CN111241292A - Menu recommendation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application provides a menu recommendation method and device, electronic equipment and a storage medium, and belongs to the field of smart home. The method comprises the steps of collecting voice data in a current scene; if the voice data contains preset keywords, acquiring prestored user characteristics; determining target menu attribute information according to the preset keywords and the user characteristics; and determining a target menu to be recommended according to the target menu attribute information and a menu knowledge map stored in advance, wherein the menu knowledge map comprises the corresponding relation between the menu and the menu attribute information. By adopting the technical scheme provided by the application, the user experience can be improved.
Description
Technical Field
The application relates to the field of smart home, in particular to a menu recommendation method and device, an electronic device and a storage medium.
Background
With the development of network technology, intelligent kitchen appliances such as intelligent electric rice cookers and intelligent pressure cookers can have the function of recommending recipes for users.
In the related art, the intelligent kitchen ware equipment can recommend recipes for the user in a mode of carrying out multiple voice interactions with the user, and the specific processing process comprises the following steps: the user inputs a wake-up voice command, and after the wake-up voice command is detected, the intelligent kitchen tool device can verify the user, wherein the wake-up voice command is used for example for the classmates, hey Siri. After the verification is passed, the user needs to input a voice instruction of a preset sentence pattern, the voice instruction of the preset sentence pattern can be 'recommend a dish', and then the intelligent kitchen tool device can output a plurality of preset questions in sequence, wherein the preset questions comprise 'please say the category of the dish that you want to eat', 'please say the taste of the dish that you want to eat'. After the information fed back by the user aiming at the plurality of preset problems is obtained, the intelligent kitchen ware device can determine the menu recommended for the user in the plurality of pre-stored menus according to the information fed back by the user, and output the menu.
However, the user needs to perform voice interaction with the intelligent kitchen equipment for multiple times before acquiring the recommended menu, which results in poor user experience.
Disclosure of Invention
An object of the embodiments of the present application is to provide a menu recommendation method, an apparatus, an electronic device, and a storage medium, so as to solve the problem of poor user experience. The specific technical scheme is as follows:
in a first aspect, a menu recommendation method is provided, the method including:
collecting voice data in a current scene;
if the voice data contains preset keywords, acquiring prestored user characteristics;
determining target menu attribute information according to the preset keywords and the user characteristics;
and determining a target menu to be recommended according to the target menu attribute information and a menu knowledge map stored in advance, wherein the menu knowledge map comprises the corresponding relation between the menu and the menu attribute information.
Optionally, after the acquiring the voice data in the current scene, the method further includes:
performing user verification based on the voice data;
and if the user verification is successful, determining whether the voice data contains preset keywords.
Optionally, the performing user verification based on the voice data includes:
extracting a plurality of voiceprint features from the voice data;
establishing a target voiceprint characteristic vector according to the characteristic values of the various voiceprint characteristics;
and if the voiceprint feature vector matched with the target voiceprint feature vector exists in the pre-stored corresponding relationship between the user identifier and the voiceprint feature vector, determining that the user verification is successful.
Optionally, the method further includes:
if the user verification is successful, determining a user identifier corresponding to the target voiceprint feature vector;
the acquiring of the pre-stored user characteristics includes:
and determining the user characteristics corresponding to the user identification according to the corresponding relation between the pre-stored user identification and the user characteristics.
Optionally, the determining whether the voice data includes a preset keyword includes:
if the voiceprint features comprise dialect voiceprint features, determining semantic information corresponding to the dialect voiceprint features according to the dialect voiceprint features, the prestored corresponding relationship between the dialect voiceprint features and the semantic information to obtain the semantic information contained in the voice data;
and determining whether the voice data contains preset keywords or not based on semantic information contained in the voice data.
Optionally, the determining, according to the preset keyword and the user characteristic, target recipe attribute information includes:
and determining target menu attribute information according to the preset keywords, the user characteristics and the dialect voiceprint characteristics, wherein the target menu attribute information comprises at least one of taste preference information and cooking modes.
Optionally, the method further includes:
if the user verification is successful, determining a preset user characteristic corresponding to the voiceprint characteristic according to the voiceprint characteristic, a pre-stored correspondence of the voiceprint characteristic and the preset user characteristic;
and if the preset user characteristics do not exist in the user characteristics of the user successfully verified, correspondingly storing the user and the preset user characteristics to update the user portrait of the user.
Optionally, the method further includes:
and if the user refuses the recommendation operation on the target menu is detected, inputting the attribute information of the target menu and the target menu into the menu knowledge graph to redetermine the target menu.
In a second aspect, there is provided a menu recommendation apparatus, the apparatus comprising:
the acquisition module is used for acquiring voice data in the current scene;
the acquisition module is used for acquiring the pre-stored user characteristics when the voice data contains preset keywords;
the first determining module is used for determining target menu attribute information according to the preset keywords and the user characteristics;
and the second determination module is used for determining a target menu to be recommended according to the target menu attribute information and a pre-stored menu knowledge map, wherein the menu knowledge map comprises a corresponding relation between the menu and the menu attribute information.
