CN108427962B - Identification method, device and equipment - Google Patents
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Abstract
The method can acquire behavior characteristics of a plurality of disabled users as sample data, train and obtain an identification model for identifying whether the user is the disabled user or not based on the acquired sample data, acquire the behavior characteristics of the user to be identified when the user to be identified needs to perform the disabled identification, and input the behavior characteristics of the user to be identified into the identification model to identify whether the user to be identified is the disabled user or not.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method, an apparatus, and a device for identification.
Background
With the continuous development of computer technology, various applications (apps) with rich functions are integrated into the daily life of people, and people can quickly and conveniently complete various online services through the apps, so that the efficiency of service processing is greatly improved.
For users with certain dysfunction (so-called handicapped users), the users usually need to use certain auxiliary tools to operate the mid-functions of the apps when using the apps. For example, for a visually impaired user using an android phone (the visually impaired user refers to a user whose visual function is impaired to some extent), the content touched on the screen of the phone can be converted into voice information through a Talkback handicap assistance tool carried by the phone system, so that each function in the App is operated through the instruction of the voice information.
For manufacturers of various apps, the apps are required to identify whether users using the apps are disabled users, and when the users are identified as disabled users, the apps provide more convenient services for the disabled users. In practical applications, it is common to identify whether a user is a disabled user by monitoring whether the user turns on a switch of a disabled aid such as Talkback in a terminal.
Based on the prior art, a more accurate identification method is needed.
Disclosure of Invention
The specification provides an identification method, which is used for solving the problem that whether a user is a disabled user cannot be identified in the prior art.
The present specification provides a method of identification, comprising:
acquiring behavior characteristics of a plurality of disabled users as sample data, wherein the behavior characteristics comprise: at least one of first information representing an operation state when a user operates a terminal and second information representing a service type of a service executed by the user;
training to obtain an identification model for identifying whether the user is a disabled user or not through the sample data;
when the user to be identified is subjected to the handicap identification, acquiring the behavior characteristics of the user to be identified, and inputting the behavior characteristics of the user to be identified into the identification model so as to identify whether the user to be identified is the handicap user.
The specification provides an identification device, which is used for solving the problem that whether a user is a disabled user cannot be identified in the prior art.
The present specification provides an apparatus for identification, comprising:
the acquisition module acquires behavior characteristics of a plurality of disabled users as sample data, wherein the behavior characteristics comprise: at least one of first information representing an operation state when a user operates a terminal and second information representing a service type of a service executed by the user;
the training module is used for training to obtain an identification model for identifying whether the user is a disabled user or not through the sample data;
the identification module is used for acquiring the behavior characteristics of the user to be identified when the user to be identified is subjected to the handicap identification, and inputting the behavior characteristics of the user to be identified into the identification model so as to identify whether the user to be identified is the handicap user.
The specification provides an identification device for solving the problem that in the prior art, whether a user is a disabled user cannot be identified.
The present specification provides an identified device comprising one or more memories and a processor, the memories storing programs and configured to perform the following steps by the one or more processors:
acquiring behavior characteristics of a plurality of disabled users as sample data, wherein the behavior characteristics comprise: at least one of first information representing an operation state when a user operates a terminal and second information representing a service type of a service executed by the user;
training to obtain an identification model for identifying whether the user is a disabled user or not through the sample data;
when the user to be identified is subjected to the handicap identification, acquiring the behavior characteristics of the user to be identified, and inputting the behavior characteristics of the user to be identified into the identification model so as to identify whether the user to be identified is the handicap user.
The technical scheme adopted by the specification can achieve the following beneficial effects:
in one or more embodiments of the present disclosure, because behavior characteristics of a disabled user and a non-disabled user have a significant difference, compared to a single mode in which whether a user to be identified is a disabled user is identified through state information indicating whether a disabled aid in a terminal is turned on, the behavior characteristics of the user to be identified are analyzed by using a pre-trained identification model, so that whether the user to be identified is a disabled user can be identified more accurately, and thus, more convenient and faster service can be provided for the user.
