Intelligent wearable device and voice-controlled lamp dimming method and system thereof

Abstract

The invention provides intelligent wearable equipment and a voice lamp control dimming method and system thereof, and belongs to the technical field of light control. In the method, an intelligent wearable device establishes wireless communication connection with a plurality of photography lamps, then configures at least one semantic identifier for distinguishing from other photography lamps for each photography lamp, extracts a user instruction in combination with voice recognition and semantic analysis, accurately matches a target photography lamp, and finally generates a dimming control instruction. And the target photography lamp is driven to execute corresponding light adjustment operation. According to the configuration of the semantic identifier, a user can quickly specify a target lamp through tags (such as a headlight and an auxiliary lamp group) in a natural language, the user does not need to memorize the serial number or position association relation of lamp equipment, the voice recognition and semantic analysis technology is matched, and the user does not need to depend on a traditional key console or a touch screen APP; a user can directly complete multi-dimensional adjustment of brightness, color temperature, color and the like through a spoken instruction, and operation is more convenient and efficient.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of light control, in particular to an intelligent wearable device and a voice-controlled light dimming method and system thereof. BACKGROUND

[0002] In the field of photography and video production, light control is a core link for shaping the atmosphere of the picture, highlighting the main body and enhancing the visual expressiveness. The traditional light control method mainly relies on physical button console or touch screen APP operation, and the photographer needs to manually adjust the brightness, color temperature, light effect mode and other parameters of the lamp. This operation method is acceptable in static shooting scenes, but in dynamic shooting (such as mobile follow-up, multi-camera coordination or live scene), the photographer needs to frequently switch device operation, which leads to low efficiency and easy distraction, affecting the shooting fluency. For example, in film shooting, the photographer needs to adjust the light while considering the composition and actor scheduling, and manual operation may delay the key moment; in live scenes, quick response to audience interaction needs (such as immediate adjustment of light effect) also faces challenges.

[0003] In related technologies, voice control as an alternative solution has been applied in the field of smart home, such as controlling light switches and basic dimming through voice assistants (such as Alexa or Google Assistant). However, these solutions lack spatial perception ability and cannot distinguish specific lamps intended by the user, which may lead to command ambiguity in multi-lamp scenes. SUMMARY

[0004] To solve at least one of the above problems, the present application provides an intelligent wearable device and a voice-controlled light dimming method and system thereof, aiming to configure at least one semantic identifier for each photography lamp to distinguish from other photography lamps, accurately locate the target lamp, and realize more convenient, accurate and intelligent voice dimming control of photography lamps in photography, video shooting and other scenes.

[0005] According to an aspect of an embodiment of the present application, a voice-controlled light dimming method is provided, applied to an intelligent wearable device, the method comprising:

[0006] The intelligent wearable device establishes a wireless communication connection with a plurality of photography lamps; The intelligent wearable device configures at least one semantic identifier for each of the photography lamps to distinguish from other photography lamps; The intelligent wearable device collects a user voice signal and performs voice recognition and semantic analysis on the user voice signal to extract a user instruction; The intelligent wearable device determines a target photography lamp to be dimmed according to the user instruction and the semantic identifier of each of the photography lamps; The smart wearable device generates a corresponding dimming control instruction according to the user instruction, and sends the dimming control instruction to the target photographic lamp to drive the target photographic lamp to perform a corresponding light adjustment operation.

[0007] In some embodiments, the smart wearable device configures at least one semantic identifier for each of the photographic lamps for distinguishing from other photographic lamps, including: In response to a user input or a preset rule, the smart wearable device sets one or more text labels as the semantic identifier for each of the photographic lamps, and the text label is used to represent the function or position of the photographic lamp in a photographic lighting scene.

[0008] In some embodiments, after the smart wearable device generates a corresponding dimming control instruction according to the user instruction, and sends the dimming control instruction to the target photographic lamp to drive the target photographic lamp to perform a corresponding light adjustment operation, the method further comprises: The smart wearable device broadcasts the result of the light adjustment operation through a voice broadcast module, and / or displays the result of the light adjustment operation through a display module.

[0009] In some embodiments, the smart wearable device collects a user voice signal, and performs voice recognition and semantic analysis on the user voice signal to extract a user instruction, including: The smart wearable device collects a user voice signal, and converts the user voice signal into text information through a local or cloud automatic speech recognition engine; The smart wearable device performs semantic analysis on the text information through a natural language understanding module or a large model to extract a user instruction.

[0010] In some embodiments, the user instruction includes at least one user intent, and one of the user intents is used to represent a light adjustment operation on one of the plurality of photographic lamps.

[0011] In some embodiments, the light adjustment operation includes at least one of light brightness adjustment, light color temperature adjustment, light color adjustment, light focal length adjustment, light rotation, and light pitch angle adjustment.

[0012] In some embodiments, the smart wearable device generates a corresponding dimming control instruction according to the user instruction, and sends the dimming control instruction to the target photographic lamp to drive the target photographic lamp to perform a corresponding light adjustment operation, including: The smart wearable device obtains target parameter adjustment information corresponding to the target photographic lamp to be dimmed according to the user instruction; The smart wearable device acquires the current values ​​of the target parameters of the target photography light; The smart wearable device calculates the target value of the target parameter corresponding to the target photography light based on the current value of the target parameter of the target photography light and the target parameter adjustment information; The smart wearable device generates a corresponding dimming control command based on the target value of the target parameter corresponding to the target photography light, and sends the dimming control command to the target photography light to drive the target photography light to perform the corresponding light adjustment operation.

