Command matching method and device, wearable device, and storage medium

Abstract

The present disclosure provides an instruction matching method and apparatus, a wearable device, and a storage medium, which belong to the field of instruction matching technology. The method includes: determining an instruction list based on a function type and an interactive action type. Determining a function priority sequence corresponding to a function type and an action priority sequence corresponding to an interactive action type based on historical usage data. Determining the functional similarity of multiple functions in a function priority sequence based on the function type, and determining a function-action matching relationship based on the function priority sequence, the action priority sequence, and the functional similarity. Determining an instruction matching relationship based on the function-action matching relationship and the instruction list. The instruction matching relationship includes an action-instruction-function matching relationship. The instruction matching method and apparatus, wearable device, and storage medium provided by the present disclosure can solve the problem that the prior art lacks an effective instruction matching method, and improve the user experience.

Description

Technical Field

[0001] The present disclosure belongs to the field of instruction matching technology, and more specifically, relates to an instruction matching method and apparatus, a wearable device, and a storage medium. Background Art

[0002] In today's rapidly evolving digital age, command matching approaches face new challenges and opportunities. As new features continue to emerge, the demand for interaction is growing exponentially. This necessitates the development of a new and comprehensive command matching strategy.

[0003] However, existing command matching solutions have many limitations. Excessive gesture operations exceed the typical learning capacity, leading to increased learning costs for users. Furthermore, the high similarity between multiple gestures makes it easy to make mistakes during key operations, seriously interfering with normal usage processes and functional implementation, affecting user experience and efficiency. This requires us to conduct a comprehensive and in-depth study of command matching methods, carefully sorting out the logical relationships between functions, and optimizing command settings and matching rules with a user-centric approach. This will minimize the operational process, reduce user learning costs, and enable all types of users to quickly adapt and become proficient in the application. Summary of the Invention

[0004] The purpose of the present disclosure is to provide a command matching method and apparatus, a wearable device, and a storage medium to solve the problem that the prior art lacks an effective command matching method and improve the user experience.

[0005] According to a first aspect of an embodiment of the present disclosure, a command matching method is provided, which is applied to a wearable device and includes:

[0006] Determine the instruction list based on the function type and the interaction action type;

[0007] Determine, based on historical usage data, a function priority sequence corresponding to the function type and an action priority sequence corresponding to the interactive action type;

[0008] Based on the function type, the functional similarity of multiple functions in the function priority sequence is determined; based on the function priority sequence, the action priority sequence and the functional similarity, the function-action matching relationship is determined; based on the function-action matching relationship and the instruction list, the instruction matching relationship is determined; the instruction matching relationship includes an action-instruction-function matching relationship.

[0009] A second aspect of the embodiments of the present disclosure provides a command matching apparatus, which is applied to a wearable device and includes:

[0010] A first calculation module, configured to determine an instruction list based on a function type and an interaction action type;

[0011] a second calculation module, configured to determine, based on historical usage data, a function priority sequence corresponding to the function type and an action priority sequence corresponding to the interactive action type;

[0012] The third calculation module is used to determine the functional similarity of multiple functions in the function priority sequence based on the function type, determine the function-action matching relationship based on the function priority sequence, the action priority sequence and the functional similarity; determine the instruction matching relationship based on the function-action matching relationship and the instruction list; the instruction matching relationship includes the action-instruction-function matching relationship.

[0013] According to a third aspect of an embodiment of the present disclosure, a wearable device is provided, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above-mentioned instruction matching method when executing the computer program.

[0014] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned instruction matching method are implemented.

[0015] The instruction matching method and apparatus, wearable device, and storage medium provided by the embodiments of the present disclosure have the following beneficial effects:

[0016] The disclosed embodiment determines the instruction list based on the function type and the interactive action type, making the instruction planning more systematic and targeted, and accurately covering various function and action combinations, ensuring that the device functions are triggered and executed comprehensively and orderly.