Optionally, the apparatus further comprises:
the user verification module is used for verifying the user based on the voice data;
and the detection module is used for determining whether the voice data contains preset keywords or not when the user successfully checks.
Optionally, the user verification module includes:
the extraction submodule is used for extracting a plurality of voiceprint characteristics from the voice data;
the establishing submodule is used for establishing a target voiceprint characteristic vector according to the characteristic values of the various voiceprint characteristics;
and the first determining submodule is used for determining that the user verification is successful when the voiceprint feature vector matched with the target voiceprint feature vector exists in the corresponding relation between the pre-stored user identification and the voiceprint feature vector.
Optionally, the determining sub-module is further configured to determine, when the user verification is successful, a user identifier corresponding to the target voiceprint feature vector;
the obtaining module is further configured to determine, according to a correspondence between a pre-stored user identifier and a user characteristic, a user characteristic corresponding to the user identifier.
Optionally, the detection module includes:
the second determining submodule is used for determining semantic information corresponding to the dialect voiceprint features according to the corresponding relation among the dialect voiceprint features, prestored dialect voiceprint features and semantic information when the voiceprint features contain the dialect voiceprint features, so as to obtain the semantic information contained in the voice data;
and the third determining submodule is used for determining whether the voice data contains preset keywords or not based on semantic information contained in the voice data.
Optionally, the first determining module is further configured to determine target recipe attribute information according to the preset keyword, the user characteristic, and the dialect voiceprint characteristic, where the target recipe attribute information includes at least one of taste preference information and a cooking manner.
Optionally, the apparatus further comprises:
the third determining module is used for determining the preset user characteristics corresponding to the voiceprint characteristics according to the voiceprint characteristics, the corresponding relation between the prestored voiceprint characteristics and the preset user characteristics when the user verification is successful;
and the updating module is used for correspondingly storing the user and the preset user characteristics when the preset user characteristics do not exist in the user characteristics of the user which is successfully verified so as to update the user portrait of the user.
Optionally, the second determining module is further configured to, when it is detected that the user rejects the recommendation operation for the target recipe, input the target recipe attribute information and the target recipe into the recipe knowledge graph to re-determine the target recipe.
In a third aspect, an electronic device is provided, which includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
a processor adapted to perform the method steps of any of the first aspects when executing a program stored in the memory.
In a fourth aspect, a computer-readable storage medium is provided, having stored thereon a computer program which, when being executed by a processor, carries out the method steps of any of the first aspects.
In a fifth aspect, there is provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform any of the above described recipe recommendation methods.
The embodiment of the application has the following beneficial effects:
the embodiment of the application provides a menu recommendation method and device, electronic equipment and a storage medium, wherein voice data in a current scene are collected; if the voice data contains preset keywords, acquiring prestored user characteristics; determining target menu attribute information according to preset keywords and user characteristics; and determining a target menu to be recommended according to the target menu attribute information and a menu knowledge map stored in advance, wherein the menu knowledge map comprises the corresponding relation between the menu and the menu attribute information. Under the condition that the collected voice data contain the preset keywords, the intelligent kitchen ware device automatically determines the target menu to be recommended according to the preset keywords and the user characteristics, so that the user does not need to perform voice interaction with the intelligent kitchen ware device for many times, and the user experience can be improved.
Of course, not all advantages described above need to be achieved at the same time in the practice of any one product or method of the present application.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flowchart of a menu recommendation method provided in an embodiment of the present application;
fig. 2 is a flowchart of another recipe recommendation method according to an embodiment of the present application;
fig. 3 is a flowchart of another recipe recommendation method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a menu recommendation device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiment of the application provides a menu recommendation method, which can be applied to intelligent kitchen ware equipment, wherein the intelligent kitchen ware equipment can have a data processing function, and the intelligent kitchen ware equipment can be used for intelligent electric rice cookers, intelligent ovens and the like.
A menu recommendation method provided in an embodiment of the present application will be described in detail below with reference to specific embodiments, as shown in fig. 1, the specific steps are as follows:
In the implementation, the intelligent kitchen ware equipment can be provided with an audio acquisition component, and the intelligent kitchen ware equipment can acquire the voice data in the current scene through the audio acquisition component.
And 102, if the voice data contain preset keywords, acquiring the pre-stored user characteristics.
The preset keywords can be names of dishes, names of cuisine, cooking modes, taste preference information and the like, the user characteristics can be gender, age, region, taste preference information and the like, and the taste preference information can be spicy, hot, light, salty, sweet and the like.
In implementation, the intelligent kitchen ware device can perform semantic analysis on the voice data to determine semantic information contained in the voice data, and if the semantic information contained in the voice data contains preset keywords, the intelligent kitchen ware device can acquire the pre-stored user characteristics. If the semantic information contained in the voice data does not contain the preset keywords, the intelligent kitchen tool equipment does not need to perform subsequent processing.
