companionship experience. Summary of the Invention

[0003] This invention provides a control method for smart toys, aiming to solve the problem that existing smart toys cannot dynamically adjust their output according to a child's growth, only interact through question-and-answer sessions, resulting in a limited interaction method and a poor companionship experience. This invention adds extra interactivity between the user and the toy by incorporating interactive events related to feeding the smart toy, increasing the fun of the companionship process and improving the overall companionship experience.

[0004] In a first aspect, embodiments of the present invention provide a control method for an intelligent toy, the method comprising the following steps:

[0005] When the smart toy is in a feedable state, acquire the current image data;

[0006] The current image data is processed by image recognition to determine the type of target feeding food in the current image;

[0007] Based on the type of the target feeding food, determine whether the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy, with different feeding stages corresponding to different types of feeding food required;

[0008] If the type of the target food matches the type of food required during the feeding phase of the smart toy, then the smart toy is controlled to interact with the user during feeding.

[0009] Optionally, before acquiring the current image data when the smart toy is in a feedable state, the method further includes:

[0010] When the smart toy is activated by the user, it is determined whether the user's intention is a feeding intention;

[0011] When the user's intention is to feed, determine whether the smart toy is in a feedable state.

[0012] Optionally, when the smart toy is activated by the user, determining whether the user's intention is a feeding intention includes:

[0013] When the smart toy is activated by the user, it acquires the user's voice data;

[0014] Perform semantic recognition on the speech data to obtain semantic recognition results;

[0015] Based on the semantic recognition results, it is determined whether the user's intent is a feeding intent.

[0016] Optionally, determining whether the smart toy is in a feedable state when the user's intention is to feed it includes:

[0017] When the user's intention is to feed the smart toy, the daily feeding data of the smart toy is obtained; based on the daily feeding data of the smart toy, it is determined whether the smart toy is in a feedable state.

[0018] Optionally, the daily feeding data includes the number of feedings and the feeding interval. Determining whether the smart toy is in a feedable state based on the daily feeding data includes:

[0019] Based on the number of times the smart toy is fed that day, it is determined whether the smart toy is in a feedable state.

[0020] Based on the feeding interval of the smart toy, determine whether the smart toy is in a feedable state.

[0021] Optionally, before determining whether the type of the target feeding food matches the type of feeding food required during the feeding phase of the smart toy, the process includes:

[0022] Get the current growth value of the smart toy;

[0023] Based on the current growth value, the feeding stage of the smart toy is determined, and different growth values ​​correspond to different feeding stages;

[0024] Based on the feeding stages of the smart toy, the type of food required to be fed during the feeding stages of the smart toy is determined.

[0025] Optionally, if the type of the target feeding food matches the type of feeding food required during the feeding phase of the smart toy, then controlling the smart toy to interact with the user during feeding includes:

[0026] If the type of the target food matches the type of food required in the feeding stage of the smart toy, obtain the growth value of the target food type.

[0027] Based on the growth value of the target feeding food type, the smart toy is controlled to increase the growth value accordingly, and the smart toy is controlled to output knowledge data about the target feeding food type.

[0028] Secondly, embodiments of the present invention also provide a control device for a smart toy, the control device for the smart toy comprising:

[0029] The first acquisition module is used to acquire current image data when the smart toy is in a feedable state;

[0030] The first determining module is used to perform image recognition processing on the current image data to determine the type of target feeding food in the current image;

[0031] The second determining module is used to determine whether the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy, based on the type of the target feeding food; different feeding stages correspond to different types of feeding food.

[0032] The control module is used to control the smart toy to interact with the user for feeding if the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy.

[0033] Thirdly, embodiments of the present invention provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps in the control method for the intelligent toy provided in the embodiments of the present invention.

[0034] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in the control method for the intelligent toy provided in the embodiments of the present invention.

[0035] In this embodiment of the invention, when the smart toy is in a feedable state, current image data is acquired; image recognition processing is performed on the current image data to determine the type of target food in the current image; based on the type of target food, it is determined whether the type of target food matches the type of food required in the feeding stage of the smart toy, with different feeding stages corresponding to different types of required food; if the type of target food matches the type of food required in the feeding stage of the smart toy, then the smart toy is controlled to interact with the user during feeding. This invention adds extra interactivity between the user and the companion toy through the interactive event of feeding the smart toy, increasing the fun of the companionship process and improving the companionship experience. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. 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 creative effort.