[0017] The disclosed embodiments leverage historical usage data to prioritize functions and actions, fully aligning with user habits and preferences. High-priority functions and actions are prioritized for command matching, improving interaction efficiency and reducing the wait time and complexity of user operations. The disclosed embodiments effectively avoid command confusion and conflict, providing users with a clear, smooth, and stable operating experience even as wearable device functionality continues to grow and interactions become increasingly complex, reducing user learning curves and improving user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1A flowchart of an instruction matching method provided in one embodiment of the present disclosure;

[0020] Figure 2 A structural block diagram of an instruction matching device provided in one embodiment of the present disclosure;

[0021] Figure 3 A schematic block diagram of a wearable device provided in one embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present disclosure. However, it will be apparent to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present disclosure with unnecessary detail.

[0023] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below with reference to the accompanying drawings.

[0024] Please refer to Figure 1 , Figure 1 This is a flow chart of a command matching method provided in one embodiment of the present disclosure. The method is applied to a wearable device and may include S101 to S103.

[0025] S101: Determine an instruction list based on the function type and the interaction action type.

[0026] In this embodiment, wearable devices may include smart glasses, smart helmets, smart bracelets, etc. Functional types are categorized into the functions that can be implemented by wearable devices. Functional types may include multimedia functions, communication functions, health monitoring functions, information interaction functions, system control functions, etc., and specific functional operations are performed under different types.

[0027] Interaction action types are a classification of the ways in which users interact with devices. Interaction action types can include touch actions, voice commands, body movements, etc.

[0028] An instruction list is a set of intermediate identifiers that associates a function type with an interaction action type. An instruction list includes multiple instructions.

[0029] In this embodiment, by sorting out the function types, we can clearly understand what the device can do; by determining the interactive action types, we know how the user operates. Then, based on the possible combinations of different functions and actions, the corresponding instructions are determined. For example, for the music playback function in the entertainment function, if the interactive action is the voice command "play music", the instruction is to launch the music playback software and start playing. This involves the voice recognition module parsing the voice command and connecting with the music playback function module. According to the functional requirements, parameters such as playback mode and volume must also be set.

[0030] For example, the trigger operation type, number of instructions, and number of functions of the wearable device are determined. The hardware and software functional modules of the wearable device are analyzed, classified according to functional characteristics, and organized into a function list, recording information such as function name, function code, and required parameters.

[0031] For interaction methods such as touch and voice, data is collected through touch sensors and microphones, and the data characteristics are analyzed to determine the action type. For example, for touch actions, the touch position, time and other data are obtained through the touch sensor to determine the action types such as click and slide. For voice actions, voice recognition technology is used to identify keywords to determine the voice command type.

[0032] Based on the combination of functions and actions, write code to create an instruction structure or object, including action trigger condition judgment code, corresponding function call code, and function parameter setting code, etc. Store these instructions in an array or linked list to form an instruction list.

[0033] S102: Determine a function priority sequence corresponding to a function type and an action priority sequence corresponding to an interactive action type based on historical usage data.

[0034] In this embodiment, historical usage data refers to user operation information recorded by the wearable device during its past operation. This data may include the time, frequency, and usage scenarios of function usage, as well as the number, sequence, and time of interactive actions. It may also include device operating status information. Historical usage data may also include statistics on trigger operations, matching relationships between commands and functions for various existing wearable devices, the usage frequency of each command, and the usage frequency of each function.

[0035] A function priority sequence ranks different function types based on factors such as importance or frequency of use. For example, different function types in smart glasses are ranked based on a combination of factors such as their historical importance and frequency of use. Function priority sequences can be determined based on frequency of function use, average duration of function use, and the proportion of function use in specific scenarios.

[0036] The action priority sequence is a sequence ranked by factors such as the convenience and frequency of user interaction actions. This can include ranking user interaction actions between the glasses and the user based on factors such as ease of use, error rate, and frequency of use. For example, the frequency of tapping the glasses' frames, the accuracy of voice command recognition, and the difficulty of performing head movements can all be used as parameters to determine the action priority sequence.

[0037] In this embodiment, various parameters about functions and actions in historical usage data are mined, and statistical analysis and weighted algorithms are used to combine multiple factors to calculate priority scores for each function type and action type, and then sort them to form function priority sequences and action priority sequences, so that high-priority function and action combinations are given priority when instructions are matched.