In the embodiment of the application, the intelligent kitchen ware equipment can acquire the pre-stored user characteristics in multiple ways, in a feasible implementation manner, the intelligent kitchen ware equipment can pre-store the general user characteristics, and the intelligent kitchen ware equipment can acquire the general user characteristics after determining that the voice data contains the preset keywords each time. In another possible implementation, the user characteristics of each registered user can be stored in the intelligent cookware device. Therefore, when the pre-stored user characteristics are acquired, the intelligent kitchen ware device can determine the user who sends the voice data and then acquire the user characteristics corresponding to the user, and the detailed processing process of the intelligent kitchen ware device will be described in detail later.
And 103, determining target menu attribute information according to preset keywords and user characteristics.
Wherein the recipe attribute information includes at least one of a name of a recipe, taste preference information, and a cooking method.
In an implementation, the smart cookware apparatus may determine the target recipe attribute information through a preset semantic analysis algorithm, such as standard Natural Language Processing (NLP), Convolutional Neural Networks (CNN), preset keywords, and user characteristics.
The embodiment of the application provides an implementation mode for determining target menu attribute information by intelligent kitchen ware equipment through a semantic analysis algorithm, preset keywords and user characteristics, wherein the implementation mode comprises the following steps:
the intelligent kitchen ware equipment can be used for storing the weight in advance aiming at each preset keyword and each user characteristic, and after the user characteristic is obtained, the intelligent kitchen ware equipment can perform fusion analysis on the preset keyword and the user characteristic according to the weight of the preset keyword and the weight of the user characteristic to obtain target menu attribute information.
For example, semantic information contained in the collected voice data is that "i want to eat shredded potatoes", wherein the preset keyword is shredded potatoes, the weight of the preset keyword "shredded potatoes" is 0.9, the user characteristic is taste preference information, the weight of sour in the taste preference information is 0.7, the weight of spicy is 0.1, the weight of salty is 0.1, and the weight of sweet is 0.2.
The intelligent kitchen ware equipment can perform fusion analysis on the preset keywords and the user characteristics according to the weight of the preset keywords and the weight of the user characteristics to obtain target menu attribute information, wherein the target menu attribute information is that the weight of shredded potatoes is 0.9, the weight of sour is 0.7, the weight of spicy is 0.1, the weight of salty is 0.1, and the weight of sweet is 0.2.
And step 104, determining a target menu to be recommended according to the attribute information of the target menu and a pre-stored menu knowledge graph.
The intelligent kitchen ware equipment can be stored with a menu knowledge graph in advance, and the menu knowledge graph comprises a corresponding relation between menus and menu attribute information.
In implementation, the intelligent kitchen tool device can input the target menu attribute information into the menu knowledge graph, and the menu corresponding to the target menu attribute information, namely the target menu to be recommended to the user, is determined through the menu knowledge graph. Then, the intelligent kitchen appliance can output the target menu.
In the embodiment of the application, the intelligent kitchen ware device determines the specific processing process of the target menu to be recommended through the target menu attribute information and the menu knowledge map, and any processing process of information matching based on the knowledge map in the related art can be referred to, and is not repeated here.
In the embodiment of the application, the intelligent kitchen ware equipment can acquire voice data in the current scene; if the voice data contains preset keywords, acquiring prestored user characteristics; determining target menu attribute information according to preset keywords and user characteristics; and determining a target menu to be recommended according to the target menu attribute information and a menu knowledge map stored in advance, wherein the menu knowledge map comprises the corresponding relation between the menu and the menu attribute information. Under the condition that the collected voice data contain the preset keywords, the intelligent kitchen ware device automatically determines the target menu to be recommended according to the preset keywords and the user characteristics, so that the user does not need to perform voice interaction with the intelligent kitchen ware device for many times, and the user experience can be improved.
In the related art, the menu is recommended in an interactive recognition mode, that is, the intelligent kitchen ware equipment needs to perform voice interaction with the user for multiple times before acquiring the recommended menu. The menu is recommended in a silent intelligent recognition mode, namely, the menu can be recommended without language interaction with the user, so that the voice interaction process can be simplified, and the disturbance of the interactive recognition mode on the normal communication of the user is avoided. Furthermore, the complexity of the process of acquiring the recommended menu by the user can be greatly reduced.
Optionally, after the intelligent kitchen ware device outputs the target menu, if the user dislikes the target menu, the intelligent kitchen ware device may also recommend the menu again, and the specific processing procedure includes: and if the user refuses the recommendation operation on the target menu is detected, inputting the attribute information of the target menu and the target menu into the menu knowledge map to re-determine the target menu.