Drawings
The accompanying drawings, which are included to provide a further understanding of the specification and are incorporated in and constitute a part of this specification, illustrate embodiments of the specification and together with the description serve to explain the specification and not to limit the specification in a non-limiting sense. In the drawings:
FIG. 1 is a schematic diagram of an identification process provided herein;
FIG. 2 is a schematic diagram of two patterns with different colors and the same shape being converted into text;
FIG. 3 is a schematic diagram of preserving behavioral characteristics of disabled users provided herein;
FIG. 4 is a schematic view of an apparatus for identification provided herein;
fig. 5 is a schematic diagram of an apparatus for identification provided in the present specification.
Detailed Description
In order to provide more convenient service for the disabled user, in the prior art, whether the user to be identified is the disabled user can be identified by monitoring whether the user to be identified opens an assistant tool for the disabled, such as Talkback and Voice Over, in a held terminal, and when the user to be identified is determined to be the disabled user, an information display mode of an App used by the disabled user is adjusted, so that the disabled user can use the App more conveniently.
Currently, whether a user to be identified opens the handicap assisting tool or not is monitored usually by means of embedding points, for example, whether a Talkback switch is opened or not is monitored by implanting a specified code. However, the existing handicapped user identification method has the following problems:
in practical applications, with continuous optimization and updating, multiple versions of an App exist, however, not all versions of the App have the function of identifying disabled users. Therefore, for the case that some disabled users are not updated due to being used to an App of one version for a long time, if the App of the version does not have the function of identifying the disabled user, the disabled user cannot be provided with convenient service for the disabled user, and inconvenience is brought to the disabled user.
Secondly, in the process of using some specific apps, a user may need to open handicap auxiliary tools such as Talkback and Voice Over to achieve some specific functions of the specific apps. However, these users are likely not disabled users. In this way, if the App capable of identifying the disabled users and providing the special service to the disabled users monitors that the users open the disabled auxiliary tool in the terminal, the special service suitable for the disabled users will be provided to the users. Moreover, the verification and processing modes of some services may be adjusted to be suitable for disabled users, which may bring inconvenience to the non-disabled users.
In order to effectively avoid inconvenience brought to a user by the above problems, in this specification, behavior characteristics of a plurality of disabled users may be acquired as sample data, and based on the acquired sample data, an identification model for identifying whether the user is a disabled user is obtained through training, when the user to be identified needs to perform the disabled identification, the behavior characteristics of the user to be identified may be acquired, and the behavior characteristics of the user to be identified are input into the identification model to identify whether the user to be identified is a disabled user.
Because the behavior characteristics of the disabled user and the non-disabled user have obvious difference, compared with the mode that whether the user to be identified is the disabled user is identified by the state information of whether the disabled auxiliary tool in the terminal is opened or not, the behavior characteristics of the user to be identified are analyzed by utilizing the pre-trained identification model, whether the user to be identified is the disabled user can be identified more accurately, and therefore more convenient service can be provided for the user.
In this specification, the executing agent for identifying the user to be identified may be an identifying device such as a server and an identifying terminal of an App manufacturer, and the identifying method provided in this specification will be described below with only the server as the executing agent.
In order to make those skilled in the art better understand the technical solutions in one or more embodiments of the present disclosure, the technical solutions in one or more embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in one or more embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.
Fig. 1 is a schematic diagram of an identification process provided in this specification, and specifically includes the following steps:
s100: behavior characteristics of a plurality of disabled users are obtained as sample data.
When a user uses a terminal or an App installed in the terminal, the terminal or the App can determine the behavior characteristics of the user and send the behavior characteristics to a server, so that the server analyzes the behavior characteristics through a pre-trained recognition model to recognize whether the user is a disabled user. The terminal mentioned here may refer to a smart phone, a tablet computer, and other devices used by a user.
