Intelligent voice interaction method and device of lifting table, lifting table and storage medium

Abstract

The invention relates to an intelligent voice interaction technology, and discloses an intelligent voice interaction method and device of a lifting table, the lifting table and a storage medium, and the method comprises the steps that when the lifting table is powered on and started, a control panel carries out system initialization operation; when the lifting table receives the voice data based on the microphone, the voice data are preprocessed; calling a preset large model to convert the preprocessed voice data into text information, and performing semantic understanding on the text information; analyzing the semantic understanding content, and judging whether the voice instruction described by the voice data belongs to a question and answer instruction or an operation instruction; if the voice instruction is a question and answer instruction, corresponding response information is obtained according to the semantic understanding content, and after the response information is converted into response voice, the response voice is output through a loudspeaker; if the voice instruction is the operation instruction, the lifting table is controlled to execute corresponding operation according to the semantic understanding content. The intelligent lifting table aims at improving the use intelligence and the control convenience of the lifting table.

Description

Technical Field

[0001] This application relates to the field of intelligent voice interaction technology, and in particular to an intelligent voice interaction method, control device, height-adjustable desk, and computer-readable storage medium for a height-adjustable desk. Background Technology

[0002] With the continuous development of technology, height-adjustable desks are being used more and more widely in offices and daily life. Traditional height-adjustable desks primarily focus on adjusting the desktop height to meet the needs of different users for comfortable working or living spaces. However, this traditional functionality is relatively limited, merely altering the height, and fails to meet the higher demands of modern users for intelligent, multifunctional office and living furniture.

[0003] In today's fast-paced work environment, people expect furniture to offer more convenient auxiliary functions. For example, when people's hands are busy processing documents or operating equipment, being able to directly control the height of a height-adjustable desk via voice commands would greatly improve work efficiency. However, traditional height-adjustable desks often require manual operation of buttons or joysticks to achieve height adjustment, which cannot meet this need for voice control.

[0004] Although some height-adjustable desks on the market integrate simple voice modules, these voice modules usually have limited functions, can only perform some preset simple commands, and have simple dialogue logic, which cannot provide a rich, flexible and intelligent interactive experience like talking to a real human.

[0005] Furthermore, in terms of information access, traditional height-adjustable desks cannot directly provide users with practical information such as weather forecasts, schedule reminders, and Q&A. If users need to access this information during work or daily life, they often have to stop what they are doing and pick up their phones or other devices to look it up, which disrupts the flow of work or life and reduces efficiency.

[0006] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0007] The main objective of this application is to provide an intelligent voice interaction method, control device, standing desk, and computer-readable storage medium for a standing desk, aiming to improve the intelligence and ease of control of the standing desk, thereby enhancing the voice interaction experience.

[0008] To achieve the above objectives, this application provides an intelligent voice interaction method for a height-adjustable desk, comprising the following steps: When the height-adjustable table is powered on, the control board performs system initialization to check the operation of the hardware modules configured on the table; these hardware modules include a microphone, speaker, 4G / WiFi module, Bluetooth / ZigBee module, and table leg motors; The height-adjustable desk preprocesses the voice data received by the microphone. The pre-defined large model is invoked to convert the pre-processed speech data into text information, and semantic understanding is performed on the text information. Analyze the semantic understanding content to determine whether the voice commands described by the voice data belong to question-and-answer commands or operation commands; If the voice command is a question-and-answer command, the corresponding response information is obtained based on the semantic understanding content, and the response information is converted into response speech and then output through the speaker. If the voice command is an operation command, the height-adjustable table will be controlled to perform the corresponding operation based on the semantic understanding of the content.

[0009] Optionally, if the voice command is an operation command, the steps of controlling the height-adjustable desk to perform the corresponding operation based on the semantically understood content include: If the voice command is an operation command, then detect the target of the operation command; If the target is a height-adjustable desk, then based on the semantic understanding content, the corresponding control instructions are queried from the control logic of the height-adjustable desk, and the desk is controlled to perform the corresponding operation. And / or, if the target is a smart home device associated with the height-adjustable desk, then based on the semantic understanding content, control commands corresponding to the smart home device are generated and sent to the smart home device to control the smart home device to perform corresponding operations; wherein, the height-adjustable desk is associated with the smart home device and establishes a communication connection based on a 4G / WiFi module or a Bluetooth / ZigBee module.

[0010] Optionally, the intelligent voice interaction method for the height-adjustable desk further includes: If the semantically understood content is detected to be associated with the environmental data collected by smart home devices, it is determined that the target is the smart home device that has collected the relevant environmental data; Among them, smart home devices equipped with environmental data acquisition sensors will share the collected environmental data with the height-adjustable desk.

[0011] Optionally, the hardware module further includes a touchscreen for: Touchscreen operation of height-adjustable desks and / or smart home devices; Displays the status parameters and / or environmental data of the height-adjustable desk; Provides a voice interaction interface; Provides a personalized settings interface.

[0012] Optionally, after the step of calling a pre-set large model to convert the preprocessed speech data into text information and performing semantic understanding on the text information, the method further includes: If the semantically understood content is detected to be related to the user's control habits, the control commands of the height-adjustable desk and / or smart home devices associated with the user's control habits are obtained, and the height-adjustable desk and / or smart home devices are controlled to perform the corresponding operations.

[0013] Optionally, if the voice command is an operation command, after controlling the height-adjustable table to perform the corresponding operation based on the semantic understanding content, the method further includes: If a command to save control habits is received, user control habits are generated based on the current semantic understanding content and the control commands of the height-adjustable desk and / or smart home devices.

[0014] Optionally, before the step of controlling the height-adjustable table to perform the corresponding operation based on semantic understanding of the content, if the voice command is an operation command, the following further step is included: If the current voice command is an operation command and the previous voice command was a question-and-answer command, and the question-and-answer content associated with the question-and-answer command is detected to be related to the current semantic understanding content, then the semantic understanding content is updated based on the question-and-answer content.

[0015] To achieve the above objectives, this application also provides a control device, comprising: The initialization module is used to perform system initialization operations on the control board when the height-adjustable table is powered on and started, in order to detect the operating status of the hardware modules configured on the height-adjustable table; the hardware modules include a microphone, speaker, 4G / WiFi module, Bluetooth / ZigBee module and table leg motors; The preprocessing module is used to preprocess the voice data received by the microphone when the height-adjustable desk is adjusted. The large model module is used to call a pre-defined large model to convert the pre-processed speech data into text information and perform semantic understanding on the text information; The analysis module is used to analyze the semantic understanding content and determine whether the voice commands described by the voice data belong to question-and-answer commands or operation commands. The response module is used to obtain the corresponding response information based on the semantic understanding content if the voice command is a question-and-answer command, and then convert the response information into response speech and output the response speech through the speaker. The operation module is used to control the height-adjustable table to perform the corresponding operation based on the semantic understanding of the content if the voice command is an operation command.

[0016] To achieve the above objectives, this application also provides a height-adjustable desk, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the intelligent voice interaction method of the height-adjustable desk described above.