In implementation, if the user does not like the target recipe, the user may perform a recommendation rejection operation, for example, the recommendation rejection operation may be clicking a preset button in the smart cookware device, and the recommendation rejection operation may also be outputting a voice instruction indicating that the recommendation is rejected.
After the intelligent kitchen tool equipment detects that the user refuses the recommendation operation on the target menu, the target menu attribute information and the target menu can be input into the menu knowledge map, the menu is determined again through the menu knowledge map, the target menu attribute information and the target menu, and the determined menu is used as the target menu to be recommended. Then, the intelligent kitchen appliance can output the target menu.
In the embodiment of the application, the intelligent kitchen ware device re-determines the specific processing process of the recipe through the recipe knowledge graph, the target recipe attribute information and the target recipe, and can refer to any one of the processing processes of the related technologies for information matching based on deep learning and the knowledge graph, which is not repeated here.
In the embodiment of the application, the intelligent kitchen tool equipment can input the attribute information of the target menu and the target menu into the menu knowledge map to re-determine the target menu after detecting that the user refuses the recommendation operation on the target menu. Because the target menu is re-determined based on the menu which is rejected and recommended by the user and the attribute information of the target menu, the re-determined target menu better meets the requirements of the user, and the user experience can be improved.
Optionally, after the voice data is collected, the intelligent kitchen ware device may perform user verification based on the voice data, if the user verification is successful, it is indicated that the user sending the voice data is a registered user, and then, the intelligent kitchen ware device may detect whether the voice data contains a preset keyword.
If the user verification fails, the voice data is not sent by the user, or the user sending the voice data is an unregistered user, and the intelligent kitchen ware device does not need to perform subsequent processing. In a possible implementation manner, in the case that the user who sends out the voice data is an unregistered user, the intelligent kitchenware device may use a pre-stored general user feature as the user feature of the unregistered user. Then, the intelligent kitchen ware device can determine target menu attribute information according to preset keywords and user characteristics, and then determine a target menu to be recommended according to the target menu attribute information and a pre-stored menu knowledge map.
In the embodiment of the application, the intelligent kitchen ware equipment can firstly carry out user verification based on the voice data, and then determines whether the voice data contain the preset keywords or not under the condition that the user verification is successful, so that the data processing burden of the intelligent kitchen ware equipment can be reduced. Furthermore, the target menu can be conveniently determined based on the user characteristics of the user successfully checked and the preset keywords, personalized recommendation of the menu is achieved, and therefore user experience is improved.
The embodiment of the application provides an implementation mode of carrying out user verification on intelligent kitchen ware equipment based on voice data, as shown in fig. 2, the implementation mode comprises the following steps:
In implementation, the intelligent kitchen appliance can extract various voiceprint features from the voice data, wherein the voiceprint features comprise the number of formants, the trend of the formants, the frequency of the formants and the like.
In implementation, the intelligent kitchen tool device can use the feature values of various voiceprint features as vector element values of corresponding voiceprint features in the initial voiceprint feature vector to obtain the target voiceprint feature vector.
In the embodiment of the application, the intelligent kitchen ware equipment can extract various voiceprint features from voice data through a preset voiceprint recognition algorithm, and establishes the target voiceprint feature vector according to the feature values of the various voiceprint features. Voiceprint recognition algorithms such as DNN-i-vector (Deep Neural Network-identity-vector), Deep Speaker: an End to End Neural Speaker Embedding System (Deep Speaker: an End-to-End Neural Speaker Embedding System).
And step 203, judging whether a voiceprint feature vector matched with the target voiceprint feature vector exists in the pre-stored corresponding relation between the user and the voiceprint feature vector.
In implementation, the intelligent kitchen tool device can judge whether the voiceprint feature vector matched with the target voiceprint feature vector exists in the pre-stored corresponding relation between the user and the voiceprint feature vector. If the user has a voiceprint feature vector matching the target voiceprint feature vector in the correspondence between the user and the voiceprint feature vector, the intelligent kitchen appliance may perform step 204.
If there is no voiceprint feature vector matching the target voiceprint feature vector in the correspondence between the user and the voiceprint feature vector, the intelligent kitchenware device may execute step 205.
And step 204, determining that the user verification is successful.
In the embodiment of the application, the intelligent kitchen tool equipment can extract various voiceprint features from voice data, and a target voiceprint feature vector is established according to the feature values of the various voiceprint features. Then, the intelligent kitchen tool device can judge whether the voiceprint feature vector matched with the target voiceprint feature vector exists in the pre-stored corresponding relation between the user and the voiceprint feature vector. If there is a voiceprint feature vector that matches the target voiceprint feature vector, the intelligent cookware apparatus may determine that the user verification is successful. If there is no voiceprint feature vector matching the target voiceprint feature vector, the intelligent cookware apparatus may determine that the user verification failed.
Therefore, the user does not need to perform account login operation such as inputting a user name and a password, the intelligent kitchen ware equipment can automatically authenticate the user, the intelligent kitchen ware equipment can directly recommend a target menu for the user while the user operation is facilitated, and the user experience can be improved.