In this specification, the behavior characteristics can be roughly classified into two types, one is first information capable of characterizing an operation state when a user operates a terminal, and the other is second information capable of characterizing a service type of a service performed by the user. Because the handicapped user often has a significant difference from the non-handicapped user (i.e., a normal user) in terms of body behavior, vision, hearing, and the like, the operation state exhibited when the handicapped user operates the terminal is often different from the operation state exhibited when the non-handicapped user operates the terminal. For example, the operation state of the non-disabled user when operating the terminal is more natural, the operation action is smoother and faster, and the operation state of the disabled user when operating the terminal may be slower and uncoordinated. Therefore, in the present specification, the first information capable of characterizing the operation state when the user operates the terminal may be taken as a behavior feature for distinguishing the handicapped user from the non-handicapped user.
The first information capable of representing the operation state of the user operating the terminal may be in various forms, for example, the first information may be the operation duration of the target object in the user operating the terminal, the accuracy of the target object in the user operating the terminal, or the state information of whether the handicap assistance tool in the terminal is turned on.
The target object in the terminal mentioned herein may be in various forms, for example, a page displayed to a user by the terminal may be referred to as a target object, a designated control in one page may be referred to as a target object, and a file in the terminal may be referred to as a target object. Accordingly, the operation duration of the target object in the user operation terminal mentioned above may also be in various forms.
For example, assuming that the target object is a designated control in the App interface, a non-visually impaired user may quickly prepare to make a click on the designated control. For the visually impaired user, the visually impaired user may need to touch each position in the App interface to convert information corresponding to each position into voice information through the handicap assistance tool and play the voice information, and the visually impaired user can determine the position of the designated control through the played voice information and perform click operation on the designated control. Therefore, the time from the beginning of displaying the designated control to the time clicked by the user can be referred to as the operation duration of the user for operating the target object, and the operation duration can effectively represent whether the user is a visually impaired user.
For another example, assuming that the target object is a designated page displayed by the terminal, the time spent by the non-visually impaired user to browse the designated page is usually short, and the time spent by the visually impaired user is usually long, so the time from the start of displaying the designated page to the switching to another page may be referred to as the operation time of the user to operate the target object.
Since the target object may have various forms, the operation duration may be defined in various ways, which is not necessarily illustrated herein. The accuracy of the target object in the user operation mentioned above may also be in various forms.
For example, assuming that the target object is a designated page displayed by the terminal, the designated page includes a plurality of designated controls, and a user can jump to different pages by clicking different designated controls. When the user clicks one of the designated controls and then performs the return operation within a set time (which may be referred to as a shorter time), the operation of the user may be determined as an error operation. The terminal can count the times of error operation of the user on the specified page in the mode, and further determine the accuracy of the user on operating the specified page. Because the accuracy rate of the normal user for operating the designated page is usually higher, and the accuracy rate of the disabled user is relatively lower, the accuracy rate can effectively represent whether the user is the disabled user.
For another example, assuming that the target object is a plurality of voice messages displayed by the terminal, when the user performs a broadcast operation for a voice message more than a set number of times, it may be determined that the voice message has performed an abnormal broadcast operation. The terminal can determine the accuracy of the playing operation performed on the voice messages by the user by counting the number of the voice messages subjected to the abnormal playing operation and the total number of the voice messages. Since the normal user has less possibility of performing abnormal broadcasting operation on the voice message and the disabled user has relatively high possibility, whether the user is the disabled user can be identified through the accuracy. Of course, the accuracy of defining the target object in the user operation terminal may be in other manners, which are not necessarily illustrated herein.
In practical application, because a disabled user usually sets the disabled assisting tool in the terminal to be in an open state when using the terminal, the state information of whether the disabled assisting tool in the terminal is open can be used as the first information to represent whether the user is a disabled user. Among them, the handicap assistance tools mentioned here may be such as Talkback, Voice Over, Voice-to-text App, etc.
The first information may be in other forms than the ones described above. For example, the amplitude and frequency of sliding a page are relatively fast because a non-visually impaired user can quickly determine the content in the page while browsing the page. For the visually impaired user, when the visually impaired user browses the page, the content in the page can be slowly determined through the played voice information only by converting the content of the page into corresponding voice information through the handicap assistance tool, so that the amplitude and the frequency of the page sliding are relatively slow. Therefore, the amplitude and the frequency of the user sliding page can also be used as first information representing the operation state of the user when the user operates the terminal, and are used for carrying out the handicap identification on the user.