[0038] For example, smart glasses have built-in recorders that record function usage and action data through touch, voice recognition, and communication modules, and store it in local memory or on a storage card. An analysis program is run regularly to extract parameters and calculate priorities. For example, the multimedia function priority score = number of music plays × 0.3 + percentage of video playback time × 0.4 + probability of multimedia use in sports scenes × 0.3; the touch frame click action priority score = click position accuracy × 0.4 + click action execution speed × 0.3 + corresponding function error rate × 0.3. A sequence is generated based on the score sorting and stored for command matching and call.

[0039] S103: Determine the functional similarity of multiple functions in the function priority sequence based on the function type, determine a function-action matching relationship based on the function priority sequence, the action priority sequence, and the functional similarity, and determine an instruction matching relationship based on the function-action matching relationship and the instruction list. The instruction matching relationship includes an action-instruction-function matching relationship.

[0040] In this embodiment, the command matching relationship includes a clear correspondence between the user's interactive actions on the smart glasses, the commands executed by the device, and the multimedia or communication functions ultimately implemented. For example, touching the frame twice corresponds to the "play / pause music" command, thus implementing the multimedia playback function.

[0041] The action-command-function matching relationship specifically describes how each interactive action type triggers a specific command to achieve the corresponding function. Actions can include touch location, frequency, and duration, as well as the content and characteristics of voice commands. Commands can include command codes, priority, and execution conditions. Functions can include function codes, status, and settings.

[0042] Exemplarily, the preferred function category is determined based on the function priority sequence, high-priority actions are screened out in combination with the action priority sequence, and then the actions, instructions, and functions are accurately matched with reference to the instruction list.

[0043] In this embodiment, functional similarity refers to the degree of similarity between different functions in terms of usage, operating logic, etc.

[0044] For example, in the design of smart glasses, the action of long-pressing a button on the side of the frame is used to illustrate. When the smart glasses are in multimedia playback mode, long-pressing the button on the side of the frame can be used to pause or play media content such as music and videos. This is because pausing and playing are the most commonly used operations in the multimedia experience. A simple long-press action can quickly realize media playback control, providing users with a convenient operation experience.

[0045] When the smart glasses are in communication mode, such as during a call, long pressing the side button of the frame can mute or unmute the glasses. Because the mute function is frequently used during calls and is similar to the pause function of multimedia playback, both controlling sound output, similar actions are matched. This design can reduce the user's learning cost, allowing users to quickly learn and accurately operate the smart glasses by memorizing similar actions when switching between different application states, improving the overall user experience and operational efficiency, and reflecting the humanization and intelligence of smart device operation design.

[0046] From the above, it can be concluded that this embodiment determines the instruction list based on the function type and the interactive action type, making the instruction planning more systematic and targeted, and can accurately cover various function and action combinations, ensuring that the device functions are triggered and executed comprehensively and orderly.

[0047] This embodiment leverages historical usage data to prioritize functions and actions, fully aligning with user habits and preferences. High-priority functions and actions are prioritized for command matching, improving interaction efficiency and reducing the wait time and complexity of user operations. This embodiment effectively avoids command confusion and conflict, providing a clear, smooth, and stable user experience even as wearable device functionality continues to grow and interactions become increasingly complex, reducing user learning curves and improving user satisfaction.

[0048] In one embodiment of the present disclosure, determining an instruction list based on a function type and an interaction action type includes:

[0049] The list of features is determined based on the feature type.

[0050] Determine the action list based on the interaction action type and the function list.

[0051] The instruction type is determined based on the interaction action type.

[0052] A first instruction quantity is determined based on the action list and the function list.

[0053] An instruction list is determined based on the instruction type and the first instruction quantity.

[0054] In this embodiment, the function types include communication function and multimedia function.

[0055] Determining a function list based on the function type includes: if the function type is a communication function, determining a communication function list based on the communication function; if the function type is a multimedia function, determining a multimedia function list based on the multimedia function.

[0056] In this embodiment, the interaction action types include touch interaction type and voice interaction type.