[0017] To achieve the above objectives, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the intelligent voice interaction method for the height-adjustable desk described above.

[0018] The intelligent voice interaction method, control device, standing desk, and computer-readable storage medium provided in this application are based on artificial intelligence technology. The standing desk uses an advanced large model for voice data processing, which can accurately convert speech into text and deeply understand semantics. Based on this, voice question and answer and voice control can be performed, which can improve the intelligence of the standing desk and the convenience of its control, thereby improving the user's voice interaction experience with the standing desk. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the steps of an intelligent voice interaction method for a height-adjustable table in one embodiment of this application; Figure 2 This is a schematic diagram of the control device in one embodiment of this application; Figure 3 This is a schematic diagram of the internal architecture of the controller board of a height-adjustable table according to an embodiment of this application.

[0020] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0022] Furthermore, descriptions using terms such as "first" and "second" in this application are for descriptive purposes only (e.g., to distinguish identical or similar features) and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, technical solutions from different embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If a combination of technical solutions is contradictory or impossible to implement, such a combination should be considered nonexistent and not within the scope of protection claimed in this application.

[0023] Reference Figure 1 In one embodiment, the intelligent voice interaction method for the height-adjustable desk includes: Step S10: When the height-adjustable table is powered on, the control board performs system initialization to detect the operating status of the hardware modules configured on the height-adjustable table; the hardware modules include a microphone, speaker, 4G / WiFi module, Bluetooth / ZigBee module and table leg motors; Step S20: When the height-adjustable table receives voice data based on the microphone, it preprocesses the voice data. Step S30: Call the pre-set large model to convert the preprocessed speech data into text information, and perform semantic understanding on the text information; Step S40: Analyze the semantic understanding content and determine whether the voice command described by the voice data belongs to a question-and-answer command or an operation command; Step S50: If the voice command is a question-and-answer command, obtain the corresponding response information based on the semantic understanding content, convert the response information into response speech, and output the response speech through the speaker; Step S60: If the voice command is an operation command, then control the height-adjustable table to perform the corresponding operation based on the semantic understanding of the content.

[0024] In this embodiment, the execution terminal can be a height-adjustable table or other devices or apparatuses (such as control devices) that control the height-adjustable table.

[0025] As described in step S10, the control board of the height-adjustable desk, in addition to serving as the core hub of the entire intelligent function of the height-adjustable desk, retains the basic circuit (including the table leg motor interface) and controller for controlling the lifting of the desktop of the traditional height-adjustable desk, and adds several key functional modules and interfaces, which are connected to the controller of the control board.

[0026] On the control board, the MIC (Microphone Interface) interface is carefully laid out to ensure that the microphone can be stably and efficiently connected to the controller, enabling accurate voice collection. At the same time, a dedicated power amplifier circuit and speaker interface are configured for sound output to ensure that the output voice is clear and loud, meeting the volume requirements of users for voice playback in different usage scenarios. In addition, a 4G / WiFi module interface is reserved on the control board. Through this interface, the corresponding wireless communication module can be conveniently connected to achieve the network connection function. Finally, a Bluetooth / ZigBee module is also carried on the control board, and different smart furniture devices can be interconnected through Bluetooth mesh or ZigBee networking.

[0027] Optionally, the control board can also be configured with a touch screen.

[0028] The above-mentioned functional modules and interfaces are all electrically connected to the controller of the control board and are controlled by the controller.

[0029] Regarding the 4G / WiFi module, the WiFi module can select a mature low-power and high-bandwidth wireless chip on the market and be connected to the control board by welding or plug-and-play. In actual application scenarios, users can conveniently set the account and password of the WiFi connection through the mobile phone APP or the touch screen interface to achieve a quick connection to the home or office network. The 4G module is equipped with a corresponding SIM card slot and is well protected against water and dust. The advantage of the 4G module is that it is not restricted by the WiFi network coverage. Even in an environment without WiFi, the lifting table can still access the cloud large model through the 4G network and maintain the normal operation of the intelligent voice dialogue function.

[0030] Regarding the Bluetooth / ZigBee module, a standard Bluetooth / ZigBee module interface is reserved on the basis of the original control board. For the Bluetooth module, a chip that supports Bluetooth version 5.0 and above can be selected to ensure high-speed and stable data transmission and a longer transmission distance. The ZigBee module selects a chip that complies with the ZigBee 3.0 protocol to ensure compatibility with various ZigBee devices.

[0031] Touch screen (optional): If a touch screen is selected to be added, the touch screen can be adhered to the surface of the tabletop or a separate operation panel can be designed and installed at an easy-to-operate position such as the side of the table leg or the edge of the tabletop. The touch screen is connected to the control board through a flexible cable to achieve data transmission and interactive control. The touch screen needs to have a high-sensitivity touch response ability to meet the fast and accurate operation needs of users. At the software level, a simple and clear interactive interface is designed for the touch screen, including intuitive lifting control buttons, intelligent voice dialogue entrances, various function setting menus, etc., to facilitate users to achieve diverse function control through touch operations.

[0032] When the height-adjustable desk is powered on and starts up, the control board first performs system initialization. During initialization, the system sequentially checks the operational status of the hardware modules configured on the desk, verifying whether the hardware modules are properly connected and functioning correctly. These hardware modules include a microphone, speaker, 4G / WiFi module, touchscreen (if equipped), Bluetooth / ZigBee module, and table leg motors. If a hardware device is detected to be faulty, the system will provide the user with the corresponding fault information via speakerphone, and simultaneously display detailed fault diagnosis and solutions on the touchscreen, facilitating quick troubleshooting for the user.

[0033] As described in step S20, when the user issues a voice command, the height-adjustable desk collects the voice signal using a microphone, converts the collected voice signal into a digital signal, and transmits it to the control board. The voice processing chip on the control board performs preliminary noise reduction, filtering, and other preprocessing operations on the collected voice data to improve the quality of the voice signal.

[0034] As described in step S30, the pre-set large model is then invoked to convert the preprocessed speech data into text information, and semantic understanding is performed on the text information. The large model can be a lightweight model deployed locally. This large model can be pre-trained on a device with sufficient computing power using a large amount of speech and text data to acquire powerful speech recognition and semantic understanding capabilities before being lightweight compressed and transferred to an adjustable desk. If network conditions permit, a large model deployed on a cloud server can also be invoked, i.e., the data is sent to the cloud server via a network connection and connected to a pre-set large model, such as Doubao or Deepseek.

[0035] The large model first extracts features from the preprocessed speech data. Speech signals are essentially continuous time-series signals containing rich acoustic features such as pitch, duration, timbre, and energy. The large model uses specific algorithms and techniques to extract these key acoustic features from the speech data, transforming them into feature vectors that the model can understand and process. These feature vectors reflect the acoustic characteristics of speech, providing a foundation for subsequent recognition.