[0013] In some embodiments, the smart wearable device generates a corresponding dimming control command based on the user instruction and sends the dimming control command to the target photography light to drive the target photography light to perform a corresponding light adjustment operation, including: The smart wearable device obtains target parameter adjustment information corresponding to the target photography light to be dimmed according to the user's instructions; The smart wearable device generates a corresponding dimming control command based on the target parameter adjustment information corresponding to the target photography light, and sends the dimming control command to the target photography light, so that the target photography light calculates the target value of the target parameter corresponding to the target photography light based on the current value of the target parameter of the target photography light and the target parameter adjustment information, and performs corresponding light adjustment operation based on the target value of the target parameter.

[0014] In some embodiments, the method further includes: The smart wearable device pre-configures the lighting adjustment operation type, adjustment step size, and maximum adjustable value for each type of photographic light.

[0015] According to one aspect of the embodiments of this application, a smart wearable device is provided, comprising: The smart wearable device communicates wirelessly with each camera light via a wireless communication module. A voice acquisition module, which is used to acquire user voice signals; The main control module is connected to the wireless communication module and the voice acquisition module respectively. The main control module is used to execute the method described in any embodiment of this application.

[0016] In some embodiments, the smart wearable device further includes: A voice broadcast module, which is connected to the main control module, is used to broadcast the results of the lighting adjustment operation; and / or a display module, the display module being connected to the main control module, the display module being used to display the result of the light adjustment operation.

[0017] In some embodiments, the smart wearable device further includes: An NFC module is connected to the main control module. When the smart wearable device approaches the photography light, the NFC module performs NFC communication and triggers the smart wearable device to establish a communication connection with the photography light.

[0018] According to one aspect of the embodiments of this application, a voice-controlled lighting dimming system is provided, comprising: The smart wearable device described in any embodiment of this application; Multiple photographic lights are wirelessly connected to the smart wearable device, which is configured to send messages to the multiple photographic lights.

[0019] The technical solutions provided by the embodiments of this application have at least the following beneficial effects: The disclosed solution involves a smart wearable device first establishing a wireless communication connection with multiple photography lights. Then, each photography light is configured with at least one semantic identifier to distinguish it from other lights. Combined with voice recognition and semantic parsing, user commands are extracted and accurately matched to the target photography light, ultimately generating dimming control commands to drive the target light to perform corresponding lighting adjustments. The semantic identifier configuration allows users to quickly specify target lights using natural language labels (such as "front light" or "filler light group"), eliminating the need for users to remember light device numbers or location relationships. Coupled with voice recognition and semantic parsing technology, it eliminates the need for traditional button control panels or touchscreen apps. Users can directly use spoken commands to adjust brightness, color temperature, color, and other dimensions, making operation more convenient and efficient. This avoids the tedium and delays of manual operation, significantly improving the flexibility and efficiency of lighting setups in shooting scenarios, making light control more user-friendly, and achieving an intelligent and humanized lighting control experience.

[0020] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this application. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the principles of this application.

[0022] Figure 1 This is a schematic diagram of the architecture of a voice-controlled lighting dimming system provided in one embodiment of this application.

[0023] Figure 2 This is a first structural schematic block diagram of a smart wearable device provided in an embodiment of this application.

[0024] Figure 3 This is a schematic block diagram of the second structure of a smart wearable device provided in an embodiment of this application.

[0025] Figure 4 This is a structural diagram of a smart glasses provided in an embodiment of this application.

[0026] Figure 5 This is a structural diagram of another type of smart glasses provided in an embodiment of this application.

[0027] Figure 6 This is a flowchart of a voice-controlled light dimming method performed by a smart wearable device according to an embodiment of this application.

[0028] Figure 7 This is a flowchart illustrating the steps of a smart wearable device according to an embodiment of the present application to collect user voice signals and perform speech recognition and semantic parsing on the user voice signals to extract user commands.

[0029] Figure 8 This is a flowchart illustrating the steps of a smart wearable device according to an embodiment of the present application to generate a corresponding dimming control command based on a user instruction and send the dimming control command to the target photography light to drive the target photography light to perform a corresponding light adjustment operation.

[0030] Figure 9 This is another step in the flowchart of an embodiment of the present application of a smart wearable device that generates a corresponding dimming control command according to a user instruction and sends the dimming control command to the target photography light to drive the target photography light to perform a corresponding light adjustment operation. Detailed Implementation

[0031] To make the objectives, implementation methods, and advantages of this application clearer, exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these exemplary embodiments are provided to make the description of this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. It should be noted that the brief descriptions of terminology in this application are merely for the convenience of understanding the embodiments described below, and are not intended to limit the embodiments of this application. Unless otherwise stated, these terms should be understood in their ordinary and common meaning.

[0032] In the description of this application, it should be understood that the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include one or more features.

[0033] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0034] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0035] In photography and film shooting, the dimming control of photography lights is a crucial aspect of ensuring shooting results. Traditional methods of dimming photography lights mainly rely on wired button control consoles or mobile device touch screen apps. Wired control consoles suffer from complex wiring and limited control range, making them unsuitable for scenarios with multiple lights distributed across the scene. Furthermore, operation requires the user to be close to the control console, interrupting the shooting process and impacting efficiency. Mobile apps, on the other hand, require the user to hold the device and operate it by touch, which can easily distract the user during shooting. It is also difficult to quickly and accurately locate the target light, especially in scenarios where multiple lights work together, requiring manual selection of light numbers or positions, which is cumbersome and prone to selection errors.

[0036] In related technologies, voice control has been applied in the smart home field as an alternative, such as controlling light switches and basic dimming via voice assistants (like Alexa or Google Assistant). However, these solutions lack spatial awareness and cannot distinguish the specific light fixture the user intends to point to, leading to ambiguity in multi-light scenarios.