For another example, a user with normal hearing usually does not use a bluetooth hearing aid when using a mobile terminal such as a mobile phone or a tablet computer, and the bluetooth hearing aid can help a hearing-impaired user (i.e., a user with hearing impairment) to perform telephone communication with another person and listen to voice information. Based on the information, the information indicating whether the connection record of the Bluetooth hearing aid exists in the terminal can also be used as first information indicating the operation state when the user operates the terminal, so that the user with hearing impairment can be distinguished from the user without hearing impairment.
In practical applications, the types of services performed by the non-disabled users and the disabled users often differ, in other words, the disabled users often perform services in daily life, and the concerned services are different from the non-disabled users. Therefore, the second information characterizing the service type of the service executed by the user can be used for identifying the disabilities of the user.
In the model training process, the second information of the disabled user acquired by the server may refer to the service types of all services executed by the disabled user, or may refer to the service types of the services related to the disabled executed by the disabled user.
In this specification, the above-mentioned recognition model may be obtained by the server through behavior feature training of a plurality of disabled users, which are acquired in advance and used as sample data. Of course, in the model training process, the further acquired behavior characteristics of the non-disabled user may also be used as sample data according to actual requirements, and the behavior characteristics of the disabled user are combined to train the recognition model.
S102: and training to obtain an identification model for identifying whether the user is a disabled user or not through the sample data.
In this specification, the recognition model may be trained by using pre-acquired sample data in a supervised learning manner. The learning method adopted by the recognition model may be a decision tree, a Deep Neural Network (DNN), a Convolutional Neural Network (CNN), and the like, and is not limited specifically herein.
S104: when the user to be identified is subjected to the handicap identification, acquiring the behavior characteristics of the user to be identified, and inputting the behavior characteristics of the user to be identified into the identification model so as to identify whether the user to be identified is the handicap user.
When the server identifies the handicap of the user to be identified, the server can acquire the behavior characteristics of the user to be identified through the terminal used by the user to be identified, and then input the behavior characteristics into a pre-trained identification model so as to identify whether the user to be identified is the handicap according to the identification result obtained by the identification model. The terminal may send the behavior characteristics of the user to be identified, which are determined within a set time (e.g., a week, a month, etc.), to the server.
The server can determine whether the user to be identified is outdoor for the handicap or not through the identification model, and can further determine the handicap user to which the user to be identified belongs. Because the corresponding behavior characteristics of handicapped users in different handicapped forms are different. For example, visually impaired users usually turn on the assistant tool capable of converting text into Voice information in the terminal, and for hearing impaired users, usually turn on the assistant tool capable of converting Voice into text in the terminal. Based on the method, different forms of disabled users can be distinguished through different behavior characteristics.
In this specification, after determining that the user to be identified is a disabled user, the server may provide convenient service for the disabled user. For example, if the server determines that the user to be identified is the visually impaired user through the identification model, the information display mode of the App used by the visually impaired user may be adjusted.
The information display mode of the App can be adjusted in many forms. For example, after determining that the user to be identified is a visually impaired user, the server may send a page adjustment instruction to an App used by the visually impaired user, so that the App adjusts the page layout according to the page adjustment instruction, so that the adjusted page layout can adapt to larger text information for display.
For another example, after determining that the user to be identified is the visually impaired user, the server may adjust the definition of the multimedia information such as the video and the like related in the information acquisition request sent by the visually impaired user to a version suitable for the visually impaired user to browse, and send the version to the visually impaired user for watching.
Of course, the adjustment of App is not limited to the adjustment of the information presentation manner, and may be in other forms. For example, after the user to be identified is determined to be the visually impaired user, the sliding amplitude of the App page (the sliding amplitude mentioned here refers to a distance that the App page slides when the user slides on the terminal screen) may be adjusted according to a preset adjustment policy, or the adjustment amplitude of the sliding distance of the App page may be determined according to the behavior characteristics of the user to be identified, so that the visually impaired user can use the App more conveniently.