Optionally, after the intelligent kitchen appliance determines that the user verification is successful, the intelligent kitchen appliance may use the user identifier corresponding to the matched voiceprint feature vector as the user identifier corresponding to the target voiceprint feature vector. Then, the intelligent kitchen appliance can determine the user characteristics corresponding to the user identification according to the pre-stored corresponding relationship between the user identification and the user characteristics. Therefore, the target menu attribute information can be conveniently determined subsequently based on the user characteristics corresponding to the user identification and the preset keywords, and further, the target menu can be determined based on the target menu attribute information and the menu knowledge map, so that personalized recommendation of the menu can be realized, and the user experience is improved.
Optionally, after the intelligent kitchen ware device determines that the user verification is successful, the intelligent kitchen ware device may further update the user portrait of the user successfully verified based on the voiceprint feature, and the specific processing procedure includes:
step 1, determining a preset user characteristic corresponding to the voiceprint characteristic according to the voiceprint characteristic, a pre-stored correspondence relationship between the voiceprint characteristic and the preset user characteristic.
In implementation, the type of the voiceprint feature corresponding to a certain preset user feature may be one or more.
The intelligent kitchen ware equipment can determine the preset user characteristics corresponding to the voiceprint characteristics according to the voiceprint characteristics of one or more users and the corresponding relation between the pre-stored voiceprint characteristics and the preset user characteristics.
For example, the user's voiceprint features are: the frequency of the formant is 70Hz, the intelligent kitchen ware equipment can search the voiceprint characteristics matched with the voiceprint characteristics of the user in the corresponding relation between the voiceprint characteristics and the preset user characteristics, and the voiceprint characteristics matched with the frequency of 70Hz of the formant are found to be the frequency range of the formant between 60Hz and 200 Hz. Then, intelligence kitchen utensils and appliances can be with the preset user characteristic that the voiceprint characteristic that matches corresponds: the gender is male, which is the preset user characteristic of the user.
And 2, judging whether preset user characteristics corresponding to the voiceprint characteristics exist in the user characteristics of the user successfully verified.
In implementation, the intelligent kitchen appliance may determine, from the locally stored user characteristics of each user, the user characteristics of the user who succeeds in verification according to the user identifier of the user who succeeds in verification. For convenience of description, the user characteristics of the user who successfully verified are referred to as target user characteristics.
Then, the intelligent kitchen ware device can judge whether preset user features corresponding to the voiceprint features exist in the target user features, and if the preset user features corresponding to the voiceprint features do not exist in the target user features, the intelligent kitchen ware device can execute the step 3; if the preset user characteristics corresponding to the voiceprint characteristics exist in the target user characteristics, the intelligent kitchen tool device can execute the step 4.
And 3, correspondingly storing the user and the preset user characteristics so as to update the user portrait of the user.
And 4, not performing subsequent treatment.
In the embodiment of the application, the intelligent kitchen ware equipment can determine the preset user characteristics corresponding to the voiceprint characteristics according to the corresponding relation between the voiceprint characteristics, the pre-stored voiceprint characteristics and the preset user characteristics, and then the intelligent kitchen ware equipment can correspondingly store the user and the preset user characteristics under the condition that the preset user characteristics corresponding to the voiceprint characteristics do not exist in the user characteristics of the user who succeeds in verification, so that the user portrait of the user can be updated.
Optionally, the intelligent kitchen ware device may further detect a preset keyword based on voice data including dialect, as shown in fig. 3, the specific processing procedure includes:
The dialect voiceprint features such as voice tones include a curled-tongue sound, a flat-tongue sound, an attack sound, and a turning sound.
In implementation, a plurality of dialect voiceprint characteristics can be stored in the intelligent kitchen ware device in advance, and the intelligent kitchen ware device can judge whether the voiceprint characteristics extracted from the voice data contain the dialect voiceprint characteristics or not.
If the voiceprint features include dialect voiceprint features, then intelligent cookware appliance may perform step 302, and if the voiceprint features do not include dialect voiceprint features, then intelligent cookware appliance may perform step 303.
And 302, determining semantic information corresponding to the dialect voiceprint features according to the dialect voiceprint features, the prestored corresponding relationship between the dialect voiceprint features and the semantic information, and obtaining the semantic information contained in the voice data.
In the embodiment of the application, the intelligent kitchen tool equipment can judge whether the voiceprint features extracted from the voice data contain dialect voiceprint features, and under the condition that the voiceprint features contain the dialect voiceprint features, semantic information corresponding to the dialect voiceprint features is determined according to the corresponding relation among the dialect voiceprint features, the prestored dialect voiceprint features and the semantic information, so that the semantic information contained in the voice data is obtained. And under the condition that the voiceprint features do not contain dialect voiceprint features, determining semantic information corresponding to the voiceprint features according to the voiceprint features, the pre-stored correspondence of the voiceprint features and the semantic information to obtain the semantic information contained in the voice data.