[0037] Based on this, embodiments of this application provide a smart wearable device and its voice-controlled lighting dimming method and system. By configuring at least one semantic identifier for each photography light to distinguish it from other photography lights, the target light can be accurately located, enabling more convenient, accurate, and intelligent voice-controlled lighting dimming in photography, film and television shooting, and other scenarios.

[0038] Reference Figure 1 , Figure 1 This is a schematic diagram of the architecture of a voice-controlled lighting dimming system provided in one embodiment of this application. Figure 1As shown, the voice-controlled lighting dimming system includes a smart wearable device 100 and multiple photographic lights 200. The multiple photographic lights 200 are wirelessly connected to the smart wearable device 100, which is configured to send messages to each photographic light 200. Each photographic light 200 has a unique device identifier and is configured with a unicast address and / or a multicast address.

[0039] The smart wearable device 100 can wirelessly connect with each of the on-site photography lights 200. Specifically, the smart wearable device 100 can network with multiple on-site photography lights 200 through its built-in wireless communication module. This networking can be achieved through various standard communication protocols, such as Wi-Fi, Bluetooth, BLE, and other industry-known communication standard protocols. Alternatively, the smart wearable device 100 can network with each photography light 200 through the wireless communication module 110 using various proprietary / private communication protocols, such as wireless communication modules using frequency bands like 5.8GHz, 2.4GHz, 1.9GHz, and 1.4GHz, and implementing networking through custom protocols. In some embodiments, an intermediate device (such as a mobile phone) is used as a communication bridge to establish a communication connection between the smart wearable device 100 and the multiple photography lights 200. In some embodiments, the wireless communication module 110 can also employ various generations of mobile communication standard protocols such as 3G / 4G / 5G.

[0040] Specifically, in this embodiment, a smart wearable device 100 can be used as the master node of a Bluetooth Mesh network. A unicast address and / or multicast address can be configured for each photography light 200 with a unique device identifier to achieve multi-light networking. This supports both precise control of a single light and meets the needs of collaborative control of multiple lights, adapting to the lighting requirements of complex shooting scenarios. Simultaneously, the smart wearable device 100 can configure at least one semantic identifier for each photography light to distinguish it from other photography lights. This allows for precise location of target lights based on user voice commands, and the generation of corresponding dimming commands based on user voice commands, which are then sent to the corresponding target lights to drive them to perform appropriate lighting adjustments, achieving precise lighting control.

[0041] It should be noted that in this embodiment, the network configurator can be the smart wearable device 100 (i.e., "the publisher also acts as the network configurator"), or it can be a device terminal (such as a mobile phone, tablet, computer, or other devices) with a corresponding application (APP) installed. In this case, the device terminal is only responsible for completing the network configuration of the photography light. After the configuration is completed, the core control authority of the network can be transferred to the smart wearable device 100, and it will no longer participate in subsequent light control command interactions. The core responsibility of the smart wearable device 100 as the "master node" is not limited to network configuration, but after the network is established, as the core message publisher in the network, it initiates and issues key commands: on the one hand, it obtains the status data of the photography light by scanning the Bluetooth signal strength (RSSI) to complete the target device location; on the other hand, it generates dimming control commands based on user voice commands and sends them to the target photography light through the BLE Mesh protocol stack (unicast address corresponds to a single light, multicast address corresponds to a group of lights) to drive the light adjustment operation. In other words, the "network configuration and access" and "control command issuance" of Bluetooth Mesh networking can be completed by different devices. The network configuration device is only responsible for the device to enter the network, while the smart wearable device 100, as the "master node", plays the role of "message publisher" and takes the lead in generating and issuing light control commands.

[0042] In some embodiments, the smart wearable device 100 can also establish a communication connection with the cloud, thereby uploading the collected user voice signals to the cloud, whereby the cloud performs voice recognition and semantic parsing to extract user intent or user instructions, and then sends the extracted user instructions to the smart wearable device 100.

[0043] Among them, the smart wearable device 100 includes headsets (or earphones, headphones), smart glasses, bracelets, watches, rings, helmets and other wearable or wearable devices. The specific form of the smart wearable device 100 is not specifically limited in the embodiments of this application.

[0044] As a controlled terminal, the Photography Light 200 possesses a unique device identifier (such as a MAC address or UUID) and can be equipped with a built-in communication module compatible with the wireless communication module of smart wearable devices to support wireless communication connections. During the network configuration phase, the Photography Light 200 is assigned a unicast address (for precise control of a single light) and / or a multicast address (for collaborative control of multiple lights in groups). Some models support NFC functionality for convenient "NFC-enabled light addition." The light source types for the Photography Light 200 can cover dual-color temperature LEDs, RGB LEDs, RGBW, RGBWW, etc., and product forms can include stick lights, board lights, COB lights, inflatable lights, cushion lights, flashes, etc., adapting to the lighting needs of different shooting scenarios. The photography light 200 can respond to commands issued by the smart wearable device, and realize multi-dimensional adjustment of brightness, color temperature, color, light focus, rotation / tilt angle, etc. It supports fixed value adjustment and step adjustment of default step size (such as 10%). Some can also realize special light effects such as dynamic light horse. It also has status feedback capability, which can synchronize the dimming result (success / failure) and current parameters to the smart wearable device 100.

[0045] Reference Figure 2 , Figure 2 This is a first structural schematic block diagram of a smart wearable device according to an embodiment of this application. The smart wearable device 100 includes a wireless communication module 110. The smart wearable device 100 can wirelessly connect with each of the on-site photography lights 200 through the wireless communication module 110.