For a color-blind user, when the user is determined to be the color-blind user through the behavior characteristics of the user (the functional state information here may indicate that the user has started the color-blind mode in the terminal), several patterns with different colors but the same shape in the App page may be converted into corresponding characters, so as to be convenient for the color-blind user to distinguish, as shown in fig. 2.
Fig. 2 is a schematic diagram of converting two patterns with different colors and the same shape into characters provided in this specification.
Assuming that one service relates to two virtual currencies, a user can acquire the two virtual currencies by signing in, completing a specified service task and the like, and redeem items such as coupons and the like through the acquired virtual currencies. The two types of virtual money shown in fig. 2 are a gold ingot and a silver ingot, respectively, and the patterns of the two types of virtual money are different in color but have the same shape. In order to facilitate the color-blind user to distinguish the two virtual currencies, after the user is determined to be the visually impaired user, the patterns of the two virtual currencies can be converted into the text form as shown in fig. 2, so as to facilitate the distinguishing of the visually impaired user.
Of course, for the case that the user to be identified is a visually impaired user, there are many ways to adjust App, and this is not necessarily illustrated here. For the disabled users in other disabled forms, the idea of the manner of the server adjusting the App is similar to the above adjusting manner. For example, for the case that the user to be identified is an hearing-impaired user, the server may convert the voice information related to the information acquisition request sent by the hearing-impaired user into text information, and send the text information to the hearing-impaired user for browsing. Other ways of adjustment are not illustrated in detail here.
In this specification, after determining that the user to be identified is a disabled user, the server may also push information to the disabled user, so as to recommend a service, an App, and the like suitable for the disabled user to the disabled user through the information.
The products such as the service and the App suitable for the disabled user can be counted in advance by the server. After determining the handicap mode of a handicap user, the server can record the service, App and other products used by the user. Based on the mode, the server can count the services, apps and other products commonly used by the disabled users in different disabled forms, and then recommend the counted services, apps and other products commonly used by the disabled users in the disabled forms to the users in an information pushing mode after identifying the specific disabled form of one disabled user.
As can be seen from this, in the prior art, it is only a single method to monitor whether the handicap assisting tool is turned on in the terminal used by the user to identify whether a user is a handicap user, and the identification result obtained in this way is often not accurate enough. The identification method provided by the specification is based on the obvious difference in behaviors of the non-disabled user and the disabled user when the user operates the terminal, and the behavior characteristics generated when the user to be identified operates the terminal can be comprehensively identified through the pre-trained identification model, so that whether the user is the disabled user or not can be accurately identified, and the identification accuracy is greatly improved.
It should be noted that, in this specification, the server determines that the user to be identified is a disabled user through the obtained behavior feature of the user to be identified, and when it is determined that the disabled user does not start the disabled assisting tool in the terminal according to the first information included in the behavior feature, may send a prompt message to the disabled user to prompt the user to start the disabled assisting tool.
If the handicap auxiliary tool is a tool carried in the terminal system, the server can firstly acquire the model information of the terminal used by the handicap user before prompting the user, then determines the starting flow of the handicap auxiliary tool matched with the model information according to the prestored starting flow of the handicap auxiliary tool of each model, and then sends the starting flow of the handicap auxiliary tool to the handicap user in the form of prompting information so as to guide the handicap user to start the handicap auxiliary tool in the used terminal.
In this specification, the server may collect the behavior characteristics of the disabled user for subsequent use, as shown in fig. 3.
Fig. 3 is a schematic diagram for saving the behavior characteristics of the disabled user provided in the present specification.
After the server acquires the behavior characteristics of the user to be identified, the behavior characteristics can be input into a pre-trained identification model so as to identify whether the user to be identified is a disabled user. When the user to be identified is determined to be a disabled user, the behavior characteristics of the disabled user can be recorded in a preset behavior characteristic library of the disabled user for storage.
In this way, subsequent developers can adjust existing businesses and apps based on the behavior characteristics stored in the behavior characteristic library of the disabled user, or develop products such as businesses and apps suitable for the disabled user according to the behavior characteristics, so as to provide better services for the disabled user.
