Man-machine interaction power supply system based on AI voice recognition technology

Abstract

The utility model discloses a man-machine interaction power supply system based on an AI voice recognition technology. The man-machine interaction power supply system comprises input and output interface equipment, an automatic voice recognition module, a natural language processing module, a text-to-voice module, a power supply control module and a feedback and monitoring module, the AI voice recognition technology is integrated, human-computer interaction based on voice commands is achieved, the system converts the voice commands of a user into executable text commands through a voice recognition module, then the commands are transmitted to power supply equipment, and specific control operations such as voltage regulation, mode switching and output starting and stopping are executed. And through the voice synthesis engine, the system can feed back an operation result in real time through voice, the user immediately obtains confirmation information after operation, and the interaction experience is improved.

Description

TECHNICAL FIELD

[0001] The utility model relates to a power management system, especially a man-machine interactive power system through AI voice recognition technology. BACKGROUND

[0002] Traditional power management systems usually rely on physical buttons, remote controllers or applications for operation, although they have certain practicality, but still need users to perform manual operation, which limits their application effect in specific scenarios. And with the rapid development of smart home and smart devices, power management is gradually developing towards automation, intelligence and high efficiency.

[0003] In recent years, speech recognition technology has made significant progress, especially AI speech recognition technology based on deep learning enables devices to understand and respond to user natural language instructions, greatly improving the efficiency and naturalness of human-computer interaction. Applying AI speech recognition technology to power management systems enables users to control power devices through voice, significantly improving the convenience and safety of operation, especially in home automation, smart appliance control and industrial power management scenarios.

[0004] Prior art and defects:

[0005] Traditional power control systems mostly use physical switches or remote controllers for operation, and users must manually trigger the opening, closing or other control instructions of the device. This method is simple and reliable, but in some cases, especially when the user's hands are occupied or cannot touch the device, it is inconvenient to operate.

[0006] With the popularity of the network, many power devices begin to integrate WiFi or Bluetooth modules, and remote control through mobile applications or Web becomes a popular solution. Users can monitor and operate the power state through mobile devices to achieve remote switching or parameter adjustment. This method enhances the flexibility of control, but still requires users to manually operate the device and the operation depends on the phone / computer and network, and cannot achieve completely touchless operation, and the application interface unfamiliar to the user may cause inconvenience. In addition, when multiple devices are controlled at the same time, the operation process is relatively complex.

[0007] In summary, the existing power control system still has the problems of slow response speed, difficulty in adapting to the control needs of multiple users or complex scenarios, therefore, developing a power control system combined with AI speech recognition technology and having intelligent learning function can not only solve the deficiencies of existing technology, but also improve the adaptability and intelligence level of the system.

[0008] Therefore, the utility model is proposed. Utility model content

[0009] The utility model discloses a man-machine interaction power supply system through AI speech recognition technology to solve the above technical problem existing in prior art.

[0010] The utility model discloses a man-machine interaction power supply system through AI speech recognition technology to solve the above technical problem existing in prior art.

[0011] The utility model discloses a man-machine interaction power supply system through AI speech recognition technology, including input output interface equipment, automatic speech recognition module, natural language processing module, text speech module, power control module and feedback and monitoring module;

[0012] Automatic speech recognition module is connected with audio processing module, including microphone or intelligent sound box, noise suppression unit and speech enhancement unit;

[0013] Natural language processing module is connected with power control module;

[0014] Power control module is connected with the device of power supply system through RS232, LAN or CAN bus interface.

[0015] Compared with prior art, the utility model discloses a man-machine interaction power supply system through AI speech recognition technology, through the integration AI speech recognition technology, realizes the man-machine interaction based on voice instruction, and this system converts the voice instruction of user into the text command of executable with the aid of speech recognition module, then passes command to power equipment, and carries out the control operation such as voltage regulation, mode switching, output start-stop etc. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 For the power supply system structure topology of the utility model embodiment;

[0017] Figure 2 For the working mode schematic diagram of man-machine interaction power supply system with AI speech recognition technology of the utility model embodiment. DETAILED DESCRIPTION

[0018] The technical scheme in the utility model embodiment is clearly and completely described below with reference to the drawings in the utility model embodiment; Obviously, the described embodiment is only a part of the embodiment of the utility model, not all the embodiment, and this does not constitute the limitation to the utility model. Based on the embodiment of the utility model, all other embodiments obtained by the ordinary skill in the art without making the creative labor belong to the protection scope of the utility model.

[0019] First, the terms that can be used in this paper are explained as follows:

[0020] The term "and / or", refers to one or both of the items it connects, e.g. X and / or Y means that the three cases of "X", "Y", or "X and Y" are all possible.

[0021] The terms "comprising", "containing", "including", "having" or other similar semantic descriptions are to be interpreted as non-exclusive inclusion. For example, the inclusion of a technical feature element (such as raw materials, components, ingredients, carriers, dosage forms, materials, sizes, parts, components, mechanisms, devices, steps, processes, methods, reaction conditions, processing conditions, parameters, algorithms, signals, data, products or articles, etc.) is to be interpreted as not only including the explicitly listed technical feature element, but also including other technical feature elements not explicitly listed but known in the art.