[0037] Figure 1 This is a flowchart of a control method for an intelligent toy provided in an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of the structure of a control device for an intelligent toy provided in an embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] like Figure 1 As shown, Figure 1 This is a flowchart of a control method for an intelligent toy provided in an embodiment of the present invention. The control method for the intelligent toy includes the following steps:

[0042] 101. When the smart toy is in a feedable state, acquire the current image data.

[0043] In this embodiment of the invention, the control method for the smart toy can be applied to a server, with a communication connection between the server and the smart toy. The smart toy includes a voice acquisition device and an image acquisition device. The voice acquisition device is used to acquire voice data, and the image acquisition device is used to acquire image data. When using the smart toy for the first time, the user can set user information, including the user's name, age, hobbies, etc.; the user can also set a wake-up word, such as "Hello, Little One" or "Hello, Little Bean"; or a special title can be set, for example, the user's special title can be set as "Little Master," and the smart toy can address the user as "Little Master" when the user interacts with the smart toy.

[0044] The users mentioned above can be understood as users bound to the smart toy.

[0045] The aforementioned feedable state can be understood as the state in which a smart toy can accept food or be fed.

[0046] The aforementioned current image data was obtained in real time by an image acquisition device. This current image data includes images of the user being fed.

[0047] 102. Perform image recognition processing on the current image data to determine the type of target feeding food in the current image.

[0048] In this embodiment of the invention, the image recognition described above can be understood as the process of analyzing image data and identifying the type of food being fed in the image. Image recognition can be performed on the user's current image data using an image recognition model. This image recognition model is obtained by training an untrained image recognition model using an image dataset. The image dataset includes a large number of food images and corresponding food annotation data. The food annotation data can be information that classifies and describes the food, such as food type, food knowledge, etc. The untrained image recognition model can be an image recognition model built based on deep learning or machine learning, such as ResNet, AlexNet, etc. Specifically, the untrained image recognition model is trained using a large number of images and corresponding food annotation data. During training, the parameters of the image recognition model are adjusted using a minimum loss function. After training, a trained image recognition model is obtained. This training can be supervised training, which uses a set of known labeled data to train the model. By optimizing the model parameters, the model can predict the label of new data or make decisions based on the characteristics of existing data. The loss function measures the difference between the model's prediction and the actual result, and can be a mean squared error loss function, a cross-entropy loss function, etc.

[0049] The types of food mentioned above include any one of the following food types: fruits, vegetables, staple foods, etc.

[0050] Furthermore, the current image data is processed using an image recognition model to obtain image recognition results. Based on these results, the type of target food being fed in the current image is determined. These image recognition results include food types such as fruits and vegetables; fruit types include apples and bananas, and vegetable types include cabbage and radishes.

[0051] In one possible embodiment, if the image recognition result is an apple, apples belong to the fruit type, and the type of the target feeding food in the current image is determined to be the fruit type; if the image recognition result is cabbage, cabbage belongs to the vegetable type, and the type of the target feeding food in the current image is determined to be the vegetable type, and so on.

[0052] 103. Based on the type of target feeding food, determine whether the type of target feeding food matches the type of feeding food required in the feeding stage of the smart toy.

[0053] In this embodiment of the invention, different feeding stages correspond to different types of food that need to be fed.

[0054] Furthermore, after determining the type of food to be fed, the current growth value of the smart toy can be obtained. Based on the correspondence between the growth value and the feeding stage of the smart toy, the feeding stage of the smart toy is determined, thereby determining the type of food required in the feeding stage. The type of food to be fed is then matched with the type of food required in the feeding stage of the smart toy to determine whether the type of food to be fed matches the type of food required in the feeding stage of the smart toy. The different growth values ​​mentioned above correspond to different feeding stages. It can be understood that the first growth value of the smart toy corresponds to the first feeding stage, the second growth value of the smart toy corresponds to the second feeding stage, the third growth value of the smart toy corresponds to the third feeding stage, and so on. The type of food required in the first feeding stage can be fruit, the type of food required in the second feeding stage can be vegetables, and the type of food required in the third feeding stage can be staple food.