[0046] The wireless communication module 110 is primarily responsible for establishing and maintaining stable wireless links with multiple photography lights 200. This module supports various network protocols and frequency bands to adapt to different connection requirements, power consumption, and bandwidth requirements in various scenarios. The smart wearable device 100 networks with the photography lights 200 through the wireless communication module 110, specifically through various standard communication protocols, such as Wi-Fi, Bluetooth, BLE, and other industry-known communication standard protocols.

[0047] The wireless communication module 110 can also be configured to support a specific single network protocol and frequency band, or it can be a wireless communication module including two or more protocols or frequency bands. For example, the wireless communication module 110 can simultaneously include a Bluetooth module and a 2.4GHz module working together. The Bluetooth module uses the standard Bluetooth protocol for communication, while the 2.4GHz module uses a custom protocol (non-standard) for communication. Through collaborative management and frequency hopping algorithms, it can automatically switch between the two communication modules to achieve optimal communication. As another example, the wireless communication module 110 can be a dual-band module, including communication modules for both 2.4GHz and 1.9GHz frequency bands. Communication between the two frequency bands can be switched through the frequency band management module of the protocol stack or a dynamic frequency selection algorithm to avoid current interference bands and improve call signal quality. The two frequency bands can also work together simultaneously, forming two parallel communication links, one link responsible for uplink data transmission and the other for downlink data transmission, or the transmission of a portion of the data required by the system can be pre-defined by one of the wireless modules.

[0048] The wireless communication module 110 can be fixed inside the circuit board of the smart wearable device 100, i.e., as standard built-in hardware at the factory, or the wireless communication module 110 can be installed in a pluggable / detachable manner on the dedicated wireless module interface of the smart wearable device 100. This design allows users to replace or upgrade the communication module according to the actual network environment, thus enhancing the adaptability and future compatibility of the device.

[0049] Specifically, the wireless communication module 110 can be a Bluetooth module, which supports wireless communication connection protocols. The smart wearable device 100 can initiate the networking process as the master node of the Mesh network, establishing a stable wireless communication connection with each photography light 200 that has a unique device identifier (such as a MAC address or UUID) and is equipped with a Bluetooth module. During the network configuration phase, the wireless communication module 110 assigns a dedicated unicast address to each connected photography light 200 (for precise control of a single light), and also supports assigning multicast addresses to some photography lights according to actual control needs (for grouped collaborative control of multiple lights). It also assists the smart wearable device 100 in maintaining a complete address mapping table, clearly associating the light ID of each photography light 200 with the corresponding unicast / multicast address, ensuring orderly device management after networking. Furthermore, during subsequent light control, the wireless communication module 110 is also responsible for accurately sending the parsed BLE Mesh dimming control command to the corresponding address of the target photography light 200, ensuring the stability and timeliness of command transmission, and laying the communication foundation for the smooth execution of the entire voice-controlled dimming process.

[0050] The smart wearable device 100 first establishes a network with multiple photography lights 200 via the wireless communication module 110, obtaining the unique device identifier (such as MAC address, UUID), unicast / multicast address, and basic device information (model, manufacturer, supported control parameters, etc.) for each photography light, and maintaining a mapping table between light IDs and addresses. Subsequently, semantic tags are deeply associated with the above device information to form a complete mapping relationship of "semantic tag - light ID - unicast / multicast address - device capabilities," ensuring that when a user triggers a semantic tag, the device can quickly locate the target light and match its control capabilities.

[0051] The configuration of semantic identifiers needs to align with users' shooting habits. For example, the smart wearable device 100 can configure functional scene-based identifiers for each photography light, based on the light's functional positioning in the lighting scene, such as "main light," "auxiliary light," "background light," and "fill light," directly corresponding to the light's lighting responsibilities. Users can quickly control these lights using commands like "brighten the background light" or "warm up the auxiliary light's color temperature." The smart wearable device 100 can also configure spatial location-based identifiers for each photography light, based on the light's positional distribution (such as azimuth and relative distance), such as "front light," "rear light," "left light," and "right light," adapting to users' lighting control needs based on spatial descriptions and echoing the spatial relationship descriptors like "left light" and "right light" in subsequent semantic parsing. The smart wearable device 100 can also configure grouping and aggregation-based identifiers for each photography light. This allows for the configuration of group control for multiple lights with the same function, such as "auxiliary light group", "background light group", "light group A", etc. Multiple photography lights (such as 5 background stick lights) can be bound to the same semantic identifier and assigned a unified multicast address, supporting group commands such as "reduce the brightness of the auxiliary light group by 10%" and "enable the color light cycle running light effect for the background light group".

[0052] Understandably, each semantic identifier corresponds to only one or a group of photographic lights to avoid control confusion caused by "labels with the same name" and ensure that the target is unique when a command is triggered. Semantic identifier names can use words frequently used in everyday speech, thus avoiding complex technical terms and reducing the difficulty of speech recognition and the user's memory burden. Semantic identifiers also need to match the actual attributes of the lights, such as configuring adjustable dual-color temperature LED lights with a "warm light" identifier and RGB series lights with a "color light group" identifier. Simultaneously, they should be associated with the device capability model to ensure that parameter compatibility can be verified during subsequent command parsing (e.g., avoiding issuing color adjustment commands to "white fill lights"). In addition, users should be able to add, modify, or delete semantic identifiers according to the needs of the shooting scene, such as temporarily configuring a fill light with a "portrait fill light" identifier to adapt to dynamic lighting requirements.