Therefore, by adopting the technical scheme provided by the embodiment of the application, multi-dimensional semantic analysis can be realized, namely, the preset keywords are detected based on the voice data containing dialects, on one hand, the detection accuracy of the preset keywords can be improved, on the other hand, the target menu which meets the requirements of the user can be recommended for the user, and therefore the user experience is improved.
Optionally, under the condition that the voiceprint features include dialect voiceprint features, the intelligent kitchen ware device can also determine target menu attribute information according to preset keywords, user features and the dialect voiceprint features.
In implementation, the intelligent kitchen ware device can determine the target menu attribute information through a preset semantic analysis algorithm, preset keywords, user characteristics and dialect voiceprint characteristics.
The embodiment of the application provides an implementation mode for determining target menu attribute information by intelligent kitchen ware equipment through a semantic analysis algorithm, preset keywords, user characteristics and dialect voiceprint characteristics:
the intelligent kitchen tool equipment can determine a target dialect to which the dialect voiceprint features belong and a target region to which the target dialect belongs, and then the intelligent kitchen tool equipment can determine taste preference information of the target region.
The intelligent kitchen ware equipment can be stored with weights in advance aiming at each preset keyword, each user characteristic and each taste preference information corresponding to a certain region, and can perform fusion analysis on the preset keyword, the user characteristic and the taste preference information of a target region according to the weight of the preset keyword, the weight of the user characteristic and the weight of the taste preference information of the target region to obtain target menu attribute information.
In the embodiment of the application, under the condition that the voiceprint features comprise dialect voiceprint features, the intelligent kitchen ware device can determine the target menu attribute information according to preset keywords, user features and the dialect voiceprint features. The intelligent kitchen tool equipment can narrow the geographical position range of the user through the dialect voiceprint characteristics, further presume the taste preference information of the user, and determine the target menu attribute information and the target menu based on the taste preference information, the preset keywords and the user characteristics of the user, so that the target menu which is more in line with the user requirements can be recommended for the user, and the user experience is improved.
Optionally, the intelligent kitchen ware device may be connected to a preset server, and the intelligent kitchen ware device may send the voice data to the server after acquiring the voice data in the current scene, so that the server acquires the pre-stored user characteristics when the voice data contains the preset keywords; determining target menu attribute information according to preset keywords and user characteristics; and determining a target menu to be recommended according to the attribute information of the target menu and a menu knowledge map stored in advance.
Based on the same technical concept, an embodiment of the present application further provides a menu recommending apparatus, as shown in fig. 4, the apparatus includes:
an acquisition module 410, configured to acquire voice data in a current scene;
an obtaining module 420, configured to obtain a pre-stored user characteristic when the voice data includes a preset keyword;
the first determining module 430 is configured to determine attribute information of the target menu according to the preset keyword and the user characteristic;
the second determining module 440 is configured to determine a target recipe to be recommended according to the target recipe attribute information and a pre-stored recipe knowledge graph, where the recipe knowledge graph includes a correspondence between recipes and recipe attribute information.
Optionally, the apparatus further comprises:
the user verification module is used for verifying the user based on the voice data;
and the detection module is used for determining whether the voice data contains preset keywords or not when the user successfully checks.
Optionally, the user verification module includes:
the extraction submodule is used for extracting a plurality of voiceprint characteristics from the voice data;
the establishing submodule is used for establishing a target voiceprint characteristic vector according to the characteristic values of the various voiceprint characteristics;
and the first determining submodule is used for determining that the user verification is successful when the voiceprint feature vector matched with the target voiceprint feature vector exists in the corresponding relation between the pre-stored user identification and the voiceprint feature vector.
Optionally, the determining sub-module is further configured to determine, when the user verification is successful, a user identifier corresponding to the target voiceprint feature vector;
the obtaining module is further configured to determine, according to a correspondence between a pre-stored user identifier and a user characteristic, a user characteristic corresponding to the user identifier.
Optionally, the detection module includes:
the second determining submodule is used for determining semantic information corresponding to the dialect voiceprint features according to the corresponding relation among the dialect voiceprint features, prestored dialect voiceprint features and semantic information when the voiceprint features contain the dialect voiceprint features, so as to obtain the semantic information contained in the voice data;
and the third determining submodule is used for determining whether the voice data contains preset keywords or not based on semantic information contained in the voice data.
Optionally, the first determining module is further configured to determine target recipe attribute information according to the preset keyword, the user characteristic, and the dialect voiceprint characteristic, where the target recipe attribute information includes at least one of taste preference information and a cooking manner.
Optionally, the apparatus further comprises:
the third determining module is used for determining the preset user characteristics corresponding to the voiceprint characteristics according to the voiceprint characteristics, the corresponding relation between the prestored voiceprint characteristics and the preset user characteristics when the user verification is successful;
and the updating module is used for correspondingly storing the user and the preset user characteristics when the preset user characteristics do not exist in the user characteristics of the user which is successfully verified so as to update the user portrait of the user.