[0055] In one possible embodiment, when the target food type is fruit, and the type of food the smart toy currently needs to be fed is also fruit, then it is determined that the type of the target food matches the type of food needed in the feeding phase of the smart toy; when the target food type is vegetable, and the type of food the smart toy currently needs to be fed is also vegetable, then it is determined that the type of the target food matches the type of food needed in the feeding phase of the smart toy.

[0056] In another possible embodiment, if the target food type is fruit and the current required food type for the smart toy is vegetable, then the target food type does not match the required food type for the smart toy's feeding stage. The smart toy can then prompt the user via voice that the food is incompatible and refuse to feed the user.

[0057] 104. If the type of food to be fed matches the type of food required during the feeding phase of the smart toy, then control the smart toy to interact with the user during feeding.

[0058] In this embodiment of the invention, when the type of the target feeding food matches the type of feeding food required during the feeding phase of the smart toy, the smart toy is controlled to interact with the user during feeding.

[0059] The aforementioned feeding interaction can be understood as a way for smart toys to interact with users through virtual feeding. For example, smart toys can perform virtual feeding actions, and after successful feeding, the system can thank the user for feeding through preset voice messages, or provide knowledge data about the type of food fed after feeding is completed.

[0060] The knowledge data on the above-mentioned types of feeding foods includes food names, nutritional components, effects, and methods of consumption.

[0061] In one possible embodiment, when the target food is an apple (a type of fruit), relevant information about apples can be output via voice, such as, "Apples are plants of the genus Malus in the family Rosaceae. Apple fruits are rich in minerals and vitamins. The nutrients in apples are highly soluble and easily absorbed by the human body. Apples contain elements such as copper, iodine, manganese, zinc, and potassium, and have effects such as lowering cholesterol, calming the nerves and promoting sleep, and relieving fatigue." By providing knowledge about food, the user's interest in food can be increased, while also enhancing the companionship experience.

[0062] In this embodiment of the invention, when the smart toy is in a feedable state, current image data is acquired; image recognition processing is performed on the current image data to determine the type of target food in the current image; based on the type of target food, it is determined whether the type of target food matches the type of food required in the feeding stage of the smart toy, with different feeding stages corresponding to different types of required food; if the type of target food matches the type of food required in the feeding stage of the smart toy, then the smart toy is controlled to interact with the user during feeding. This invention adds extra interactivity between the user and the companion toy through the interactive event of feeding the smart toy, increasing the fun of the companionship process and improving the companionship experience.

[0063] It is understood that in the specific implementation of this application, data such as voice data, image data, knowledge data, and user data are involved. When the embodiments in this application are applied to specific products or technologies, user permission or consent is required. Furthermore, the collection, use, and processing of related data, as well as the training, deployment, and invocation of algorithm models, must comply with the relevant laws, regulations, and standards of the relevant countries and regions.

[0064] Optionally, before acquiring the current image data when the smart toy is in a feedable state, when the smart toy is woken up by the user, it is determined whether the user's intention is a feeding intention; if the user's intention is a feeding intention, it is determined whether the smart toy is in a feedable state.

[0065] In this embodiment of the invention, when the smart toy is used for the first time, the user can set a wake-up word, such as "Hello, Little One" or "Hello, Little Bean." The wake-up function can be understood as the process by which the user activates the smart toy in a specific way. The user can wake up the smart toy using the set wake-up word, or through touch wake-up operations or other wake-up methods.

[0066] The users mentioned above can be understood as users bound to the smart toy.

[0067] The user intent mentioned above can be understood as the purpose the user wants to express or the action they want to perform. User intent can be feeding intent, question-and-answer intent, etc.

[0068] The feeding intent mentioned above can be understood as the user's intention to feed the smart toy. The question-and-answer intent mentioned above can be understood as the user's intention to ask and answer questions with the smart toy.

[0069] The aforementioned feedable state can be understood as the state in which a smart toy can accept food or be fed.