[0036] Large models utilize the parameters and structure acquired during training to infer and compute the extracted feature vectors. During training, the model learns a large number of mapping relationships between speech and corresponding text. Through these mapping relationships, the model analyzes and matches the input feature vectors to predict the most likely corresponding text sequence. This process involves complex neural network computations, including multi-layered convolutions, recurrent loops, and attention mechanisms to fully capture the semantic information in the speech data.

[0037] After model inference, a preliminary text sequence prediction result is obtained. However, this result may contain certain errors or uncertainties. Therefore, decoding algorithms are needed to further process and optimize the prediction result. Common decoding algorithms include Viterbi algorithm and beam search, which combine the knowledge of the language model, consider the grammatical and semantic relationships between characters, and select the most reasonable text sequence as the final recognition result. Finally, this text sequence is output, completing the conversion from speech data to text information.

[0038] The large model performs part-of-speech tagging on the converted text information, that is, determining the part of speech of each word in the sentence, such as noun, verb, adjective, adverb, etc. Part-of-speech tagging helps to understand the structure and grammar of the sentence, providing a foundation for subsequent semantic analysis. By identifying the part of speech of words, we can clarify the role and function of words in the sentence, thereby better grasping the overall meaning of the sentence.

[0039] Building upon part-of-speech tagging, the large model performs syntactic analysis, examining the sentence's structure and components to determine the grammatical relationships between words, such as subject-verb-object, attributive, adverbial, and complement. Syntactic analysis helps the model understand the sentence's hierarchy and logical structure, clarifying the relationships between words within the sentence, thus enabling a more accurate grasp of the sentence's semantics.

[0040] The large model combines pre-trained semantic knowledge with contextual information to perform semantic parsing of textual information. The purpose of semantic parsing is to understand the actual meaning expressed by the sentence, including identifying the topic, intention, and emotion within the sentence. The model breaks down sentences into semantic units based on the semantic and grammatical structure of words, analyzes the relationships between these units, and thus infers the user's true intention. For example, if a user says "raise the table by 10 centimeters," the model can recognize through semantic parsing that this is an instruction, and the intention is to raise the table by 10 centimeters.

[0041] To more accurately understand semantics, the large model also matches the parsed semantic information with a knowledge base for height-adjustable desks. This knowledge base contains various technical parameters, operating procedures, and frequently asked questions about height-adjustable desks. For example, if a user asks, "What is the maximum weight the desk can bear?", the model will search the knowledge base for information about the desk's maximum weight capacity and add it to the semantic understanding result to more accurately respond to the user's question.

[0042] As described in step S40, a rule base is established, which contains feature rules for question-and-answer instructions and operation instructions respectively. For question-and-answer instructions, the rules may cover specific interrogative words, such as "what," "why," "how," "how much," "how long," etc. For example, sentences such as "What is the maximum weight capacity of the height-adjustable desk?" and "Why does the height-adjustable desk make noise?" contain obvious interrogative words and conform to the feature rules of question-and-answer instructions.

[0043] For operation instructions, the rules will contain keywords indicating actions, such as "rise," "fall," "stop," and "adjust to." For example, statements such as "raise the table to 80 centimeters" and "stop the table from falling" contain operation-related keywords and belong to the feature rules of operation instructions.

[0044] The semantically understood text information is compared one by one with the rules in the rule base. The system scans the text information to check for the presence of feature keywords defined in the rule base. If it finds a question word, it determines that the voice command may be a question-and-answer command; if it finds a keyword for an operation action, it determines that it is an operation command.

[0045] As described in step S50, after determining that the voice command is a question-and-answer command, the corresponding response information is obtained according to the semantic understanding content, converted into response voice, and output through the speaker.

[0046] A local knowledge base is pre-built in the height-adjustable desk system, storing various common questions related to the desk and their corresponding answers. This knowledge includes the desk's technical parameters (such as maximum load capacity, height adjustment speed, and adjustment range), user manuals (such as how to turn it on and off, and how to perform routine maintenance), and troubleshooting methods (such as solutions to problems like jamming and noise).

[0047] The semantically understood text information is matched against questions in the local knowledge base. The system uses methods such as keyword matching and semantic similarity calculation to find the question record most similar to the user's question. For example, if a user asks "What is the maximum weight capacity of an adjustable desk?", the system will search the knowledge base for records containing the keyword "maximum weight capacity" and find the corresponding answer.

[0048] If no matching answer is found in the local knowledge base, the system can connect to the Internet via a 4G / WiFi module and use a search engine or professional knowledge platform to search; or, it can call an artificial intelligence question-answering model to obtain response information.

[0049] The system integrates a text-to-speech (TTS) engine, which can convert the acquired response information into speech signals. In practical applications, appropriate TTS engines can be selected according to different needs, such as engines with different timbres, speech rates, and intonations, to meet the diverse auditory experiences of users.

[0050] The TTS engine synthesizes speech based on the input response information and according to the set parameters. The engine converts the text information into corresponding audio signals, a process involving processing of speech rhythm and pronunciation to generate natural and fluent speech. Next, the converted response audio file is transmitted to the speakers on the height-adjustable desk. The system uses its internal audio transmission channel to ensure that the audio signal is accurately transmitted to the speakers.

[0051] Optionally, during the playback of the response voice through the speaker, the system can provide playback status prompts to the user through indicator lights, screen displays, etc., letting the user know that the voice is playing or has finished playing. If the user inputs a new voice command during playback, the system will process it accordingly based on the command type, such as pausing playback, resuming playback, or switching content, to achieve real-time interaction with the user.

[0052] As described in step S60, after determining that the voice command is an operation command, the height-adjustable table is controlled to perform the corresponding operation based on the semantic understanding content.

[0053] First, the system performs a detailed analysis of the semantically understood textual information to extract key information related to the operation. This key information includes the operation action and the target parameter. For example, for the instruction "raise the table to 80 centimeters," "raise" is the operation action, and "80 centimeters" is the target parameter.

[0054] If the instructions are complex, the system will use natural language processing technology to extract the key elements. For example, if the instruction is "lower the table to 60 centimeters and then raise it by 10 centimeters", the system can accurately parse the two actions of "lowering" and "raising", as well as the two target parameters of "60 centimeters" and "raising by 10 centimeters (i.e., the final height is 70 centimeters)".

[0055] Based on the extracted key information, the system will plan the specific operation process. If the operation involves multiple steps, the system will determine the order of the operations. Taking "first descend to 60 cm, then ascend 10 cm" as an example, the system will first plan to perform the descent operation to 60 cm, and then perform the ascent operation to 10 cm.

[0056] For operations involving multiple conditions or constraints, the system will also make reasonable plans. For example, if the command is "raise the table to 75 centimeters when there is sufficient light nearby", the system will first determine whether the light conditions are met, and then execute the raising operation.

[0057] Simultaneously, the system checks whether the operating commands comply with the hardware capabilities and safety specifications of the height-adjustable desk. For target parameters, it verifies whether they are within the adjustable range of the desk. For example, if the adjustment range of the desk is 60-120 cm, and the command requests adjustment to 150 cm, the system will determine that the command is invalid.