Optionally, the second determining module is further configured to, when it is detected that the user rejects the recommendation operation for the target recipe, input the target recipe attribute information and the target recipe into the recipe knowledge graph to re-determine the target recipe.
The embodiment of the application has the following beneficial effects:
the embodiment of the application provides a menu recommending device, which collects voice data in a current scene; if the voice data contains preset keywords, acquiring prestored user characteristics; determining target menu attribute information according to preset keywords and user characteristics; and determining a target menu to be recommended according to the target menu attribute information and a menu knowledge map stored in advance, wherein the menu knowledge map comprises the corresponding relation between the menu and the menu attribute information. Under the condition that the collected voice data contain the preset keywords, the intelligent kitchen ware device automatically determines the target menu to be recommended according to the preset keywords and the user characteristics, so that the user does not need to perform voice interaction with the intelligent kitchen ware device for many times, and the user experience can be improved.
Based on the same technical concept, the embodiment of the present application further provides an electronic device, as shown in fig. 5, including a processor 501, a communication interface 502, a memory 503 and a communication bus 504, where the processor 501, the communication interface 502 and the memory 503 complete mutual communication through the communication bus 504,
a memory 503 for storing a computer program;
the processor 501, when executing the program stored in the memory 503, implements the following steps:
collecting voice data in a current scene;
if the voice data contains preset keywords, acquiring prestored user characteristics;
determining target menu attribute information according to the preset keywords and the user characteristics;
and determining a target menu to be recommended according to the target menu attribute information and a menu knowledge map stored in advance, wherein the menu knowledge map comprises the corresponding relation between the menu and the menu attribute information.
Optionally, after the acquiring the voice data in the current scene, the method further includes:
performing user verification based on the voice data;
and if the user verification is successful, determining whether the voice data contains preset keywords.
Optionally, the performing user verification based on the voice data includes:
extracting a plurality of voiceprint features from the voice data;
establishing a target voiceprint characteristic vector according to the characteristic values of the various voiceprint characteristics;
and if the voiceprint feature vector matched with the target voiceprint feature vector exists in the pre-stored corresponding relationship between the user identifier and the voiceprint feature vector, determining that the user verification is successful.
Optionally, the method further includes:
if the user verification is successful, determining a user identifier corresponding to the target voiceprint feature vector;
the acquiring of the pre-stored user characteristics includes:
and determining the user characteristics corresponding to the user identification according to the corresponding relation between the pre-stored user identification and the user characteristics.
Optionally, the determining whether the voice data includes a preset keyword includes:
if the voiceprint features comprise dialect voiceprint features, determining semantic information corresponding to the dialect voiceprint features according to the dialect voiceprint features, the prestored corresponding relationship between the dialect voiceprint features and the semantic information to obtain the semantic information contained in the voice data;
and determining whether the voice data contains preset keywords or not based on semantic information contained in the voice data.
Optionally, the determining, according to the preset keyword and the user characteristic, target recipe attribute information includes:
and determining target menu attribute information according to the preset keywords, the user characteristics and the dialect voiceprint characteristics, wherein the target menu attribute information comprises at least one of taste preference information and cooking modes.
Optionally, the method further includes:
if the user verification is successful, determining a preset user characteristic corresponding to the voiceprint characteristic according to the voiceprint characteristic, a pre-stored correspondence of the voiceprint characteristic and the preset user characteristic;
and if the preset user characteristics do not exist in the user characteristics of the user successfully verified, correspondingly storing the user and the preset user characteristics to update the user portrait of the user.
Optionally, the method further includes:
and if the user refuses the recommendation operation on the target menu is detected, inputting the attribute information of the target menu and the target menu into the menu knowledge graph to redetermine the target menu.
The communication bus mentioned in the electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component.
In yet another embodiment provided by the present application, a computer-readable storage medium is further provided, in which a computer program is stored, and the computer program, when executed by a processor, implements the steps of any of the above recipe recommendation methods.
In yet another embodiment provided by the present application, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform any of the recipe recommendation methods of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is merely exemplary of the present application and is presented to enable those skilled in the art to understand and practice the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (18)
1. A method for menu recommendation, the method comprising:
collecting voice data in a current scene;
if the voice data contains preset keywords, acquiring prestored user characteristics;
determining target menu attribute information according to the preset keywords and the user characteristics;
and determining a target menu to be recommended according to the target menu attribute information and a menu knowledge map stored in advance, wherein the menu knowledge map comprises the corresponding relation between the menu and the menu attribute information.
2. The method of claim 1, wherein after the collecting the speech data in the current scene, further comprising:
performing user verification based on the voice data;
and if the user verification is successful, determining whether the voice data contains preset keywords.