[0070] In one possible embodiment, when a user wakes up the smart toy via voice, the voice acquisition device can acquire the user's voice data in real time, and perform intent recognition on the voice data to determine whether the user's intent is to feed the toy. When a user wakes up the smart toy via touch, the image acquisition device can acquire the user's current image data in real time, perform image recognition on the current image data, and determine whether the user's intent is to feed the toy based on the image recognition result. The intent recognition described above can be understood as the process of judging the purpose or intent of the user's voice data. The image recognition described above can be understood as the process of recognizing and analyzing image data to identify whether there is a feeding food type in the current image.

[0071] Optionally, in the step of determining whether the user's intention is a feeding intention when the smart toy is woken up by the user, when the smart toy is woken up by the user, the user's voice data is acquired; semantic recognition is performed on the voice data to obtain the semantic recognition result; and based on the semantic recognition result, it is determined whether the user's intention is a feeding intention.

[0072] In this embodiment of the invention, the user's voice data is collected by the voice acquisition device of the smart toy. The voice data may include phrases such as "Can I give you something to eat?" or "I want to give you something to eat."

[0073] The aforementioned semantic recognition can be understood as the process of semantic recognition of speech data. Natural Language Processing (NLP) technology can be used to perform semantic recognition processing on speech data. NLP technology enables machines to understand, interpret, and generate human language, achieving effective communication between humans and machines, and allowing computers to perform tasks such as language translation, sentiment analysis, and text summarization.

[0074] The semantic recognition results described above are the understanding obtained by analyzing speech data using natural language processing technology. These results include the user's intent expressed in their speech. For example, if a user says, "Can I give you something to eat?", the semantic recognition result is an intent to feed the smart toy; while if it's "What day of the week is it?", the semantic recognition result is an intent to ask and answer questions with the smart toy, and so on.

[0075] In one possible embodiment, when the wake word of the smart toy is "Hello, little one", when the user says to the smart toy, "Hello, little one, I want to feed you something", the smart toy is awakened by the wake word "Hello, little one". The smart toy collects the user's voice data, performs semantic recognition on the user's voice data "I want to feed you something", obtains the semantic recognition result of "intention to interact with the smart toy for feeding", and determines that the user's intention is a feeding intention.

[0076] In another possible embodiment, when the wake word of the smart toy is "Hello, Little Bean", when the user says to the smart toy, "Hello, Little Bean, what day of the week is it today", the smart toy is awakened by the wake word "Hello, Little Bean", and then semantic recognition is performed on the user's voice data "What day of the week is it today", to obtain the semantic recognition result of "the intention to interact with the smart toy in a question and answer manner", and the user's intention is determined to be a question and answer intention.

[0077] Optionally, in the step of determining whether the smart toy is in a feedable state when the user's intention is to feed, the daily feeding data of the smart toy is obtained; and based on the daily feeding data of the smart toy, it is determined whether the smart toy is in a feedable state.

[0078] In this embodiment of the invention, when the user's intention is to feed the food, the daily feeding data of the smart toy can be obtained. This feeding data can be related data about the food recorded by the smart toy, such as the number of feedings corresponding to the food type and the feeding interval.

[0079] Furthermore, the feeding frequency corresponding to the type of food provided by the smart toy can be used to determine whether the smart toy is in a feedable state; the feeding interval can also be used to determine whether the smart toy is in a feedable state.

[0080] The aforementioned feedable state refers to the state in which the intelligent toy can accept food or be fed.

[0081] Optionally, the daily feeding data includes the number of feedings and the feeding interval. In the step of determining whether the smart toy is in a feedable state based on the daily feeding data of the smart toy, the smart toy can be determined based on the number of feedings of the smart toy in the day; or based on the feeding interval of the smart toy.

[0082] In this embodiment of the invention, the aforementioned number of feedings per day can be understood as the number of times the smart toy is fed during a day. Specifically, the number of times the user interacts with the smart toy to feed it in a day is recorded, and this recorded number of feeding interactions is the number of feedings per day. For example, if the number of times the user interacts with the smart toy to feed it in a day is m, then the number of feedings per day is m; if the number of times the user interacts with the smart toy to feed it in a day is n, then the number of feedings per day is n.