[0057] Determine the action list based on the interaction action type and function list, including:

[0058] If the interaction action type is a touch interaction type, a touch action list is determined based on the touch interaction type and the touch dimension.

[0059] If the interaction action type is a voice interaction type, a voice action list is determined based on the voice interaction type and the function list.

[0060] In this embodiment, the function type is a classification and summary of the functions of the wearable smart glasses. Communication functions can include making calls, answering calls, sending text messages, and viewing the address book; multimedia functions can include music playback, video playback, and image browsing.

[0061] Interaction action types categorize how users interact with smart glasses. Touch interaction types can include various touch gestures, such as tap, double-tap, long press, and swipe. Voice interaction types refer to voice commands issued by the user. Parameters related to touch interaction include touch location, touch force, and touch duration. Parameters related to voice interaction include the command's vocabulary, voice intonation, speech speed, and voice recognition accuracy.

[0062] The function list may include a communication function list, a multimedia function list, an AI assistant wake-up function, a mode switching control function, etc. The multimedia function list may include multimedia playback control functions, which may include play and pause, switching tracks or videos, adjusting volume, and AI interactive queries. The communication function list may include communication control functions, which may include answering and hanging up calls, rejecting calls, calling contacts, call volume adjustment, and call recording. The mode switching control function may include communication mode switching functions, such as Bluetooth connection switching and communication network switching.

[0063] The action list is a collection of specific actions generated based on the interaction action type and function list. Each action in the touch action list has parameters such as the corresponding touch area, number of touches, touch trajectory, and touch duration. Each voice command in the voice action list has parameters such as keywords and semantic understanding models.

[0064] In this embodiment, all specific functions are sorted out according to the function type to form a function list, and then the user's possible operation actions are determined according to the interaction action type and the function list to form an action list. At the same time, the category of the instruction is determined according to the interaction action type, and the required number of instructions is calculated through the combination of the action list and the function list. A complete instruction list is generated according to the instruction type and the number of instructions, thereby building an instruction bridge from interaction action to function realization.

[0065] For example, the camera, microphone, display, communication module and software function module of the smart glasses are analyzed, and specific function items are sorted out for communication function and multimedia function respectively, stored in the function list data structure, and relevant data is associated with each function item.

[0066] Touch action: Acquire touch data through the touch sensor, determine the touch action type based on the touch position, number of touches, touch duration, etc., combine with the function list to generate a touch action list, and store the touch actions and related parameters.

[0067] Voice action: Use voice recognition technology to analyze the collected voice signals, combine the function keywords and semantics in the function list, determine the voice command type, generate a voice action list, and store the voice commands and related parameters.

[0068] Determine the command type: Write command processing modules for touch interaction type and voice interaction type respectively, define the command types corresponding to different interaction actions, such as touch click corresponding to selection command, voice playback command corresponding to execution playback function command, and determine the command type and related parameters.

[0069] Traverse the action list and function list, count the number of instructions required for different action and function combinations, and store this number. Based on the instruction type and number of instructions, create an instruction structure or object containing the instruction type, corresponding action, corresponding function, and related parameter information, and store it in the instruction list data structure to complete the instruction list construction.

[0070] This embodiment can accurately match user needs with device functions. By carefully combing through functions and action types, it closely connects instructions with actual usage scenarios, improving operational accuracy and efficiency. This embodiment can enhance the user experience, combining rich touch and voice interaction actions with diverse functions to provide users with convenient, flexible, and natural control methods, reducing learning costs. This embodiment is conducive to system optimization and expansion, with clear instruction types, quantities, and list construction, making it convenient for developers to optimize code and resource allocation in a targeted manner. When functions or interaction methods are updated, the instruction system can be quickly adjusted based on this framework.

[0071] In one embodiment of the present disclosure, the instruction matching method further includes:

[0072] In response to receiving the target trigger action, a target instruction is determined based on the target trigger action, an application state of the wearable device, and an instruction matching relationship.

[0073] In this embodiment, in response to receiving a target trigger action, determining a target instruction based on the target trigger action, an application state of the wearable device, and an instruction matching relationship includes:

[0074] In response to receiving the target trigger action, a target instruction type is determined based on the target trigger action.