[0053] It should be noted that the configuration of semantic tags can be completed simultaneously during the network configuration phase. Specifically, the smart wearable device 100 can take pictures of the lighting scene with its camera, identify the lamp model, appearance size, and location distribution, and automatically recommend semantic tags (such as recommending "left lamp" and "right lamp" based on azimuth angle). Users can also manually configure them through voice or the device's interactive interface. After configuration, the semantic tags and their corresponding mapping relationships (associated lamp ID, address, and device capabilities) will be stored in the local database of the smart wearable device 100, forming a standardized tag library. This library can be accessed in real time during network deployment and supports dynamic updates to the tag mapping table when lamps are added or removed.

[0054] Reference Figure 2 The smart wearable device 100 also includes a voice acquisition module 120, which is used to acquire user voice signals. The voice acquisition module 120 is the core input module for realizing voice-controlled lighting dimming functions. Its core component is a microphone array, which can accurately capture various voice commands issued by the user in scenarios such as photography and film shooting. Simultaneously, the voice acquisition module 120 also possesses powerful audio preprocessing capabilities. Through noise reduction, echo cancellation, and other technologies, it can effectively filter out interference factors such as ambient noise and equipment operating sounds at the shooting location, ensuring the purity and clarity of the acquired voice signals and laying a high-quality foundation for subsequent voice processing. The voice signals acquired by the voice acquisition module 120 can cover various types, including single-parameter commands (such as "adjust headlight brightness to 88%)" and multi-parameter composite commands (such as "increase headlight color temperature, decrease auxiliary light brightness, decrease background brightness"). The voice acquisition module 120 can also completely retain the speech features such as pauses in the user's speech, which is convenient for the subsequent ASR engine to recognize and convert into text signals with punctuation marks or segmentation marks. This helps the natural language understanding (NLU) module to accurately segment intent and parse key information (such as target device, control action, adjustment parameters and parameter values). It is a key bridge connecting user commands and device lighting operation, and provides core support for the smooth start of the entire voice lighting control process.

[0055] Reference Figure 2 The smart wearable device 100 also includes a main control module 130. The wireless communication module 110 and the voice acquisition module 120 are respectively connected to the main control module 130. The main control module 130 may be a main processor integrating Bluetooth functionality. The main control module 130 is used to perform voice recognition and semantic analysis on the user voice signal acquired by the voice acquisition module 120 to extract user commands. Based on the user commands and the semantic identifiers corresponding to each camera light, it determines the target camera light to be dimmed, generates corresponding dimming control commands based on the user commands, and sends the dimming control commands to the target camera light via the wireless communication module 110 to drive the target camera light to perform the corresponding light adjustment operation. This completes the voice dimming control of the camera lights in the shooting scene.

[0056] Reference Figure 3 , Figure 3 This is a schematic block diagram of the second structure of a smart wearable device provided in an embodiment of this application. Figure 3 As shown, the smart wearable device 100 may also include an NFC module 140. The NFC module 140 is connected to the main control module 130. When the smart wearable device 100 is close to the photography light 200, the NFC module 140 performs NFC communication and triggers the smart wearable device 100 to establish a communication connection with the photography light 200.

[0057] The NFC module 140 serves as a convenient auxiliary module for wireless communication connections. It establishes a connection with and is managed by the main control module 130, its core function being to simplify the network access process for the photographic light 200. When a user brings the smart wearable device 100 close to the NFC-enabled photographic light 200, the NFC module 140 quickly establishes near-field communication with the corresponding NFC component of the photographic light 200, automatically completing device authentication (based on the photographic light's unique device identifier, such as MAC address or UUID), and triggering the main control module 130 to initiate the wireless communication connection process, eliminating the need for complex manual pairing operations by the user. During communication, the NFC module 140 assists in transmitting basic device information of the photographic light (such as model and supported control parameters) to the main control module 130, providing data support for the main control module 130 to quickly allocate unicast and / or multicast addresses for the photographic light and update the address mapping table. This significantly shortens network setup time, improves device access efficiency in multi-light lighting scenarios, allows users to more easily build a lighting control system, and further enhances the ease of use of voice-controlled lighting via smart wearable devices.

[0058] Reference Figure 3The smart wearable device may also include a voice broadcast module 150. The voice broadcast module 150 is connected to the main control module 130 and is used to announce the results of the lighting adjustment operation. After the main control module 130 completes the dimming command and receives feedback from the target camera light, it synchronizes the dimming result (success or failure) and key information to the voice broadcast module 150. This module uses text-to-speech (TTS) technology to convert text information into natural speech for broadcast. Specifically, if the dimming is successful, the voice broadcast module 150 will accurately announce the operation details. For example, if the user command is "adjust the headlight brightness to 80%", the voice broadcast module 150 can announce "The headlight brightness has been adjusted to 80%". If it is a step adjustment (such as "increase brightness"), the voice broadcast module 150 can announce the corresponding state after the step adjustment. If dimming fails (e.g., signal timeout, lamp offline, lamp does not support this parameter adjustment), the voice broadcast module 150 can promptly broadcast fault prompts, such as "Adjustment failed, please check if the lamp is online" or "This lamp does not support color temperature adjustment," helping users quickly locate the problem. The voice broadcast module 150's voice is clear, concise, and highly recognizable, adaptable to complex shooting environments, ensuring users can know the lighting control results in real time without viewing the display interface, further enhancing the convenience and interactive experience of voice-controlled lighting, making the entire lighting control process more intuitive and efficient.

[0059] Reference Figure 3 The smart wearable device may also include a display module 160. The display module 160 is connected to the main control module 130 and is used to display the results of the light adjustment operation. The display module 160 can be used to intuitively present the relevant results of the light adjustment operation, providing visual feedback to the user, and forming a dual feedback mechanism with the voice broadcast module 150.