[0083] The feeding interval mentioned above can be understood as the length of time between two feedings.

[0084] It should be noted that the smart toy has a daily feeding limit for each type of food. When the number of feedings for a given food type is below the daily limit, the smart toy is considered feedable; when the number of feedings for a given food type is above the daily limit, the smart toy is considered unfeedable. The smart toy also has a feeding interval threshold. If the feeding interval for a given food type is below the daily limit but reaches the threshold, the smart toy is considered feedable; if the feeding interval is below the threshold, the smart toy is considered unfeedable.

[0085] It should be noted that the smart toy also features voice and / or physical prompts to indicate refusal to be fed. When the smart toy is in a non-feedable state, it can provide voice and / or physical prompts. Voice prompts could include phrases like, "I'm full, I can't eat anymore today, or I'll become a little fatso," or "You need a balanced diet every day, don't eat too much!" Physical prompts could include shaking your head or waving your hands.

[0086] In one possible embodiment, the smart toy is set to feed fruit a certain number of times (M) and have a feeding interval of H. When the target feeding type of the smart toy is fruit, the daily feeding number of fruit is N. When the daily feeding number of fruit (N) is less than the daily feeding number of fruit (M) and the feeding interval reaches the feeding interval H, the smart toy is determined to be in a feedable state. When the daily feeding number of fruit (N) is less than the daily feeding number of fruit (M) and the feeding interval does not reach the feeding interval H, the smart toy is determined to be in a non-feedable state.

[0087] It should be noted that different food types have a feeding limit. For example, the number of times fruit can be fed can be set to 'a', vegetable to 'b', and staple food to 'c', etc. The feeding limit for each food type can be adjusted based on the increase in the smart toy's growth value.

[0088] Optionally, before determining whether the type of target food matches the type of food required in the feeding stage of the smart toy, the current growth value of the smart toy can be obtained; the feeding stage of the smart toy can be determined based on the current growth value; and the type of food required in the feeding stage of the smart toy can be determined based on the feeding stage of the smart toy.

[0089] In this embodiment of the invention, the different growth values ​​correspond to different feeding stages.

[0090] The current growth value of the aforementioned smart toy can be understood as the current growth value of the smart toy's interaction with the user. The growth value of the smart toy corresponds to the feeding stage of the smart toy.

[0091] The feeding stages of the aforementioned smart toys are determined based on the growth value of the smart toys, and different feeding stages correspond to different types of food.

[0092] The types of food mentioned above include fruits, vegetables, and staple foods.

[0093] Furthermore, after obtaining the current growth value of the smart toy, the feeding stage of the smart toy can be determined based on the correspondence between the growth value and the feeding stage. Combining the correspondence between the feeding stage and the type of food, the type of food required for the feeding stage of the smart toy can be determined.

[0094] The correspondence between the growth value and the feeding stage of the smart toy is a pre-set relationship by the system. Specifically, the first growth value corresponds to the first feeding stage, the second growth value corresponds to the second feeding stage, the third growth value corresponds to the third feeding stage, and so on. Among these, the third growth value is higher than the second growth value, and the second growth value is higher than the first growth value.

[0095] The correspondence between the feeding stages and the types of food mentioned above is a pre-set correspondence by the system. Specifically, the first feeding stage may correspond to the type of fruit, the second feeding stage to the type of vegetable, and the third feeding stage to the type of staple food, etc.

[0096] In one possible embodiment, when the smart toy's current growth value is a first growth value, the feeding stage is determined to be the first feeding stage based on the correspondence between the smart toy's growth value and its feeding stage. Furthermore, based on the correspondence between the feeding stage and the type of food, the type of food required for this feeding stage is determined to be fruit. When the smart toy's current growth value is a second growth value, the feeding stage is determined to be the second feeding stage based on the correspondence between the smart toy's growth value and its feeding stage. Furthermore, based on the correspondence between the feeding stage and the type of food, the type of food required for this feeding stage is determined to be vegetable. When the smart toy's current growth value is a third growth value, the feeding stage is determined to be the third feeding stage based on the correspondence between the smart toy's growth value and its feeding stage. Furthermore, based on the correspondence between the feeding stage and the type of food, the type of food required for this feeding stage is determined to be staple food. The aforementioned fruit types include apples and bananas; the aforementioned vegetable types include cabbage and radishes; and the aforementioned staple food types include rice and dumplings.