[0075] The target function type is determined based on the target instruction type and application status.

[0076] The target instruction is determined based on the target function type and the instruction matching relationship.

[0077] In this embodiment, the target trigger action is a specific interactive action currently performed by the user on the wearable smart glasses, such as touching a certain position of the frame, speaking a specific voice command, etc., which includes the action itself and related parameters.

[0078] The application status of the wearable device may include the application scenario or mode currently running in the smart glasses, such as playing music, being on a call, being in standby mode, etc. The same action in different states may correspond to different instructions.

[0079] The target instruction is the specific instruction to be executed based on the target trigger action, device application status and instruction matching relationship to achieve the corresponding function.

[0080] The target instruction type is the instruction category corresponding to the target-triggered action, such as touch control type, voice query type, etc., and is related to the nature of the action.

[0081] The target function type is the category of the function to be implemented, which is determined based on the target instruction type and application status, such as multimedia function, communication function, etc.

[0082] In this embodiment, upon receiving a target trigger action, the target instruction type is first determined based on the action. The target function type to be achieved is further clarified based on the wearable device's current application state. Finally, based on the established instruction matching relationship, the specific target instruction corresponding to the target function type is found and the corresponding operation is executed.

[0083] For example, a user is using smart glasses to watch a video, and the current application state is that the video is playing. At this time, the user issues a voice command "pause", which is a target trigger action. After receiving the voice command, the smart glasses determine that the target command type is a control command based on this voice command. Combined with the application state of the current video playback and the control command type, it is determined that the target function type is the pause function in the multimedia playback control. Based on the pre-established command matching relationship, the specific command code corresponding to the multimedia playback pause function is found in the command library, such as "MEDIA_PLAY_PAUSE". After receiving the target command, the smart glasses will execute the operation of pausing the video playback. The video screen will stop, and the audio will also pause, waiting for the user's next command, such as continuing to play, fast forward or rewind.

[0084] For example, a user is wearing smart glasses and is in standby mode. At this time, the user double-clicks on the left area of ​​the frame. This touch action is the target trigger action. After the touch sensor of the smart glasses detects the double-click action, it determines that the target instruction type corresponding to this touch action is a selection instruction according to the preset rules. Because it is currently in standby mode, combined with the selection instruction type, the target function type is further determined to be the address book viewing function. According to the instruction matching relationship, the specific instruction corresponding to the address book viewing function is found in the instruction set, such as the "CONTACTS_SHOW" instruction. After the processing system of the smart glasses receives the instruction, the address book list will pop up in the display area of ​​the glasses to facilitate the user to view contact information. If the user performs further operations later, such as clicking on a contact to make a call, the smart glasses will again determine the corresponding target instruction and execute it based on the new target trigger action, application status and instruction matching relationship.

[0085] This embodiment determines the target instruction by comprehensively matching the target trigger action, application state, and instruction. This can accurately match the user's intention and reduce misoperations, such as accurately responding to action instructions in different application scenarios. This embodiment is highly flexible. The same action can perform different functions depending on the application state, meeting diverse needs. For example, the touch action functions are different when in standby mode and when playing a video. This embodiment can enhance the user experience and operate naturally and smoothly. Both voice and touch instructions can be efficiently converted into function execution, allowing users to conveniently control smart glasses, enhancing the practicality and usability of the product, and promoting the popularization and application expansion of smart wearable devices.

[0086] In one embodiment of the present disclosure, the historical usage data includes historical function usage data and historical action usage data.

[0087] Determine the function priority sequence corresponding to the function type and the action priority sequence corresponding to the interaction action type based on historical usage data, including:

[0088] Determine the feature priority sequence corresponding to the feature type based on historical feature usage data.

[0089] Determine the action priority sequence corresponding to the interaction action type based on historical action usage data.

[0090] In this embodiment, historical usage data may include relevant information recorded during the past use of a wearable device (such as smart glasses). This historical usage data may include the user's use of various functions and the interactive actions performed. Historical usage data may also include relevant data statistics for various other products, command matching methods, and so on.