[0058] In addition, it will check whether the operation is consistent with physical logic. For example, if the table is already at its lowest position and a "continue to descend" instruction is received, the system will determine that the instruction is unreasonable.

[0059] If other operations or pre-defined tasks are currently in progress in the system, the system will check whether the new operation instruction will conflict with them. For example, if a table is being raised and a lowering instruction is received, the system needs to determine how to handle this conflict. It may prioritize executing the latest instruction and stop the current operation, or it may coordinate according to pre-defined rules.

[0060] Verified operation commands are converted into control signals for the table leg motors. The system calculates the required direction, speed, and time for the motors based on the operation and target parameters. For example, a forward rotation control signal is generated for a rising operation, and a reverse rotation control signal is generated for a lowering operation.

[0061] The strength and duration of the control signal are precisely adjusted according to the target parameters. To rise to a specific height, the system calculates the number of revolutions and the time required for the motor to rotate based on the motor's speed and gear ratio, ensuring that the table accurately reaches the target position.

[0062] Control signals are sent to the drive module of the table leg motor, which then drives the motor to operate. The motor drives the mechanical structure of the table legs to raise, lower, or stop the table.

[0063] During operation, the system monitors the motor's operating status in real time, such as current and speed, to ensure normal operation. If any abnormality is detected, such as excessive current or unstable speed, the system will take timely measures, such as stopping operation and issuing an alarm.

[0064] Once the operation is complete, the system will provide feedback to the user via speaker. For example, it might say, "The table has been raised to 80 centimeters," letting the user know whether the operation was successful.

[0065] Meanwhile, the system can also provide users with intuitive feedback on the operation results through indicator lights, screen displays, and other means. If the operation fails, the system will clearly state the reason for the failure, such as "Operation failed, target height exceeds the adjustment range".

[0066] In this way, users can not only adjust the height of the table legs by voice control, but also perform operations such as weather inquiries, schedule reminders, and Q&A, meeting the needs of modern fast-paced life and office work for convenient information access and diverse operations.

[0067] In terms of interactive experience, it uses an advanced large model for voice data processing. Compared with simple voice modules on the market, it can accurately convert speech into text and deeply understand semantics. The dialogue logic is more intelligent and flexible, just like communicating with a real person, bringing users a more natural and smooth interactive experience.

[0068] In terms of efficiency improvement, users no longer need to manually operate buttons or put down their tasks to use other devices; they can simply use voice commands to operate or retrieve information, avoiding interruptions to their work and life rhythms and greatly improving efficiency. Furthermore, the device performs operational checks on the hardware modules upon power-on, ensuring stable operation and providing users with a reliable experience.

[0069] In one embodiment, the height-adjustable desk is based on artificial intelligence technology and uses an advanced large model for voice data processing. It can accurately convert speech into text and deeply understand semantics. Based on this, it can perform voice question and answer and voice control, which can improve the intelligence of the height-adjustable desk and the convenience of its control, thereby improving the user's experience of voice interaction with the height-adjustable desk.

[0070] In one embodiment, based on the above embodiments, the step of controlling the height-adjustable table to perform the corresponding operation according to the semantically understood content, if the voice command is an operation command, includes: If the voice command is an operation command, then detect the target of the operation command; If the target is a height-adjustable desk, then based on the semantic understanding content, the corresponding control instructions are queried from the control logic of the height-adjustable desk, and the desk is controlled to perform the corresponding operation. And / or, if the target is a smart home device associated with the height-adjustable desk, then based on the semantic understanding content, control commands corresponding to the smart home device are generated and sent to the smart home device to control the smart home device to perform corresponding operations; wherein, the height-adjustable desk is associated with the smart home device and establishes a communication connection based on a 4G / WiFi module or a Bluetooth / ZigBee module.

[0071] In this embodiment, once the system determines that the received voice command is an operation command, its primary task is to identify the target of that operation command. This is because the operation command may be directed at the height-adjustable desk itself or at a smart home device associated with the desk. The system will further analyze the semantic understanding content to identify the specific target object mentioned. For example, if the user says "raise the height-adjustable desk by 20 centimeters," the system can clearly identify the target as the height-adjustable desk through semantic understanding; if the user says "turn on the living room light associated with the height-adjustable desk," the system can determine that the target is the smart home device (living room light) associated with the desk.

[0072] Specifically, the operation is for when the target is a height-adjustable desk: The control logic of an adjustable desk is a set of pre-defined rules and procedures that define the control commands corresponding to different operations. Once the target of the operation command is determined to be the adjustable desk, the system will search within this control logic based on semantic understanding. For example, if semantic understanding determines that the user's voice command is "lower the adjustable desk to the lowest position," the system will search the control logic for the control command corresponding to "lower to the lowest position." This is similar to looking up the specific steps of a particular operation in an instruction manual.

[0073] Once the corresponding control command is found in the control logic, the system immediately sends it to the relevant hardware modules, such as the table leg motors. Upon receiving the command, the table leg motors will act accordingly. For example, to lower the table to its lowest position, the table leg motors will drive the legs down until the table reaches the lowest position. During this process, the control board monitors the operating status of the table leg motors in real time to ensure the accuracy and safety of the operation. If any abnormality occurs during operation, such as motor failure or reaching a limit, the control board will take appropriate measures, such as stopping the motors and issuing an alarm.

[0074] Specifically, the operation when the target is a smart home device associated with a height-adjustable desk: When an operation command targets a smart home device associated with the height-adjustable desk, the system generates the corresponding control command for that smart home device based on semantic understanding. Different smart home devices have different control protocols and command formats. For example, common control commands for smart lights might include turning on, turning off, and adjusting brightness; for smart curtains, control commands might include opening, closing, and stopping. The system determines the specific operation requirement based on semantic understanding and then generates the corresponding command according to the control protocol of the smart home device. For example, if a user says, "Adjust the brightness of the bedroom smart light associated with the height-adjustable desk to 50%", the system will generate the control command "Set the brightness to 50%" based on the smart light's control protocol.

[0075] The height-adjustable desk establishes a communication connection with smart home devices via a 4G / WiFi module or a Bluetooth / ZigBee module. After generating control commands, the system sends the commands to the corresponding smart home devices through these communication connections. For example, if connected via WiFi, the system sends the control commands as network data packets to the network where the smart home device is located. After receiving the command, the smart home device parses the command content and executes the corresponding operation. Similarly, taking smart lights as an example, when it receives the command "set the brightness to 50%", it will adjust its own brightness to 50%. Throughout the process, the system monitors the sending and execution of commands. If any abnormalities occur, such as sending failure or device unresponsiveness, it will attempt to resend the command or perform appropriate error handling.

[0076] In one embodiment, the system can accurately detect the target of operation commands, improving the accuracy and flexibility of voice interaction. Users can control multiple devices through a single system, making the process convenient and smooth. When operating the height-adjustable desk, the system queries commands based on preset control logic, ensuring standardized and stable operation with high repeatability and consistency. Furthermore, it can connect to smart home devices through various communication modules, generating and sending control commands to achieve integrated control of multiple devices, expanding the functionality of the height-adjustable desk and creating a smart living environment.