[0097] Optionally, in the step of controlling the smart toy to interact with the user for feeding if the type of the target food matches the type of food required in the feeding stage of the smart toy, the growth value of the target food type is obtained; based on the growth value of the target food type, the smart toy is controlled to increase the growth value accordingly, and the smart toy is controlled to output the knowledge data of the target food type.

[0098] In this embodiment of the invention, the growth value of the target type of feeding food can be understood as the increase in growth value corresponding to the type of feeding food.

[0099] Furthermore, based on the growth value increase corresponding to the type of food fed to the target user, the growth value of the smart toy can be controlled to increase accordingly. It is important to understand that the growth value increase corresponding to the food fed to the user corresponds to the growth value of the smart toy, and the growth value increase from feeding the food corresponds to the growth value increase from the smart toy.

[0100] In one possible embodiment, if the type of food fed is fruit, and the growth value corresponding to fruit is e, then the growth value of the smart toy is increased by +e; if the type of food fed is vegetables, and the growth value corresponding to vegetables is f, then the growth value of the smart toy is increased by +f, and so on.

[0101] The knowledge data on the types of food for the target feeding mentioned above includes food name, nutritional components, efficacy, and methods of consumption.

[0102] The above output can be understood as a pre-set output format by the system, specifically, it can be voice output. This voice output can be understood as the intelligent toy converting knowledge data about the type of food being fed to the target into playable voice information.

[0103] In one possible embodiment, when the target food is an apple (a fruit), relevant information about apples can be output via voice, such as, "Apples are plants of the genus Malus in the Rosaceae family. Apple fruits are rich in minerals and vitamins. The nutrients in apples are highly soluble and easily absorbed by the human body. Apples contain elements such as copper, iodine, manganese, zinc, and potassium, and have effects such as lowering cholesterol, calming the nerves and promoting sleep, and relieving fatigue." Similarly, when the target food is cabbage (a vegetable), relevant information about cabbage can be output via voice, such as, "Cabbage..." Vegetables are rich in water and vitamins. Cabbage has the effects of nourishing the stomach, promoting body fluid production, clearing heat, and relieving irritability. Mashing cabbage to extract its juice, then decocting it with lily bulbs and ophiopogon japonicus, can be effective for stomach pain caused by stomach yin deficiency. When the target food is rice, a staple food, information about rice can be output via voice, such as: "Rice is the most important of the five grains, and it is one of the main ingredients in people's daily diet. Rice is a food made by steaming or simmering rice with an appropriate amount of water. Rice can be seasoned with various flavors to provide the body with the necessary nutrients. It has the effects of relieving fatigue and strengthening the spleen and stomach."

[0104] It should be noted that when the growth value of the smart toy reaches the preset growth value for level upgrade, the smart toy's level can be upgraded. The growth value corresponds to the level of the smart toy. During each level upgrade, the smart toy can announce via voice, "Little master, I've grown a little more, and now I've learned ZZ skills." For example, when the smart toy's level is 0 and it upgrades to 1, it announces, "Little master, I've grown a little more, and now I can eat fruit. Please talk to me so I can learn more about you." When the smart toy's level is 1 and it upgrades to 2, it announces, "Little master, I've grown a little more, and now I can eat vegetables. I've already met my little master's family," and so on. This invention allows the growth value to increase with user interaction with the smart toy, enhancing its fun factor.

[0105] like Figure 2 As shown, an embodiment of the present invention provides a control device for a smart toy, the control device for the smart toy comprising:

[0106] The first acquisition module 201 is used to acquire current image data when the smart toy is in a feedable state;

[0107] The first determining module 202 is used to perform image recognition processing on the current image data to determine the type of target feeding food in the current image;

[0108] The second determining module 203 is used to determine whether the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy, based on the type of the target feeding food; different feeding stages correspond to different types of feeding food required.

[0109] The control module 204 is used to control the smart toy to interact with the user for feeding if the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy.

[0110] Optionally, the device further includes:

[0111] The third determining module is used to determine whether the user's intention is a feeding intention when the smart toy is woken up by the user.