[0091] Historical function usage data is a detailed record of the past use of each function type, including the time, frequency, and duration of use. For example, the duration of each play of the music playback function, the number of calls made by the phone call function, etc.

[0092] Historical action usage data is a record of past user interactions with smart glasses, such as the touch location, number of times, and duration of touch actions, the content of voice commands, and the number of times they are issued.

[0093] The function priority sequence is a sequence formed by sorting each function type based on factors such as its importance and frequency in historical use. Functions with relatively higher priorities will be given priority in processing such as instruction matching.

[0094] The action priority sequence is a sequence sorted by factors such as the convenience and commonness of the interaction action types in historical use. This makes it easier to select actions corresponding to functions, so that frequently used functions are matched with high-priority actions that are simpler and more convenient to operate.

[0095] In this embodiment, determining a function priority sequence corresponding to a function type based on historical function usage data and the function type includes:

[0096] The usage frequency and importance weight coefficient of each function type are determined based on historical function usage data.

[0097] The function priority sequence corresponding to the function type is calculated based on the usage frequency and importance weight coefficient of the function type and the function priority function.

[0098] The feature priority function is:

[0099]

[0100] Among them, let the function type set be F={ ,..., }, represents the i-th function type, express Functional priority, express Length of use, express The number of times it is used, express The importance weight coefficient, n represents the total number of functional types, j represents the index variable corresponding to n functional types, represents the number of times the jth function type is used, Indicates the usage duration of the jth function type.

[0101] In this embodiment, determining the action priority sequence corresponding to the interaction action type based on the historical action usage data includes:

[0102] Based on historical action usage data, the usage frequency, error rate, and operation complexity of each interactive action type are determined.

[0103] The action priority sequence corresponding to the interactive action type is calculated based on the usage frequency, error rate and operation complexity of the interactive action type.

[0104] Exemplary, function priority calculation: regularly analyze historical usage data, count the usage frequency of each function type, combine the importance of the function, calculate the function priority by weighted average method, and generate a function priority sequence.

[0105] Calculating action priorities: Also based on historical usage data, we analyze factors such as frequency of use, error rate, and complexity of each action type. Each action type is assigned a priority value, forming an action priority sequence. Statistical analysis methods and threshold settings can be used to determine action priorities.

[0106] For example, a data logging module built into the operating system of smart glasses records each function usage in detail, such as the duration and frequency of calls made in the communication function, the number of music tracks played and their duration in the multimedia function, and historical action usage data such as the location and number of touch operations and the specific content of voice commands.

[0107] We regularly run data analysis programs to analyze historical function usage data, analyzing parameters such as the frequency of use and total usage time of each function type. We then calculate function priority scores using a weighted average algorithm. For example, if the music playback function accounts for 30% of total usage time and is used frequently, its priority score will be correspondingly higher. This ranking is then used to generate a function priority sequence.

[0108] Historical action usage data is analyzed for usage frequency and accuracy of each interactive action type. For example, if a touch and click action has a 90% accuracy rate and is frequently used, its action priority score is high. This score is then used to determine an action priority sequence. This sequence is then applied to the command matching process, prioritizing the matching of commands corresponding to high-priority functions and actions, thereby optimizing the operational response logic of the smart glasses.

[0109] This embodiment enables smart glasses to better match commands to user habits. Prioritizing high-priority functions with convenient actions reduces the number of steps required and improves response speed. Precise personalized settings make the user experience smoother and more efficient, enhancing the product's practicality and intelligence and improving user satisfaction.

[0110] Corresponding to the instruction matching method of the above embodiment, Figure 2 This is a structural block diagram of an instruction matching device provided by an embodiment of the present disclosure. For ease of explanation, only the parts related to the embodiment of the present disclosure are shown. Figure 2 The instruction matching device 20 is applied to a wearable device and includes: a first calculation module 21, a second calculation module 22 and a third calculation module 23.

[0111] The first calculation module 21 is used to determine an instruction list based on the function type and the interaction action type.