[0077] In one embodiment, based on the above embodiments, the intelligent voice interaction method for the height-adjustable desk further includes: If the semantically understood content is detected to be associated with the environmental data collected by smart home devices, it is determined that the target is the smart home device that has collected the relevant environmental data; Among them, smart home devices equipped with environmental data acquisition sensors will share the collected environmental data with the height-adjustable desk.

[0078] In this embodiment, in a smart living scenario, some smart home devices are equipped with environmental data acquisition sensors. These sensors can collect various environmental data in real time, such as: (1) Temperature and humidity sensor: Smart air conditioners, smart humidifiers and other devices can be equipped with temperature and humidity sensors to collect indoor temperature and humidity data. For example, in summer, the indoor temperature may reach above 30°C and the humidity may be around 60%, and these data will be collected by the device.

[0079] (2) Light sensor: Smart curtains and smart lighting devices can be equipped with light sensors to detect indoor light intensity. During the day when there is plenty of sunlight, the indoor light intensity may reach several thousand lux; while at night, the light intensity may be almost zero.

[0080] (3) Air quality sensor: Air purifiers, fresh air systems and other equipment can be equipped with air quality sensors to monitor indoor air quality, such as PM2.5 concentration and formaldehyde content. If someone smokes indoors, the PM2.5 concentration may rise rapidly.

[0081] Smart home devices equipped with these environmental data acquisition sensors will establish a communication connection with the standing desk via 4G / WiFi modules or Bluetooth / ZigBee modules, and share the collected environmental data with the standing desk. The control panel of the standing desk will receive and display this environmental data so that users can understand the environmental conditions.

[0082] Once the adjustable desk receives a user's voice command and completes semantic understanding, the system will further analyze the semantic understanding to see if it is related to environmental data collected by smart home devices. For example: The user says, "Adjust the air conditioner temperature around the height-adjustable desk according to the current indoor temperature." The semantically understood content clearly mentions an operation related to the environmental data of indoor temperature. At this point, the system will detect that the semantically understood content is associated with the temperature data collected by the smart air conditioner.

[0083] When a user says, "When the light intensity reaches a certain level, adjust the state of the curtains near the lift table," the system will find that the semantic understanding content is related to the light intensity data collected by the smart curtains.

[0084] Once the system detects a correlation between semantically understood content and environmental data collected by smart home devices, it determines that the target is the smart home device that collected the relevant environmental data. The system will then determine which smart home device(s) collected this data based on the type of associated environmental data. For example, if the associated data is temperature data, then the smart air conditioner that collected that temperature data will be identified as the target.

[0085] The system will further determine the operation to be performed on the smart home device based on the specific requirements in the semantic understanding content. For example, in the example of "adjusting the air conditioner temperature around the height-adjustable table according to the current indoor temperature", the system will generate a control command to adjust the air conditioner temperature based on the current indoor temperature and semantic requirements, and send it to the smart air conditioner.

[0086] In one embodiment, intelligent linkage between the height-adjustable desk and smart home devices is realized, which can automatically control related devices based on environmental data and user voice commands, thereby improving the level of intelligence in home life.

[0087] Optionally, personalized services can be provided to users based on different environmental data and user needs. For example, the air conditioning temperature can be automatically adjusted according to the indoor temperature to keep users in a comfortable environment at all times.

[0088] In this way, users do not need to manually operate each smart home device separately. They can simply interact with the lift-up table by voice to achieve coordinated control of multiple devices, improving the convenience and efficiency of life.

[0089] In one embodiment, based on the above embodiments, the hardware module further includes a touchscreen, used for: Touchscreen operation of height-adjustable desks and / or smart home devices; Displays the status parameters and / or environmental data of the height-adjustable desk; Provides a voice interaction interface; Provides a personalized settings interface.

[0090] In this embodiment, the touchscreen serves as an intuitive interactive interface, allowing users to send control commands to the height-adjustable table or associated smart home devices by touching virtual buttons, icons, or making swipe gestures on the screen. Its operation logic is simple and easy to understand, requiring no complex learning process.

[0091] Optionally, users can adjust the height of the height-adjustable desk by tapping the "Up" and "Down" icons on the touchscreen. They can also set specific height values ​​to allow the desk to stop precisely at the target position. For example, if a user wants to adjust the desk to a comfortable standing height while working, they simply need to enter the preset standing height value on the touchscreen, and the desk will automatically rise or fall to that position.

[0092] Optionally, users can also operate smart home devices associated with the height-adjustable table, such as smart lights, smart curtains, and smart air conditioners, on the touchscreen. For example, by tapping the light icon on the screen, users can select "on," "off," or adjust the brightness; by tapping the curtain icon, users can control the opening and closing of the curtains; and users can also set parameters such as the air conditioner's temperature and mode.

[0093] Optionally, the touchscreen can display various status parameters of the height-adjustable desk in real time, such as current height, lifting speed, and battery level (if the desk is electric and battery-powered). Users can check this information at any time to understand the desk's working status. For example, during the lifting process, the screen will dynamically display the height change value, allowing users to clearly understand the lifting progress.

[0094] Because smart home devices equipped with environmental data collection sensors share the collected environmental data with the standing desk, this data is also displayed on the touchscreen. This data includes indoor temperature, humidity, light intensity, and air quality (such as PM2.5 concentration and formaldehyde levels). By viewing this data, users can intuitively understand the surrounding environmental conditions and adjust the standing desk or related smart home devices accordingly. For example, if the indoor temperature is too high, the user can use the touchscreen to operate the smart air conditioner to lower the temperature.

[0095] Optionally, the touchscreen will provide a dedicated voice interaction interface, typically marked with a microphone icon. Users can tap this icon to begin voice input. The interface may display prompts to guide the user to clearly and accurately speak the command, such as "Please speak your command." After the user's voice input, the touchscreen will display the recognized voice command in text form on the interface, allowing the user to confirm accurate recognition. Simultaneously, when the system executes the command, corresponding feedback information will be displayed on the interface to inform the user of the result. For example, if the user's voice command is "Raise the height-adjustable desk by 10 centimeters," the screen will display the command, and after the desk has been raised, the screen will display "Height-adjustable desk raised by 10 centimeters." This interface can also provide voice interaction settings, such as adjusting voice recognition sensitivity and toggling voice prompts. Users can personalize these settings according to their usage habits and environmental conditions for a better voice interaction experience.

[0096] Optionally, users can customize the functions of the height-adjustable desk in the personalized settings interface. For example, they can set multiple commonly used height presets for quick height adjustment in different usage scenarios; they can also set parameters such as lifting speed and sound effects during lifting. Users can adjust the desk to their most suitable usage mode based on their height, work habits, and other factors. Furthermore, users can set linkage rules between the desk and smart home devices in this interface, such as automatically turning on smart lights when the desk reaches a specific height, or automatically adjusting the desk's angle when indoor light intensity reaches a certain level. Through these personalized settings, users can create a smart living scenario tailored to their needs.