[0022] The term "consisting of" means excluding any technical feature element not explicitly listed. If this term is used in a claim, the term will make the claim closed so that it does not contain technical feature elements other than those explicitly listed, except for conventional impurities associated therewith. If the term is only present in a certain clause of the claim, it only limits the elements explicitly listed in that clause, and the elements described in other clauses are not excluded from the overall claim.

[0023] The contents not described in detail in the embodiments of the present application are the existing technology known to the person skilled in the art. The embodiments of the present application are not specified under the conditions, and are carried out according to the conventional conditions in the art or the conditions recommended by the manufacturer. The reagents or instruments used in the embodiments of the present application are not specified by the manufacturer, and are all conventional products that can be purchased on the market.

[0024] The man-machine interaction power supply system through AI voice recognition technology of the present application comprises an input / output interface device, an automatic voice recognition module, a natural language processing module, a text-to-speech module, a power control module and a feedback and monitoring module.

[0025] The automatic voice recognition module is connected with the audio processing module, which comprises a microphone or a smart speaker, a noise suppression unit and a voice enhancement unit.

[0026] The natural language processing module is connected with the power control module.

[0027] The power control module is connected with the devices of the power supply system through RS232, LAN or CAN bus interface.

[0028] Self-learning and optimization module, multi-round dialogue and complex operation module, remote control and expansion module.

[0029] Also includes a skill matching and processing module, which includes any one or more of the following functional units:

[0030] Run / stop unit, measurement setting unit, protection setting unit, configuration setting unit, system setting unit.

[0031] The natural language processing module performs semantic analysis on the text command and converts it into operation instructions matching the control protocol of the power supply system;

[0032] The power supply control module communicates with the devices of the power supply system through RS232, LAN or CAN bus interface, and performs specific operations such as regulating voltage, switching mode, starting / stopping output;

[0033] The feedback and monitoring module feeds back the operation result to the user through the voice synthesis module, ensuring that the user can accurately know the operation status.

[0034] Also includes any one or more of the following modules:

[0035] Self-learning and optimization module:

[0036] This module uses self-learning function to record user operation habits and gradually optimize command analysis and execution efficiency. For commonly used instructions, the system will reduce the interaction steps and improve the response speed;

[0037] And through historical data learning different users' voice features and habits, improve the recognition accuracy in multi-user environment.

[0038] Multi-round dialogue and complex operation module:

[0039] This module supports multi-round dialogue interaction and can process multiple consecutive instructions one by one, maintaining the logical consistency of the context;

[0040] Complex instruction support: the system can handle complex operation instructions, and users can complete multiple settings through a single voice command;

[0041] Multi-scene mode: supports test experiment mode, aging experiment mode, factory default mode, last run mode, regular working mode, and safe shutdown mode for setting different scene modes;

[0042] Remote control and expansion module:

[0043] Remote control: users can perform remote voice control through networked devices. The remote access module allows users to send voice commands through mobile devices to achieve remote operation of the power supply system devices and confirm the execution result through voice feedback;

[0044] Function expansion: support user-defined instruction words, expand function modules to adapt to different power management scenarios, users can add specific power operation instructions according to needs, and the open source structure is used for secondary development of functions.

[0045] It also includes a skill matching and processing module that implements any one or more of the following functions:

[0046] Run / stop, measurement settings, protection settings, configuration settings, system settings.

[0047] As can be seen from the above, the human-computer interaction power supply system of the embodiment of the utility model through the AI voice recognition technology, through the integration of AI voice recognition technology, realize the human-computer interaction based on voice instruction, the system with the aid of voice recognition module converts the voice instruction of user into executable text command, then pass the command to power supply equipment, execute specific control operation, such as voltage regulation, mode switching, output start-stop etc.

[0048] The system supports natural language processing (NLP) and multi-round dialogue interaction, and can learn and adaptively optimize user voice features through deep learning technology, improve recognition accuracy and control efficiency. At the same time, the system supports custom command words and function expansion, and flexibly meets the power management needs in different scenarios. In addition, through the voice synthesis engine, the system can also provide real-time voice feedback on the operation results, so that the user can obtain confirmation information immediately after operation, and improve the interaction experience.

[0049] In order to more clearly show the technical solutions provided by the utility model and the technical effects generated, the following will describe the in detail with specific embodiments.

[0050] Embodiment 1

[0051] As shown in Figure 1 , Figure 2 :

[0052] After the voice dialogue robot is woken up, the voice instruction of the user will first pass through the automatic speech recognition (ASR) engine to recognize the text, then the recognized text is subjected to natural language understanding (NLU) analysis, and then the analysis result is subjected to skill matching and given to the skill plug-in suitable for processing the instruction for processing. After the plug-in processing is completed, the obtained result is given to the text-to-speech (TTS) engine to synthesize into voice and played to the user. Although one interaction may include multiple network requests, the benefit is that each link can be modified and customized.