[0112] The second calculation module 22 is configured to determine a function priority sequence corresponding to a function type and an action priority sequence corresponding to an interactive action type based on historical usage data.

[0113] The third calculation module 23 is configured to determine the functional similarity of multiple functions in the function priority sequence based on the function type, determine a function-action matching relationship based on the function priority sequence, the action priority sequence, and the functional similarity, and determine an instruction matching relationship based on the function-action matching relationship and the instruction list. The instruction matching relationship includes an action-instruction-function matching relationship.

[0114] In one embodiment of the present disclosure, the first calculation module 21 is specifically configured to determine a function list based on a function type.

[0115] Determine the action list based on the interaction action type and the function list.

[0116] The instruction type is determined based on the interaction action type.

[0117] A first instruction quantity is determined based on the action list and the function list.

[0118] An instruction list is determined based on the instruction type and the first instruction quantity.

[0119] In one embodiment of the present disclosure, the function type includes a communication function and a multimedia function. The first calculation module 21 is further configured to determine a communication function list based on the communication function if the function type is a communication function.

[0120] If the function type is a multimedia function, a multimedia function list is determined based on the multimedia function.

[0121] In one embodiment of the present disclosure, the interaction action type includes a touch interaction type and a voice interaction type. If the interaction action type is a touch interaction type, a touch action list is determined based on the touch interaction type and the touch dimension.

[0122] If the interaction action type is a voice interaction type, a voice action list is determined based on the voice interaction type and the function list.

[0123] In one embodiment of the present disclosure, the instruction matching device 20 further includes:

[0124] The fourth calculation module is used to determine the target instruction based on the target trigger action, the application state of the wearable device and the instruction matching relationship in response to receiving the target trigger action.

[0125] In one embodiment of the present disclosure, the fourth calculation module is specifically configured to determine the target instruction type based on the target trigger action in response to receiving the target trigger action.

[0126] The target function type is determined based on the target instruction type and application status.

[0127] The target instruction is determined based on the target function type and the instruction matching relationship.

[0128] In one embodiment of the present disclosure, the historical usage data includes historical function usage data and historical action usage data. The second calculation module 22 is specifically configured to determine a function priority sequence corresponding to a function type based on the historical function usage data.

[0129] Determine the action priority sequence corresponding to the interaction action type based on historical action usage data.

[0130] See also Figure 3 , Figure 3 This is a schematic block diagram of a wearable device provided by an embodiment of the present disclosure. Figure 3The wearable device 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of the modules in the above-mentioned device embodiments, such as Figure 2 The functions of modules 21 to 23 are shown.

[0131] It should be understood that in the embodiments of the present disclosure, the processor 301 may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0132] The input device 302 may include a touchpad, a fingerprint collection sensor (for collecting user fingerprint information and fingerprint direction information), a microphone, etc. The output device 303 may include a display (LCD, etc.), a speaker, etc.

[0133] The memory 304 may include a read-only memory and a random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store information about the device type.

[0134] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of the instruction matching method provided in the embodiments of the present disclosure, and can also execute the implementation methods of the wearable device 300 described in the embodiments of the present disclosure, which will not be repeated here.

[0135] In another embodiment of the present disclosure, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program. The computer program includes program instructions. When the program instructions are executed by a processor, all or part of the process of the method in the above embodiment is implemented. The computer program can also be used to instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of each of the above method embodiments are implemented. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium.

[0136] The computer-readable storage medium can be the internal storage unit of the wearable device of any of the aforementioned embodiments, such as the wearable device's hard drive or memory. The computer-readable storage medium can also be an external storage device of the wearable device, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the computer-readable storage medium can include both the wearable device's internal storage unit and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the wearable device. The computer-readable storage medium can also be used to temporarily store data that has been output or is about to be output.

[0137] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0138] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the wearable device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0139] In the several embodiments provided in this application, it should be understood that the disclosed wearable devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces or units, or it can be an electrical, mechanical or other form of connection.

[0140] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the objectives of the embodiments of the present disclosure.