[0097] In one embodiment, based on the above embodiments, after the step of calling a pre-set large model to convert the preprocessed speech data into text information and performing semantic understanding on the text information, the method further includes: If the semantically understood content is detected to be related to the user's control habits, the control commands of the height-adjustable desk and / or smart home devices associated with the user's control habits are obtained, and the height-adjustable desk and / or smart home devices are controlled to perform the corresponding operations.

[0098] In this embodiment, after semantically understanding the voice commands, the system compares and analyzes the semantically understood content with pre-recorded user control habit data. This user control habit data is formed by recording user actions on the height-adjustable desk and smart home devices over a long period. For example, around 10 AM each day, the user typically raises the desk to a standing height and opens the corresponding smart curtains to increase indoor lighting; around 3 PM, they lower the desk to a seated height and turn on the smart air conditioner to adjust the temperature. The system establishes a correlation model between time, scenario, and operation commands.

[0099] After receiving a new voice command and completing semantic understanding, the system will determine whether it is related to the user's control habits based on key information in the semantic content, such as time, operation type, and scene description. For example, if a user issues the voice command "adjust to a suitable state" at 10:00 AM, the system will determine, through semantic understanding and the user's control habits, that the command is related to the user's usual operation habits at 10:00 AM, such as raising the height-adjustable table or opening the smart curtains.

[0100] Once the system detects that the semantically understood content is associated with the user's control habits, it immediately retrieves the corresponding control commands from the stored user control habit data. These control commands are records of operations performed by the user in similar scenarios, which have been organized and stored. For example, based on the scenario association of 10:00 AM mentioned above, the system will retrieve the two control commands: "raise the height-adjustable desk to standing work height" and "open the smart curtains corresponding to the window".

[0101] After retrieving the control commands, the system adapts and optimizes them based on the current situation. For example, considering the weather, if it's cloudy, the brightness of the smart lights might be increased appropriately; if the indoor temperature is already comfortable, the set temperature of the smart air conditioner might be adjusted. This ensures that the control commands better meet the user's actual needs in the current scenario.

[0102] Optionally, the system will acquire and optimize control commands and send them to the relevant hardware modules of the height-adjustable table (such as the control board for the table leg motors) and corresponding smart home devices. Wired or wireless communication methods, such as WiFi, Bluetooth, and ZigBee, will be used to ensure that the commands are accurately transmitted to the target devices.

[0103] Upon receiving control commands, the height-adjustable desk and smart home devices will immediately execute the corresponding operations. During operation, the devices will provide real-time feedback on their execution status to the system. For example, the control panel of the height-adjustable desk will provide feedback on the operation of the desk leg motors, and smart curtains will provide feedback on their opening and closing status. The system will monitor and adjust based on the feedback information. If any abnormalities occur, such as device malfunctions or command execution deviations, appropriate measures will be taken promptly, such as issuing alarms, resending commands, or prompting the user to check.

[0104] In one embodiment, taking into full account user habits, the system can automatically execute corresponding operations based on the user's daily operating patterns, providing personalized intelligent services and improving user satisfaction and comfort. Users do not need to issue detailed operation commands every time; they only need to express their needs, and the system can automatically complete a series of operations based on their habits, saving users time and effort and improving efficiency in life and work. The system adapts and optimizes control commands according to actual conditions, better adapting to different scenarios and environmental changes, making the device operation more intelligent and precise.

[0105] In one embodiment, based on the above embodiments, after the step of controlling the height-adjustable table to perform the corresponding operation according to the semantic understanding content if the voice command is an operation command, the method further includes: If a command to save control habits is received, user control habits are generated based on the current semantic understanding content and the control commands of the height-adjustable desk and / or smart home devices.

[0106] In this embodiment, after the user controls the height-adjustable table to perform corresponding operations via voice commands, the system continuously listens for new voice commands. When it receives a command related to "saving control habits," the system recognizes that this is a command requesting the saving of the current operating mode as a control habit. For example, after adjusting the height-adjustable table to a specific height and simultaneously turning on the associated smart lights and curtains, the user says "save current operating habits," and the system captures this command and enters the process of saving the user's control habits.

[0107] The system extracts semantic understanding content from previously processed voice operation commands. This semantic understanding content includes key information about the user's actions, such as the object being operated on (adjustable desk, smart home device), the type of operation (raise, lower, open, close, etc.), and potentially involved parameters (such as the target height of the adjustable desk, the brightness of the light, etc.). For example, if the previous voice command was "Raise the adjustable desk to 80 cm, turn on the left smart light and adjust it to 50% brightness, open the curtains," the system will extract the semantic understanding content as "Raise the adjustable desk to 80 cm," "Turn on the left smart light and adjust it to 50% brightness," and "Open the curtains."

[0108] Optionally, the system will associate the extracted semantic understanding content with the actual control commands sent to the height-adjustable desk and smart home devices. These control commands are specific codes or signals that, after being processed by the system, are used to directly control the devices to perform corresponding operations. For example, for the semantic understanding content "raise the height-adjustable desk to 80 centimeters," the corresponding control command might be a set of specific voltage signals sent to the height-adjustable desk's motor control board to drive the motor and raise the desk legs to the 80-centimeter position; for "turn on the left smart light and adjust it to 50% brightness," the corresponding control command might be a brightness adjustment command code sent to the smart bulb.

[0109] The system integrates the associated semantic understanding content and control commands to form a complete record of user control habits. This record includes a description of the operation scenario (such as the time the command was issued, environmental data at the time, etc.), the specific content of the operation, and the corresponding control commands. For example, the record might show: "At 10:00 AM on [Date], in an environment with an indoor temperature of 25°C and humidity of 50%, the user issued commands to raise the height-adjustable table to 80 cm, turn on the left smart light and adjust its brightness to 50%, and open the curtains. The corresponding control commands are [height-adjustable table motor control signal], [smart light brightness adjustment code], and [curtain opening / closing control code]."

[0110] The generated user control habit records are stored in the system's database and managed effectively. The system assigns a unique identifier to each control habit record for easy retrieval, access, and modification. Simultaneously, the system regularly updates and maintains the control habit data to ensure its accuracy and validity. When a user issues a command related to a saved habit, the system can quickly retrieve the corresponding control habit record and automatically execute the action, providing a more convenient and personalized intelligent experience.

[0111] In one embodiment, users are allowed to save frequently used operating modes as control habits according to their actual needs and operating preferences, so that the intelligent system can better adapt to personal usage habits and provide more personalized services.

[0112] In this way, when the same or similar operation needs to be performed again, the user does not need to describe the operation command in detail again. The system can automatically recall the saved control habits and quickly complete the operation, saving time and effort and improving efficiency. Moreover, as users continue to save and use control habits, the system can accumulate more user behavior data. Through data analysis and machine learning algorithms, the system can further optimize intelligent control strategies and provide users with more intelligent and considerate services.