In addition, in the process of describing the identification method provided by the present specification, the above is performed by taking the visually impaired user and the visually impaired user as examples, and the identification method provided by the present specification is not limited to the identification of the visually impaired user and the visually impaired user, and can also be used for identifying other forms of visually impaired users.
For example, the server may determine each public number concerned by the user to be identified and the service type of the executed service, and input each determined public number and each determined service type as a behavior feature into a pre-trained identification model to perform handicap identification on the user to be identified. If the public number concerned by the user to be identified contains a large number of public numbers related to wheelchair aspects, and some services such as insurance, convenience for traveling and the like are related to the executed services, the user to be identified can be identified as the user with leg disabilities through the identification model, and then service information related to leg disabilities is pushed to the user.
The above identification method provided for one or more embodiments of the present specification is based on the same idea, and the present specification further provides a corresponding identification device, as shown in fig. 4.
Fig. 4 is a schematic diagram of an identification apparatus provided in this specification, which specifically includes:
the obtaining module 401 obtains behavior features of a plurality of disabled users as sample data, where the behavior features include: at least one of first information representing an operation state when a user operates a terminal and second information representing a service type of a service executed by the user;
a training module 402, which trains to obtain an identification model for identifying whether the user is a disabled user or not through the sample data;
the identification module 403, when performing the handicap identification on the user to be identified, obtains the behavior characteristics of the user to be identified, and inputs the behavior characteristics of the user to be identified into the identification model to identify whether the user to be identified is the handicap user.
The first information includes: at least one of operation duration of a target object in a user operation terminal, accuracy of the target object in the operation terminal, and state information indicating whether a handicap assistance tool of the terminal is turned on, wherein the handicap assistance tool comprises: at least one of Talkback and Voice Over.
The handicapped user includes: and at least one of visually impaired users and hearing impaired users.
The device further comprises:
and an adjusting module 404, configured to adjust an information display mode of the application App used by the user to be identified if the user to be identified is a visually impaired user.
The adjustment of the information display mode comprises the following steps: and adjusting at least one of the page layout of the App page and the display form of the multimedia information in the App page.
The device further comprises:
and a prompting module 405, configured to prompt the user to be identified to start the auxiliary tool if the user to be identified is determined to be a disabled user and the auxiliary tool is determined to be in an unopened state according to the first information.
Based on the above-described identification method, the present specification also correspondingly provides an apparatus for identification, as shown in fig. 5. The apparatus includes one or more memories and a processor, the memories storing programs and configured to perform the following steps by the one or more processors:
acquiring behavior characteristics of a plurality of disabled users as sample data, wherein the behavior characteristics comprise: at least one of first information representing an operation state when a user operates a terminal and second information representing a service type of a service executed by the user;
training to obtain an identification model for identifying whether the user is a disabled user or not through the sample data;
when the user to be identified is subjected to the handicap identification, acquiring the behavior characteristics of the user to be identified, and inputting the behavior characteristics of the user to be identified into the identification model so as to identify whether the user to be identified is the handicap user.
In one or more embodiments of the present specification, behavior characteristics of a plurality of users with disabilities may be acquired as sample data, an identification model for identifying whether a user is a user with disabilities is obtained through training based on the acquired sample data, when a user to be identified needs to perform disability identification, the behavior characteristics of the user to be identified may be acquired, and the behavior characteristics of the user to be identified may be input to the identification model to identify whether the user to be identified is a user with disabilities.
Because the behavior characteristics of the disabled user and the non-disabled user have obvious difference, compared with a mode of identifying whether the user to be identified is the disabled user or not through the functional state information, the behavior characteristics of the user to be identified are analyzed by utilizing the pre-trained identification model, whether the user to be identified is the disabled user or not can be identified more accurately, and therefore more convenient service can be provided for the user.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to one or more embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that 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 like elements in a process, method, article, or apparatus that comprises the element.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The above description is merely one or more embodiments of the present disclosure and is not intended to limit the present disclosure. Various modifications and alterations to one or more embodiments of the present description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of one or more embodiments of the present specification should be included in the scope of the claims of the present specification.