[0060] After the main control module 130 completes the issuance of the dimming command and the reception of the result, it will synchronize the dimming status, key parameters, and other information to the display module 160. Specifically, if dimming is successful, the display module 160 can clearly display a dimming success prompt message, and can also sequentially or cyclically display the specific parameters of the target lamp (or lamp group) after dimming, such as "Current color temperature of the front lamp is 4100K", "Current brightness of the rear lamp is 50%", "Brightness of the left lamp has been adjusted to 88%", etc., allowing users to accurately grasp the current working status of the lamp. If dimming fails (such as signal timeout, lamp offline, lamp not supporting the corresponding parameter adjustment), the display module 160 will display a fault prompt message, such as "Adjustment failed, please check if the lamp is online" or "This lamp does not support color temperature adjustment", etc., to help users quickly troubleshoot the problem. The display module 160 features a simple, clear, and highly recognizable interface that is compatible with wearable devices such as smart glasses. Users can obtain information intuitively through their eyes without any additional operation. Especially in noisy shooting environments where it is inconvenient to rely on voice broadcasts, it can effectively ensure that users know the lighting control results in a timely manner, further improving the convenience, intuitiveness, and reliability of voice-controlled lighting.

[0061] Reference Figure 4 and Figure 5 , Figure 4 This is a structural diagram of a smart glasses embodiment provided in this application. Figure 5 This is a structural diagram of another type of smart glasses provided in one embodiment of this application. This application uses smart glasses as an example of a smart wearable device 100 for detailed description. The smart glasses include a display lens 1 (used to present dimming results, lighting parameters, and fault prompts), an integrated microphone 2 (or microphone array, used to collect voice signals and perform noise reduction and echo cancellation preprocessing), a speaker 3 (used to broadcast dimming results and fault prompts), and a charging port 4 (to ensure device battery life). The smart glasses also include a main processor 5 with integrated Bluetooth (i.e., the aforementioned main control module 130) and a camera 6 (used for taking pictures). All hardware components are compactly arranged within the smart glasses body, satisfying both wearability convenience and supporting the entire process of operation from networking, command acquisition and parsing to lighting control feedback through collaborative work.

[0062] Reference Figure 6 , Figure 6 This is a flowchart of a voice-controlled light dimming method performed by a smart wearable device according to an embodiment of this application. The smart wearable device can be any of the smart wearable devices provided in any embodiment of this application. The method includes, but is not limited to, steps S610 to S650.

[0063] In step S610, the smart wearable device establishes a wireless communication connection with multiple photography lights.

[0064] In this step, the smart wearable device 100 can first establish a wireless communication connection with multiple photography lights through its built-in wireless communication module. For example, the smart wearable device 100 (such as smart glasses, a smart helmet, or a smart vest) can act as the master node of a Bluetooth Mesh network to initiate the networking process, establishing a stable wireless connection with multiple photography lights 200 on site that each possess a unique device identifier (such as a MAC address or UUID). During the networking process, "NFC-enabled lights" can be added via the NFC module, simplifying the connection operation of the photography lights 200. During the network configuration phase, the smart wearable device 100 assigns a dedicated unicast address to each connected camera light 200 (for precise control of a single light). It also supports assigning multicast addresses to some camera lights 200 based on the needs of multi-light group collaborative control (such as grouping multiple background lights into one group and assigning a unified multicast address). Simultaneously, it maintains a complete address mapping table, clearly associating the light ID of each camera light 200 with the corresponding unicast / multicast address. At the same time, it can build and store the device capability model of each camera light during this phase (recording supported control parameters such as brightness, color temperature, color, etc.), laying the foundation for subsequent precise light control, command parsing, and device matching, ensuring that each camera light can be managed and controlled in an orderly manner after network configuration.

[0065] In step S620, the smart wearable device configures at least one semantic identifier for each of the photography lights to distinguish it from other photography lights.

[0066] In this step, after the smart wearable device establishes wireless communication connections with multiple photography lights and obtains basic information such as the unique device identifier (e.g., MAC address or UUID), unicast / multicast address, model, manufacturer, and supported control channels for each light, it can configure at least one semantic identifier for each light that is easy for users to understand and trigger via voice. This identifier must be unique to distinguish different lights. Types can include "main light," "auxiliary light," and "background light" based on lighting functions; "front light" and "right light" based on spatial location; and "auxiliary light group" and "light group A" based on group control. Configuration methods can be automatically recommended by the smart wearable device after capturing scene images and identifying the location, model, and appearance of the lights, or manually set by the user via voice or the device's interface. These semantic identifiers are deeply associated with the light ID, address, and device capability model of the photography lights and stored in an address mapping table, forming a complete mapping relationship of "semantic identifier - light ID - unicast / multicast address - device capability." This lays the foundation for quickly locating the target photography light and achieving precise light control during subsequent voice command parsing.

[0067] Among them, smart wearable devices can respond to user input or preset rules to set one or more text labels as semantic identifiers for each photography light. These text labels can be used to characterize the function or position of the photography light in the photography lighting scene.

[0068] Specifically, semantic labeling can be set in two scenarios: First, user input triggering. Users can manually set text labels for each camera light according to the lighting plan through the interactive interface of the smart wearable device or voice commands. For example, the light responsible for main lighting can be named "main light," the side fill light can be named "side fill light," or named "left front light" and "right rear light" according to their actual placement. Second, preset rules triggering. After the smart wearable device completes wireless communication connection, it can take pictures of the lighting scene through the camera, identify the shape, size, model and spatial distribution of the lights, and then automatically generate text labels according to preset rule models (such as the relative position of the lights and the subject, and the default division rules of lighting functions). For example, the light closest to the subject can be marked as "close-up light," and the lights in the background area can be marked as "background light group."