[0112] The fourth determining module is used to determine whether the smart toy is in a feedable state when the user's intention is to feed.

[0113] Optionally, the third determining module includes:

[0114] The first acquisition submodule is used to acquire the user's voice data when the smart toy is woken up by the user;

[0115] The semantic recognition submodule is used to perform semantic recognition on the voice data to obtain semantic recognition results; based on the semantic recognition results, it is determined whether the user's intent is a feeding intent.

[0116] Optionally, the fourth determining module includes:

[0117] The second acquisition submodule is used to acquire the daily feeding data of the smart toy when the user's intention is to feed.

[0118] The first determining submodule is used to determine whether the smart toy is in a feedable state based on the daily feeding data of the smart toy.

[0119] Optionally, the first determining submodule includes:

[0120] The first determining unit is used to determine whether the smart toy is in a feedable state based on the number of times the smart toy is fed that day.

[0121] The second determining unit is used to determine whether the smart toy is in a feedable state based on the feeding interval of the smart toy.

[0122] Optionally, the device further includes:

[0123] The second acquisition module is used to acquire the current growth value of the smart toy;

[0124] The fifth determining module is used to determine the feeding stage of the smart toy based on the current growth value, wherein different growth values ​​correspond to different feeding stages;

[0125] The sixth determining module is used to determine the type of food required for feeding the smart toy during its feeding stage, based on the feeding stage of the smart toy.

[0126] Optionally, the control module 204 includes:

[0127] The third acquisition submodule is used to acquire the growth value of the target feeding food type if the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy.

[0128] The control submodule is used to control the smart toy to increase the growth value correspondingly based on the growth value of the target feeding food type, and to control the smart toy to output knowledge data about the type of the target feeding food.

[0129] like Figure 3 As shown, this embodiment of the invention also provides an electronic device, including a processor, which can execute any of the above-described control methods for intelligent toys.

[0130] Specifically, it includes a processor 301 and a memory 302, as well as a computer program stored in the memory 302 and capable of running on the processor 301, which executes the control method for the intelligent toy, wherein:

[0131] The processor 301 executes the calculator program for the control method of the intelligent toy stored in the memory 302, and performs the following steps:

[0132] When the smart toy is in a feedable state, acquire the current image data;

[0133] The current image data is processed by image recognition to determine the type of target feeding food in the current image;

[0134] Based on the type of the target feeding food, determine whether the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy, with different feeding stages corresponding to different types of feeding food required;

[0135] If the type of the target food matches the type of food required during the feeding phase of the smart toy, then the smart toy is controlled to interact with the user during feeding.

[0136] Optionally, the method executed by the processor 301 before acquiring the current image data when the smart toy is in a feedable state further includes:

[0137] When the smart toy is activated by the user, it is determined whether the user's intention is a feeding intention;

[0138] When the user's intention is to feed, determine whether the smart toy is in a feedable state.

[0139] Optionally, the step of determining whether the user's intention is a feeding intention when the smart toy is awakened by the user, performed by the processor 301, includes:

[0140] When the smart toy is activated by the user, it acquires the user's voice data;

[0141] Perform semantic recognition on the speech data to obtain semantic recognition results;

[0142] Based on the semantic recognition results, it is determined whether the user's intent is a feeding intent.

[0143] Optionally, the step of determining whether the smart toy is in a feedable state when the user's intention is a feeding intention, performed by the processor 301, includes:

[0144] When the user's intention is to feed the smart toy, the daily feeding data of the smart toy is obtained; based on the daily feeding data of the smart toy, it is determined whether the smart toy is in a feedable state.

[0145] Optionally, the daily feeding data includes the number of feedings and the feeding interval. The processor 301 executes the daily feeding data based on the smart toy to determine whether the smart toy is in a feedable state, including:

[0146] Based on the number of times the smart toy is fed that day, determine whether the smart toy is in a feedable state;

[0147] Based on the feeding interval of the smart toy, determine whether the smart toy is in a feedable state.