[0053] 1. Voice Acquisition and Recognition

[0054] Voice Acquisition: The system collects user voice commands through connected devices such as microphones or smart speakers. The device uses the audio processing module of the voice dialogue robot to perform noise suppression and voice enhancement, ensuring the clarity of the voice input.

[0055] Voice Recognition: The collected audio signals are processed by the integrated speech recognition module (ASR). The ASR engine converts the voice into text according to the user's input instructions, such as "set voltage to 220V" or "switch to AC mode". The voice dialogue robot supports multiple Chinese ASR engines, thereby improving the accuracy and diversity of voice recognition.

[0056] 2. Instruction Analysis and Execution

[0057] Instruction Analysis: The recognized text commands are semantically analyzed by the natural language processing module of the voice dialogue robot, identifying key parameters such as voltage, frequency, or mode in the instructions. The system can recognize complex commands and multi-round interactions, such as "adjust the voltage to 220 volts and set the harmonic analysis to three harmonics".

[0058] Power Control: The analyzed commands are converted into operation instructions compatible with the control protocol of the power system. The system communicates with power system devices through RS232, LAN, or CAN bus interfaces to perform specific operations such as adjusting voltage, switching modes, starting / stopping output, etc.

[0059] 3. Voice Feedback and Confirmation

[0060] Feedback Mechanism: After the operation is completed, the system provides feedback on the operation results to the user through the text-to-speech (TTS) module. For example, when the user sets the voltage to 220V, the system will inform the user through voice that "the voltage has been set to 220V". This real-time feedback ensures that the user can accurately know the operation status.

[0061] 4. Self-learning and Optimization

[0062] Intelligent Learning: The system uses the self-learning function of the voice dialogue robot to record user operation habits and gradually optimize command analysis and execution efficiency. For frequently used instructions, the system will reduce interaction steps and improve response speed. At the same time, the AI module can learn the voice characteristics and habits of different users through historical data, improving the recognition accuracy in a multi-user environment.

[0063] 5. Multi-round Dialogue and Complex Operations

[0064] Multi-turn dialogue: The system supports multi-turn dialogue interaction. For example, the user can first issue "set the power supply to AC mode" and then issue "set the frequency to 50Hz". The system can process multiple consecutive instructions in sequence, maintaining logical consistency of the context.

[0065] Complex instruction support: The system can handle complex operation instructions, and users can complete multiple settings through a single voice instruction. For example, the user can directly issue "enable AC+DC mode, voltage set to 110V, frequency 50Hz", and the system will parse and execute these operations in sequence, simplifying the operation process.

[0066] Multi-scenario mode: The system supports setting different scene modes such as test experiment mode, aging experiment mode, factory default mode, last run mode, regular work mode, and safe shutdown mode.

[0067] 6. Remote control and expansion

[0068] Remote control: Users can remotely control the power supply system through networked devices such as smartphones and tablets. The remote access module of the voice dialogue robot allows users to send voice instructions through mobile devices to remotely operate the power supply system, and the system provides voice feedback to confirm the execution result.

[0069] Function expansion: The system supports user-defined instruction words and extended function modules to adapt to different power management scenarios. Users can add specific power operation instructions as needed, and the open-source structure of the voice dialogue robot allows secondary development of functions.

[0070] As can be seen, the utility model is based on AI voice recognition technology, combined with AC / DC load power supply products, and realizes intelligent interactive control of the power supply system through voice instructions. Using deep learning technology, the system can adapt to different user voice characteristics, with high recognition accuracy and strong operation safety. The recognized instructions are used to control various functions of the power supply, such as voltage regulation, harmonic analysis, and mode switching, to realize power on / off, parameter adjustment, and mode switching, greatly improving the convenience of operation. This non-contact interaction method not only improves user experience, but also can adapt to more complex application scenarios.

[0071] The above merely describes a preferred specific implementation of the present application, but the scope of protection of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be encompassed within the scope of protection of the present application. Therefore, the scope of protection of the present application should be subject to the scope of protection of the claims. The information disclosed in the background section of the present application is merely intended to deepen the understanding of the overall background technology of the present application, and should not be regarded as acknowledging or implying in any form that the information constitutes the prior art known to those skilled in the art.

Claims

1. A human-machine interaction power supply system through AI voice recognition technology, characterized in that, The system includes input / output interface devices, automatic speech recognition module, natural language processing module, text-to-speech module, power control module and feedback and monitoring module; The automatic speech recognition module is connected with the audio processing module, including a microphone or a smart speaker, a noise suppression unit and a speech enhancement unit; The natural language processing module is connected with the power control module; The power control module is connected with the devices of the power system through RS232, LAN or CAN bus interface. 2.The human-machine interaction power supply system through an AI voice recognition technology according to claim 1, wherein, It also includes any one or more of the following modules: Self-learning and optimization module, multi-turn dialogue and complex operation module, remote control and expansion module. 3.The human-machine interaction power supply system through an AI voice recognition technology according to claim 1 or 2, characterized in that, It also includes a skill matching and processing module, which includes any one or more of the following functional units: Run / stop unit, measurement setting unit, protection setting unit, configuration setting unit, system setting unit.

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