[0069] Each photography light supports the configuration of one or more text tags to adapt to the diverse lighting control needs of complex lighting scenarios. For example, a light can be simultaneously labeled as "left auxiliary light" (position + function), supporting both location-based and function-based invocation. These text tags are deeply associated with the photography light's unique device identifier (MAC address / UUID), unicast / multicast address, and device capability model, and stored in the address mapping table of the smart wearable device, forming a complete mapping relationship of "text tag - light ID - device information." This provides the core basis for quickly locating the target light and achieving precise lighting control during subsequent voice command parsing, while reducing the cost for users to remember complex device identifiers and making lighting control operations more in line with the usage habits of shooting scenarios.

[0070] In step S630, the smart wearable device collects the user's voice signal and performs speech recognition and semantic parsing on the user's voice signal to extract user commands.

[0071] In this step, the smart wearable device 100 can collect the user's voice signal for controlling the lights in the shooting scene through its built-in microphone array. After collection, it first performs preprocessing such as noise reduction and echo cancellation to filter environmental interference and improve signal purity. Then, it calls the local or cloud-based ASR (speech recognition) engine, combines acoustic and language models for decoding, and converts the voice signal into a text signal. It can also recognize pauses in the user's speech and automatically insert punctuation marks or segmentation marks (e.g., converting "adjust the front light color temperature and adjust the rear light brightness" into "adjust the front light color temperature and adjust the rear light brightness"). Finally, it uses natural language understanding (NLE) to process the text. The U module or large model performs semantic parsing on text signals. On the one hand, it segments the complex text to extract multiple independent instruction intents. On the other hand, it extracts key information for each intent, including target device selection conditions (such as "front light", "rear light", etc.), control actions (adjust up, adjust down, adjust to), adjustment parameters (brightness, color temperature, color, focus, etc.) and parameter values ​​(such as 88%, default step size 10%). It also supports the parsing of synonyms such as "warm up" and "cool down" and the decomposition of complex multi-parameter instructions, ultimately forming clear and executable user instructions, providing a basis for subsequent target lamp determination and dimming control instruction generation.

[0072] The user instructions include at least one user intent, which represents a lighting adjustment operation for one of a plurality of camera lights. Each user intent explicitly targets a specific lighting adjustment operation for one (or a group of) camera lights in a Bluetooth Mesh network. Specifically, the smart wearable device first collects the user's spoken voice for controlling the lights through a microphone array (i.e., the voice acquisition module). After noise reduction and echo cancellation preprocessing, the voice is converted into a text signal by a local or cloud-based ASR engine. During this process, pauses in the user's spoken speech are identified and punctuation marks (such as commas and periods) are inserted to provide a basis for intent segmentation. Subsequently, the Natural Language Understanding (NLU) module parses the text, first segmenting the complex text containing multiple lighting control requests into independent user intents (e.g., the user's voice "increase the color temperature of the front light and decrease the brightness of the auxiliary light" can be segmented into two intents: "increase the color temperature of the front light" and "decrease the brightness of the auxiliary light"). Each intent revolves around a single adjustment target. The target device selection for these intents relies on the semantic tags (such as "front light", "fill light", "background light group") configured for each camera light during the network configuration phase, accurately identifying the corresponding single or group of camera lights. Each intent also fully includes control actions (adjust up, adjust down, adjust to, etc.), adjustment parameters (brightness, color temperature, color, light focus, etc.) and parameter values ​​(such as specific percentages, default 10% increments). It supports the parsing of synonyms such as "warming up" and "cooling down" and verifies whether the target light supports the corresponding adjustment parameters through the device capability model. This ensures that each intent can drive the target camera light to perform effective light adjustment operations, adapting to the diverse single or group light control needs in shooting scenarios, and achieving precise binding between semantic tags and light control intents.

[0073] Lighting adjustment operations include at least one of the following: brightness adjustment, color temperature adjustment, color adjustment, focus adjustment, rotation adjustment, and tilt angle adjustment. Brightness adjustment supports both fixed numerical adjustments (e.g., to 80%) and preset step adjustments (e.g., 10%). Mesh models commonly use a range of 0-255 or 0-100% to quantize brightness values. Color temperature adjustment supports precise adjustments based on synonyms such as "warmer," "warmer" (corresponding to a decrease in color temperature), "cooler," and "cooler" (corresponding to an increase in color temperature). Color adjustment is compatible with various light sources such as dual-color temperature LEDs, RGB LEDs, RGBW, and RGBWW, and some also support special lighting effects modes such as dynamic color light effects. Focus, rotation, and tilt angle adjustments can be implemented mechanically or electronically based on user voice commands to meet the lighting angle and focus requirements of different shooting scenarios. These adjustments can be triggered by single-parameter or multi-parameter composite voice commands, which are then analyzed by smart wearable devices to generate corresponding control signals that drive the target lighting precisely.

[0074] Specifically, refer to Figure 7 , Figure 7 This application provides a flowchart of the steps for a smart wearable device to collect user voice signals and perform speech recognition and semantic parsing on the user voice signals to extract user commands, including but not limited to steps S710 to S720.

[0075] Step S710: The smart wearable device collects the user's voice signal and converts the user's voice signal into text information through a local or cloud-based automatic speech recognition engine. In step S720, the smart wearable device performs semantic parsing of the text information through a natural language understanding module or a large model to extract user instructions.