Claims (9)
1. A method of identification, comprising:
acquiring behavior characteristics of a plurality of disabled users as sample data, wherein the disabled users comprise: at least one of visually impaired users and hearing impaired users; the behavior characteristics include: at least one of first information representing an operation state when a user operates a terminal and second information representing a service type of a service executed by the user; the first information includes: at least one of operation duration of a target object in a user operation terminal, accuracy of the target object in the operation terminal, and state information indicating whether a handicap assistance tool of the terminal is turned on, wherein the handicap assistance tool comprises: at least one of Talkback and Voice Over;
training to obtain an identification model for identifying whether the user is a disabled user or not through the sample data;
when the user to be identified is subjected to the handicap identification, acquiring the behavior characteristics of the user to be identified, and inputting the behavior characteristics of the user to be identified into the identification model so as to identify whether the user to be identified is the handicap user.
2. The method of claim 1, further comprising:
and if the user to be identified is identified as the visually impaired user, adjusting the information display mode of the application App used by the user to be identified.
3. The method of claim 2, wherein adjusting the information presentation mode comprises: and adjusting at least one of the page layout of the App page and the display form of the multimedia information in the App page.
4. The method of claim 1, further comprising:
and if the user to be identified is determined to be the disabled user and the disabled auxiliary tool is determined to be in the unopened state according to the first information, prompting the user to be identified to open the disabled auxiliary tool.
5. An apparatus for identification, comprising:
the acquisition module acquires behavior characteristics of a plurality of disabled users as sample data, wherein the disabled users comprise: at least one of visually impaired users and hearing impaired users; the behavior characteristics include: at least one of first information representing an operation state when a user operates a terminal and second information representing a service type of a service executed by the user; the first information includes: at least one of operation duration of a target object in a user operation terminal, accuracy of the target object in the operation terminal, and state information indicating whether a handicap assistance tool of the terminal is turned on, wherein the handicap assistance tool comprises: at least one of Talkback and Voice Over;
the training module is used for training to obtain an identification model for identifying whether the user is a disabled user or not through the sample data;
the identification module is used for acquiring the behavior characteristics of the user to be identified when the user to be identified is subjected to the handicap identification, and inputting the behavior characteristics of the user to be identified into the identification model so as to identify whether the user to be identified is the handicap user.
6. The apparatus of claim 5, further comprising:
and the adjusting module is used for adjusting the information display mode of the application App used by the user to be identified if the user to be identified is the visually impaired user.
7. The apparatus of claim 6, wherein adjusting the information presentation comprises: and adjusting at least one of the page layout of the App page and the display form of the multimedia information in the App page.
8. The apparatus of claim 6, further comprising:
and the prompting module prompts the user to be identified to start the auxiliary tool for the disabled if the user to be identified is determined to be the user with the disabled and the auxiliary tool for the disabled is determined to be in the unopened state according to the first information.
9. An identified device comprising one or more memories and a processor, the memories storing programs and configured to perform the following steps by the one or more processors:
acquiring behavior characteristics of a plurality of disabled users as sample data, wherein the behavior characteristics comprise: at least one of first information representing an operation state when a user operates a terminal and second information representing a service type of a service executed by the user;
training to obtain an identification model for identifying whether the user is a disabled user or not through the sample data;
when the user to be identified is subjected to the handicap identification, acquiring the behavior characteristics of the user to be identified, and inputting the behavior characteristics of the user to be identified into the identification model so as to identify whether the user to be identified is the handicap user.
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| CN112843724B (en) * | 2021-01-18 | 2022-03-22 | 浙江大学 | Game scenario display control method and device, electronic equipment and storage medium |
| CN113010008A (en) * | 2021-02-01 | 2021-06-22 | 深圳市沃特沃德信息有限公司 | Tooth movement interaction method and device based on TWS earphone and computer equipment |
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| CN107016233A (en) * | 2017-03-14 | 2017-08-04 | 中国科学院计算技术研究所 | The association analysis method and system of motor behavior and cognitive ability |
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| CN107016233A (en) * | 2017-03-14 | 2017-08-04 | 中国科学院计算技术研究所 | The association analysis method and system of motor behavior and cognitive ability |
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