[0148] Optionally, before determining whether the type of the target feeding food matches the type of feeding food required during the feeding phase of the smart toy, the method executed by the processor 301 further includes:

[0149] Get the current growth value of the smart toy;

[0150] Based on the current growth value, the feeding stage of the smart toy is determined, and different growth values ​​correspond to different feeding stages;

[0151] Based on the feeding stages of the smart toy, the type of food required to be fed during the feeding stages of the smart toy is determined.

[0152] Optionally, the step of processor 301 executing the statement that if the type of the target feeding food matches the type of feeding food required in the feeding phase of the smart toy, then controlling the smart toy to interact with the user for feeding includes:

[0153] If the type of the target food matches the type of food required in the feeding stage of the smart toy, obtain the growth value of the target food type.

[0154] Based on the growth value of the target feeding food type, the smart toy is controlled to increase the growth value accordingly, and the smart toy is controlled to output knowledge data about the target feeding food type.

[0155] This invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the intelligent toy control method provided in this invention and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0156] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0157] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A control method for an intelligent toy, characterized in that, The method includes the following steps: When the smart toy is in a feedable state, acquire the current image data; The current image data is processed by image recognition to determine the type of target feeding food in the current image; Based on the type of the target feeding food, determine whether the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy, with different feeding stages corresponding to different types of feeding food required; If the type of the target food matches the type of food required during the feeding phase of the smart toy, then the smart toy is controlled to interact with the user during feeding.

2. The control method for the intelligent toy as described in claim 1, characterized in that, Before acquiring the current image data when the smart toy is in a feedable state, the method further includes: When the smart toy is activated by the user, it is determined whether the user's intention is a feeding intention; When the user's intention is to feed, determine whether the smart toy is in a feedable state.

3. The control method for the intelligent toy as described in claim 2, characterized in that, When the smart toy is activated by the user, determining whether the user's intention is a feeding intention includes: When the smart toy is activated by the user, it acquires the user's voice data; Perform semantic recognition on the speech data to obtain semantic recognition results; Based on the semantic recognition results, it is determined whether the user's intent is a feeding intent.

4. The control method for the intelligent toy as described in claim 2, characterized in that, When the user's intention is to feed the toy, determining whether the smart toy is in a feedable state includes: When the user's intention is to feed, obtain the daily feeding data of the smart toy; Based on the daily feeding data of the smart toy, it is determined whether the smart toy is in a feedable state.

5. The control method for the intelligent toy as described in claim 4, characterized in that, The daily feeding data includes the number of feedings and the feeding interval. Determining whether the smart toy is in a feedable state based on the daily feeding data includes: Based on the number of times the smart toy is fed that day, determine whether the smart toy is in a feedable state; Based on the feeding interval of the smart toy, determine whether the smart toy is in a feedable state.

6. The control method for the intelligent toy as described in claim 5, characterized in that, Before determining whether the type of the target feeding food matches the type of food required during the feeding phase of the smart toy, the process includes: Get the current growth value of the smart toy; Based on the current growth value, the feeding stage of the smart toy is determined, and different growth values ​​correspond to different feeding stages; Based on the feeding stages of the smart toy, the type of food required to be fed during the feeding stages of the smart toy is determined.

7. The control method for the intelligent toy as described in claim 6, characterized in that, If the type of the target feeding food matches the type of feeding food required during the feeding phase of the smart toy, then controlling the smart toy to interact with the user during feeding includes: If the type of the target food matches the type of food required in the feeding stage of the smart toy, obtain the growth value of the target food type. Based on the growth value of the target feeding food type, the smart toy is controlled to increase the growth value accordingly, and the smart toy is controlled to output knowledge data about the target feeding food type.

8. A control device for an intelligent toy, characterized in that, The control device for the intelligent toy includes: The first acquisition module is used to acquire current image data when the smart toy is in a feedable state; The first determining module is used to perform image recognition processing on the current image data to determine the type of target feeding food in the current image; The second determining module determines whether the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy, based on the type of target feeding food. Different feeding stages correspond to different types of feeding food. The control module is used to control the smart toy to interact with the user for feeding if the type of the target feeding food matches the type of feeding food required in the feeding stage of the smart toy.

9. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the control method for the intelligent toy as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the control method for the intelligent toy as described in any one of claims 1 to 7.

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