[0141] In addition, the functional units in the various embodiments of the present disclosure may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0142] The above are only specific embodiments of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or replacements within the technical scope disclosed in this disclosure, and such modifications or replacements should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A command matching method, characterized in that: Applied to wearable devices, including: Determine the instruction list based on the function type and the interaction action type; Determine the usage frequency and importance weight coefficient of each function type based on historical function usage data; calculate the function priority sequence corresponding to the function type based on the usage frequency and importance weight coefficient of the function type and the function priority function; The feature priority function is: Among them, let the function type set be F={ ,..., }, represents the i-th function type, express Functional priority, express Length of use, express The number of times it is used, express The importance weight coefficient, n represents the total number of functional types, j represents the index variable corresponding to n functional types, represents the number of times the jth function type is used, Indicates the usage time of the jth function type; Determine the usage frequency, error rate, and complexity of each interactive action type based on historical action usage data; calculate the action priority sequence corresponding to the interactive action type based on the usage frequency, error rate, and complexity of the interactive action type; Determining functional similarity of multiple functions in a functional priority sequence based on the functional type, determining a function-action matching relationship based on the functional priority sequence, the action priority sequence, and the functional similarity; determining an instruction matching relationship based on the function-action matching relationship and the instruction list; the instruction matching relationship includes an action-instruction-function matching relationship; The method further includes: in response to receiving a target trigger action, determining a target instruction based on the target trigger action, an application state of the wearable device, and the instruction matching relationship.

2. The instruction matching method according to claim 1, wherein: The step of determining the instruction list based on the function type and the interaction action type includes: determining a function list based on the function type; determining an action list based on the interaction action type and the function list; Determining an instruction type based on the interaction action type; determining a first instruction quantity based on the action list and the function list; The instruction list is determined based on the instruction type and the first instruction quantity.

3. The instruction matching method according to claim 2, wherein: The functional types include communication functions and multimedia functions; The determining of the function list based on the function type includes: If the function type is a communication function, determining a communication function list based on the communication function; If the function type is a multimedia function, a multimedia function list is determined based on the multimedia function.

4. The instruction matching method according to claim 2, wherein: The interaction action types include touch interaction type and voice interaction type; The determining of the action list based on the interaction action type and the function list includes: If the interaction action type is a touch interaction type, determining a touch action list based on the touch interaction type and the touch dimension; If the interaction action type is a voice interaction type, a voice action list is determined based on the voice interaction type and the function list.

5. The instruction matching method according to claim 1, wherein: The step of determining, in response to receiving a target trigger action, a target instruction based on the target trigger action, an application state of the wearable device, and the instruction matching relationship includes: In response to receiving a target trigger action, determining a target instruction type based on the target trigger action; Determining a target function type based on the target instruction type and the application state; The target instruction is determined based on the target function type and the instruction matching relationship.

6. An instruction matching device, characterized in that: Applied to wearable devices, including: A first calculation module, configured to determine an instruction list based on a function type and an interaction action type; The second calculation module is used to determine the usage frequency and importance weight coefficient of each function type based on the historical function usage data; calculate the function priority sequence corresponding to the function type based on the usage frequency and importance weight coefficient of the function type and the function priority function; The feature priority function is: Among them, let the function type set be F={ ,..., }, represents the i-th function type, express Functional priority, express Length of use, express The number of times it is used, express The importance weight coefficient, n represents the total number of functional types, j represents the index variable corresponding to n functional types, represents the number of times the jth function type is used, Indicates the usage time of the jth function type; Determine the usage frequency, error rate, and complexity of each interactive action type based on historical action usage data; calculate the action priority sequence corresponding to the interactive action type based on the usage frequency, error rate, and complexity of the interactive action type; a third calculation module, configured to determine, based on the function type, functional similarity of multiple functions in a function priority sequence, determine a function-action matching relationship based on the function priority sequence, the action priority sequence, and the functional similarity; and determine an instruction matching relationship based on the function-action matching relationship and the instruction list; the instruction matching relationship including an action-instruction-function matching relationship; The fourth calculation module is configured to, in response to receiving the target trigger action, determine the target instruction based on the target trigger action, the application state of the wearable device, and the instruction matching relationship.

7. A wearable device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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