3. The method of claim 2, wherein the performing the user verification based on the voice data comprises:
extracting a plurality of voiceprint features from the voice data;
establishing a target voiceprint characteristic vector according to the characteristic values of the various voiceprint characteristics;
and if the voiceprint feature vector matched with the target voiceprint feature vector exists in the pre-stored corresponding relationship between the user identifier and the voiceprint feature vector, determining that the user verification is successful.
4. The method of claim 3, further comprising:
if the user verification is successful, determining a user identifier corresponding to the target voiceprint feature vector;
the acquiring of the pre-stored user characteristics includes:
and determining the user characteristics corresponding to the user identification according to the corresponding relation between the pre-stored user identification and the user characteristics.
5. The method of claim 3, wherein the determining whether the voice data contains a predetermined keyword comprises:
if the voiceprint features comprise dialect voiceprint features, determining semantic information corresponding to the dialect voiceprint features according to the dialect voiceprint features, the prestored corresponding relationship between the dialect voiceprint features and the semantic information to obtain the semantic information contained in the voice data;
and determining whether the voice data contains preset keywords or not based on semantic information contained in the voice data.
6. The method of claim 5, wherein the determining target menu attribute information according to the preset keyword and the user characteristic comprises:
and determining target menu attribute information according to the preset keywords, the user characteristics and the dialect voiceprint characteristics, wherein the target menu attribute information comprises at least one of taste preference information and cooking modes.
7. The method according to any one of claims 3-6, further comprising:
if the user verification is successful, determining a preset user characteristic corresponding to the voiceprint characteristic according to the voiceprint characteristic, a pre-stored correspondence of the voiceprint characteristic and the preset user characteristic;
and if the preset user characteristics do not exist in the user characteristics of the user successfully verified, correspondingly storing the user and the preset user characteristics to update the user portrait of the user.
8. The method of claim 1, further comprising:
and if the user refuses the recommendation operation on the target menu is detected, inputting the attribute information of the target menu and the target menu into the menu knowledge graph to redetermine the target menu.
9. A menu recommendation device, characterized in that the device comprises:
the acquisition module is used for acquiring voice data in the current scene;
the acquisition module is used for acquiring the pre-stored user characteristics when the voice data contains preset keywords;
the first determining module is used for determining target menu attribute information according to the preset keywords and the user characteristics;
and the second determination module is used for determining a target menu to be recommended according to the target menu attribute information and a pre-stored menu knowledge map, wherein the menu knowledge map comprises a corresponding relation between the menu and the menu attribute information.
10. The apparatus of claim 9, further comprising:
the user verification module is used for verifying the user based on the voice data;
and the detection module is used for determining whether the voice data contains preset keywords or not when the user successfully checks.
11. The apparatus of claim 10, wherein the user verification module comprises:
the extraction submodule is used for extracting a plurality of voiceprint characteristics from the voice data;
the establishing submodule is used for establishing a target voiceprint characteristic vector according to the characteristic values of the various voiceprint characteristics;
and the first determining submodule is used for determining that the user verification is successful when the voiceprint feature vector matched with the target voiceprint feature vector exists in the corresponding relation between the pre-stored user identification and the voiceprint feature vector.
12. The apparatus according to claim 11, wherein the determining sub-module is further configured to determine, when the user verification is successful, a user identifier corresponding to the target voiceprint feature vector;
the obtaining module is further configured to determine, according to a correspondence between a pre-stored user identifier and a user characteristic, a user characteristic corresponding to the user identifier.
13. The apparatus of claim 11, wherein the detection module comprises:
the second determining submodule is used for determining semantic information corresponding to the dialect voiceprint features according to the corresponding relation among the dialect voiceprint features, prestored dialect voiceprint features and semantic information when the voiceprint features contain the dialect voiceprint features, so as to obtain the semantic information contained in the voice data;
and the third determining submodule is used for determining whether the voice data contains preset keywords or not based on semantic information contained in the voice data.
14. The apparatus of claim 13, wherein the first determining module is further configured to determine target recipe attribute information according to the preset keyword, the user characteristic, and the dialect voiceprint characteristic, and the target recipe attribute information includes at least one of taste preference information and cooking manner.
15. The apparatus of any of claims 11-14, further comprising:
the third determining module is used for determining the preset user characteristics corresponding to the voiceprint characteristics according to the voiceprint characteristics, the corresponding relation between the prestored voiceprint characteristics and the preset user characteristics when the user verification is successful;
and the updating module is used for correspondingly storing the user and the preset user characteristics when the preset user characteristics do not exist in the user characteristics of the user which is successfully verified so as to update the user portrait of the user.
16. The apparatus of claim 9, wherein the second determining module is further configured to input the target recipe attribute information and the target recipe into the recipe knowledge graph to re-determine the target recipe when the user's recommendation rejection operation for the target recipe is detected.
17. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any of claims 1 to 8 when executing a program stored in the memory.
18. A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method steps of any one of the claims 1-8.
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