[0113] In one embodiment, based on the above embodiments, before the step of controlling the height-adjustable table to perform the corresponding operation according to the semantic understanding content if the voice command is an operation command, the method further includes: If the current voice command is an operation command and the previous voice command was a question-and-answer command, and the question-and-answer content associated with the question-and-answer command is detected to be related to the current semantic understanding content, then the semantic understanding content is updated based on the question-and-answer content.

[0114] In this embodiment, the system identifies the type of the currently received voice command and the type of the previous voice command. Voice commands are mainly divided into two types: operation commands and question-and-answer commands. Operation commands are usually instructions to perform specific operations on the height-adjustable desk or related smart home devices, such as "raise the height-adjustable desk by 10 centimeters"; question-and-answer commands are instructions from the user to ask for information, such as "what is the maximum height of the height-adjustable desk?" The system uses natural language processing technology to analyze the semantics and structure of the commands to accurately determine the command type.

[0115] Once the system determines that the current voice command is an operation command and the previous voice command was a question-and-answer command, it will further detect whether the question-and-answer content associated with the previous command is related to the semantic understanding content of the current operation command. For example, if the previous question-and-answer command was "What is the maximum height of the height-adjustable desk?" and the system answered "The maximum height of the height-adjustable desk is 120 centimeters", and the current operation command is "Raise the height-adjustable desk to the maximum height", then the system will detect that the question-and-answer content "The maximum height is 120 centimeters" is related to the current semantic understanding content "Raise to the maximum height".

[0116] Once the system detects that the question-and-answer content is relevant to the current semantic understanding content, it extracts key information from the question-and-answer content and integrates it into the current semantic understanding content. In the example above, the system extracts the key information "120 centimeters" and updates the current semantic understanding content "raise to the highest height" to "raise to 120 centimeters".

[0117] Beyond simple information integration, the system also logically corrects and improves the updated semantic understanding content. For example, if the question-and-answer content provides certain constraints or additional information, the system ensures that the updated semantic understanding content conforms to these conditions. Suppose the question-and-answer content states, "When the load does not exceed 50 kg, the maximum height of the adjustable table is 120 cm," but the current operation command was issued with a load of 30 kg. The system will consider this load condition when updating the semantic understanding content to ensure the rationality and safety of the operation.

[0118] The updated semantic understanding will serve as the basis for generating control commands. The system will convert the updated content into specific control signals and send them to the control module of the height-adjustable desk. In the example of "raising to 120 centimeters," the system will generate a corresponding electrical signal to drive the motor of the height-adjustable desk, raising it to a height of 120 centimeters.

[0119] During the operation of the height-adjustable desk, the system monitors the operation based on updated semantic understanding. If any abnormalities occur, such as the desk failing to reach the specified height or exceeding the safe load, the system will take appropriate action based on the logic and conditions in the updated content, such as stopping the operation, issuing an alarm, or prompting the user to check the load. Simultaneously, the system will provide feedback on the operation results to the user, ensuring the user understands the execution status.

[0120] In one embodiment, semantic understanding content is updated by associating question-and-answer content, enabling the system to better understand the user's intent and provide more intelligent and accurate services. Users do not need to repeatedly provide information already requested; the system can automatically apply relevant information to subsequent operations, improving the efficiency and convenience of interaction.

[0121] Taking into account the personalized information and restrictions in the question-and-answer content, the system can adjust its operation according to the user's specific situation, providing a more personalized user experience and enhancing the user's satisfaction and trust in the intelligent system.

[0122] When updating semantic understanding content, the system corrects and improves the logic and conditions of the operation to ensure its security and reliability. This avoids operational errors caused by incomplete information or logical mistakes, thus protecting the safety of the height-adjustable desk and the user.

[0123] In addition, refer to Figure 2 This application also provides a control device Z10, comprising: The initialization module Z11 is used to perform system initialization operations on the control board when the height-adjustable table is powered on and started, in order to detect the operating status of the hardware modules configured on the height-adjustable table; the hardware modules include a microphone, a speaker, a 4G / WiFi module, a Bluetooth / ZigBee module, and table leg motors; The preprocessing module Z12 is used to preprocess the voice data received by the microphone when the height-adjustable desk is raised. The large model module Z13 is used to call a pre-defined large model to convert the pre-processed speech data into text information and perform semantic understanding on the text information; The analysis module Z14 is used to analyze the semantic understanding content and determine whether the voice command described by the voice data belongs to a question-and-answer command or an operation command. The response module Z15 is used to obtain the corresponding response information based on the semantic understanding content if the voice command is a question-and-answer command, and then convert the response information into response voice and output the response voice through the speaker. The operation module Z16 is used to control the height-adjustable table to perform the corresponding operation based on the semantic understanding of the content if the voice command is an operation command.

[0124] Optionally, the control device Z10 can be a virtual control device (such as a virtual machine) or a physical device (such as a physical device that can execute the corresponding method, excluding the height-adjustable table).

[0125] Furthermore, this application embodiment also provides a height-adjustable desk, wherein the internal architecture of the controller on the control board of the height-adjustable desk can be as follows: Figure 3 As shown, the system includes a processor, memory, communication interface, and input interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores data called by the computer programs. The communication interface is used for data communication with external terminals. The input interface is used to receive signals input from external devices. When the computer program is executed by the processor, it implements an intelligent voice interaction method for a height-adjustable desk as described in the above embodiment.

[0126] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the height-adjustable desk to which the present application is applied. For example, in some optional embodiments, the height-adjustable desk may also include an output interface (not shown in the figure), and the output interface is also connected to the system bus and used to output corresponding signals to peripherals.

[0127] Furthermore, this application also proposes a computer-readable storage medium comprising a computer program that, when executed by a processor, implements the steps of the intelligent voice interaction method for the height-adjustable desk described in the above embodiments. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0128] In summary, the intelligent voice interaction method, control device, height-adjustable desk, and computer-readable storage medium provided in the embodiments of this application have the following advantages: From the perspective of enhancing the intelligent experience, the integration of large-scale AI voice dialogue functionality has resulted in a qualitative leap in user experience. In traditional height-adjustable desks, users had to manually search for and operate buttons to adjust the desktop height. Now, users can easily adjust the desktop height simply by using a voice command, such as "raise the desk to a suitable height for standing work." This not only greatly benefits users whose hands are occupied or who have limited mobility, but also improves operational efficiency and reduces the distraction caused by searching for buttons or manual operation, allowing users to focus more on work or life tasks. Moreover, the voice dialogue capability based on the large-scale model makes the height-adjustable desk seem like a personal intelligent assistant for the user, capable of natural and fluent conversation. For example, if a user asks "How's the weather today?" or "Tell me a joke to relax," the height-adjustable desk can provide accurate and interesting answers based on the intelligent calculations of the large-scale model, adding fun and vitality to monotonous work or life scenarios, transforming the originally single-function height-adjustable desk into a more interactive and engaging work and life partner.

[0129] In terms of expanding functional diversity, the addition of new hardware modules enables network connectivity and voice interaction, greatly enriching the functionality of the height-adjustable desk. By leveraging 4G / WiFi modules to access the network and connect to a cloud-based platform, the desk is no longer limited to simple height adjustment but can achieve more intelligent functions. For example, users can use voice commands to query various information, including news and academic knowledge, without switching devices, thus improving the convenience of information access. Simultaneously, the touchscreen configuration further expands the interaction methods. The touchscreen provides users with an intuitive visual interface, allowing them to complete complex function settings, such as timed reminders and personalized voice assistant voice selection, and flexibly switch between touch operation and voice interaction to meet the diverse interaction needs of different users in different scenarios, comprehensively enhancing the applicability of the height-adjustable desk in modern digital life and office environments.

[0130] From the perspective of improving the convenience of smart home integration, the addition of a Bluetooth / ZigBee module enables seamless connectivity with various smart home devices. Users no longer need to switch between multiple apps to control different devices; they can easily achieve coordinated control of surrounding smart home devices simply through voice commands or touchscreen operation on the adjustable table. For example, after waking up in the morning, users can simply say "Good morning" to the adjustable table, which will automatically adjust to a suitable height, open the curtains via the ZigBee network to let sunlight into the room, and turn on the smart speaker via Bluetooth to play relaxing music, setting a pleasant tone for the day. This one-stop control method greatly improves user convenience, saves time and effort, and makes smart home living smoother and more natural.

[0131] From the perspective of enhancing product competitiveness, this innovative design makes the height-adjustable desk stand out in the market. As consumer demand for intelligent products grows, height-adjustable desks with large-scale AI voice dialogue capabilities have a clear differentiated advantage compared to traditional competitors. For consumers seeking a high-quality, intelligent living and working experience, this product better meets their needs, thereby attracting more potential customers and bringing higher market share and economic benefits to businesses. At the same time, this innovative design also helps drive the entire height-adjustable desk industry towards intelligent development, promoting continuous technological progress and product upgrades.

[0132] Through the specific implementation methods of the above-mentioned close cooperation between hardware and software, this height-adjustable desk can stably and efficiently realize intelligent voice dialogue function based on a large model, diverse human-computer interaction functions, and linkage with other intelligent devices, bringing users a brand-new intelligent user experience.

[0133] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media provided in this application and in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0134] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0135] The above description is only a preferred embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural changes made based on the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for intelligent voice interaction on a height-adjustable desk, characterized in that, include: When the height-adjustable table is powered on, the control board performs system initialization to check the operation of the hardware modules configured on the table; these hardware modules include a microphone, speaker, 4G / WiFi module, Bluetooth / ZigBee module, and table leg motors; The height-adjustable desk preprocesses the voice data received by the microphone. The pre-defined large model is invoked to convert the pre-processed speech data into text information, and semantic understanding is performed on the text information. Analyze the semantic understanding content to determine whether the voice commands described by the voice data belong to question-and-answer commands or operation commands; If the voice command is a question-and-answer command, the corresponding response information is obtained based on the semantic understanding content, and the response information is converted into response speech and then output through the speaker. If the voice command is an operation command, the height-adjustable table will be controlled to perform the corresponding operation based on the semantic understanding of the content.

2. The intelligent voice interaction method for a height-adjustable desk as described in claim 1, characterized in that, If the voice command is an operation command, the steps for controlling the height-adjustable desk to perform the corresponding operation based on the semantic understanding content include: If the voice command is an operation command, then detect the target of the operation command; If the target is a height-adjustable desk, then based on the semantic understanding content, the corresponding control instructions are queried from the control logic of the height-adjustable desk, and the desk is controlled to perform the corresponding operation. And / or, if the target is a smart home device associated with the height-adjustable desk, then based on the semantic understanding content, control commands corresponding to the smart home device are generated and sent to the smart home device to control the smart home device to perform corresponding operations; wherein, the height-adjustable desk is associated with the smart home device and establishes a communication connection based on a 4G / WiFi module or a Bluetooth / ZigBee module.

3. The intelligent voice interaction method for a height-adjustable desk as described in claim 2, characterized in that, The intelligent voice interaction method for the height-adjustable desk also includes: If the semantically understood content is detected to be associated with the environmental data collected by smart home devices, it is determined that the target is the smart home device that has collected the relevant environmental data; Among them, smart home devices equipped with environmental data acquisition sensors will share the collected environmental data with the height-adjustable desk.

4. The intelligent voice interaction method for a height-adjustable desk as described in claim 3, characterized in that, The hardware module also includes a touchscreen for: Touchscreen operation of height-adjustable desks and / or smart home devices; Displays the status parameters and / or environmental data of the height-adjustable desk; Provides a voice interaction interface; Provides a personalized settings interface.

5. The intelligent voice interaction method for the height-adjustable desk as described in any one of claims 2-4, characterized in that, After the steps of calling a pre-defined large model to convert the preprocessed speech data into text information and performing semantic understanding on the text information, the method further includes: If the semantically understood content is detected to be related to the user's control habits, the control commands of the height-adjustable desk and / or smart home devices associated with the user's control habits are obtained, and the height-adjustable desk and / or smart home devices are controlled to perform the corresponding operations.

6. The intelligent voice interaction method for a height-adjustable desk as described in claim 5, characterized in that, If the voice command is an operation command, then after the step of controlling the height-adjustable table to perform the corresponding operation based on the semantic understanding content, the method further includes: If a command to save control habits is received, user control habits are generated based on the current semantic understanding content and the control commands of the height-adjustable desk and / or smart home devices.

7. The intelligent voice interaction method for a height-adjustable desk as described in any one of claims 1-4, characterized in that, Before the step of controlling the height-adjustable table to perform the corresponding operation based on semantic understanding, if the voice command is an operation command, the following steps are also included: If the current voice command is an operation command and the previous voice command was a question-and-answer command, and the question-and-answer content associated with the question-and-answer command is detected to be related to the current semantic understanding content, then the semantic understanding content is updated based on the question-and-answer content.

8. A control device, characterized in that, include: The initialization module is used to perform system initialization operations on the control board when the height-adjustable table is powered on and started, in order to detect the operating status of the hardware modules configured on the height-adjustable table; the hardware modules include a microphone, speaker, 4G / WiFi module, Bluetooth / ZigBee module and table leg motors; The preprocessing module is used to preprocess the voice data received by the microphone when the height-adjustable desk is adjusted. The large model module is used to call a pre-defined large model to convert the pre-processed speech data into text information and perform semantic understanding on the text information; The analysis module is used to analyze the semantic understanding content and determine whether the voice commands described by the voice data belong to question-and-answer commands or operation commands. The response module is used to obtain the corresponding response information based on the semantic understanding content if the voice command is a question-and-answer command, and then convert the response information into response speech and output the response speech through the speaker. The operation module is used to control the height-adjustable table to perform the corresponding operation based on the semantic understanding of the content if the voice command is an operation command.

9. A height-adjustable desk, characterized in that, The controller of the control panel of the height-adjustable table includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the intelligent voice interaction method of the height-adjustable table as described in any one of claims 1 to 7.

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

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