[0076] In this embodiment, the smart wearable device 100 can accurately collect the user's voice signals for controlling lights in scenarios such as photography and film shooting through its built-in microphone array. These signals can cover various types, including single-parameter commands (such as "adjust the front light brightness to 88%)" and multi-parameter composite commands (such as "increase the front light color temperature and decrease the rear light brightness"). After collection, the device first performs preprocessing on the voice signal, such as noise reduction and echo cancellation, to effectively filter out interference factors such as ambient noise and equipment operating sounds at the shooting location, ensuring signal purity. Subsequently, the smart wearable device 100 can call upon a local or cloud-based Automatic Speech Recognition (ASR) engine, combining an acoustic model and a language model for decoding. The acoustic model is responsible for determining the optimal phoneme sequence that generates the acoustic features of the speech, while the language model, based on massive amounts of text training results, selects the most grammatically and semantically reasonable word sequence, ultimately converting the speech signal into text information. During this process, the engine can recognize pauses in the user's spoken language and automatically insert punctuation marks (such as commas and periods) or segmentation marks. For example, it can convert speech text without punctuation into "turn up the color temperature of the headlights and turn down the brightness of the taillights", providing a clear foundation for subsequent semantic parsing and intent segmentation.

[0077] Next, the smart wearable device 100 can perform deep analysis of the text information converted in step S710 through its built-in Natural Language Understanding (NLU) module or large model. First, intent segmentation is performed. For complex text containing multiple lighting control requirements, independent instruction intents are extracted (e.g., splitting the complex text into two sub-intents: "increase the color temperature of the front light" and "decrease the brightness of the rear light"). Then, according to preset parsing rules, key elements of each sub-intent are extracted, including target device selection conditions (e.g., "front light," "rear light," etc.), control actions (e.g., "increase to," "increase," "decrease"), adjustment parameters (e.g., brightness, color temperature, color, light focus, light rotation / tilt angle, etc.), and parameter values ​​(e.g., 88%, default step size 10%). During the parsing process, it also supports synonym conversion (e.g., "warm up," "increase" is parsed as "decrease color temperature," "cool down," "cool down" is parsed as "increase color temperature") and complex multi-parameter instruction splitting. Simultaneously, it combines the device capability model defined in the network configuration phase to verify parameter adaptability (e.g., determining whether the lighting fixture supports color temperature adjustment). Finally, the analysis results are integrated into clear and executable user instructions, providing a precise basis for subsequent target luminaire determination, dimming parameter calculation, and control instruction generation.

[0078] In step S640, the smart wearable device determines the target camera light to be dimmed based on the user's instructions and the semantic identifier of each camera light.

[0079] In this step, after the smart wearable device completes user voice signal acquisition, preprocessing, ASR conversion, and NLU semantic parsing, it can first extract at least one user intent from the extracted user commands, clarifying the target device selection criteria (such as semantic keywords like "front light" and "auxiliary light group"), control actions, and adjustment parameters contained in each intent. Then, it calls the address mapping table stored in the network configuration phase to accurately match the semantic keywords in the commands with the semantic identifiers of each camera light to pinpoint the target light fixture. By directly matching the corresponding identifiers of individual or group camera lights through semantic tags, the matching process combines the device capability model to verify whether the target light fixture supports the adjustment parameters in the command. Finally, it determines a unique or group of target camera lights to be dimmed from multiple camera lights and obtains their corresponding unicast or multicast addresses, providing precise guidance for the subsequent generation and issuance of dimming control commands.

[0080] In step S650, the smart wearable device generates a corresponding dimming control command based on the user's instruction and sends the dimming control command to the target photography light to drive the target photography light to perform the corresponding light adjustment operation.

[0081] In this step, after identifying the target camera light to be dimmed, the smart wearable device 100 can perform precise calculations of the dimming parameters based on the user instructions extracted through semantic parsing (including key information such as control actions, adjustment parameters, and parameter values). Specifically, if the instruction is a "adjust to a specified value" type (such as "adjust brightness to 80%)", the adjusted parameter value can be obtained by multiplying the maximum brightness value by a specified ratio according to the brightness quantization range commonly used in Mesh models of 0-255 or 0-100%. If the instruction is a "adjust up" or "adjust down" type step adjustment instruction (such as "adjust brightness up"), the current parameter status of the target camera light can be obtained through Mesh status query or local cache, and the target parameter value can be calculated by combining it with a preset adjustment step size (such as 10%). At the same time, it can verify whether the target camera light supports the adjustment parameter (such as determining whether the lamp supports color temperature adjustment). Subsequently, based on the calculated target parameter value and the unicast address (or multicast address) corresponding to the target camera light, a dimming control instruction conforming to the communication protocol (such as the BLE Mesh protocol) specification can be constructed. Finally, the smart wearable device uses its built-in wireless communication module to precisely send the control command to the target photography light, thereby driving the target photography light to perform corresponding lighting adjustment operations such as brightness, color temperature, color, light focus, rotation or tilt angle, completing the closed-loop control from command generation to execution.

[0082] Specifically, refer to Figure 8 , Figure 8This application provides a flowchart of the steps for a smart wearable device to generate a corresponding dimming control command based on a user instruction and send the dimming control command to the target photography light to drive the target photography light to perform a corresponding light adjustment operation, including but not limited to steps S810 to S840.

[0083] In step S810, the smart wearable device obtains the target parameter adjustment information corresponding to the target photography light to be dimmed according to the user's instructions.

[0084] In this step, after completing voice recognition and semantic analysis, the smart wearable device 100 can accurately filter out the target parameter adjustment information corresponding to the target photographic light to be dimmed from the extracted user commands. This target parameter adjustment information covers core control elements: first, control actions, including types such as "adjust to," "adjust up," and "adjust down." If it is color temperature adjustment, it also includes the action logic corresponding to synonyms such as "warm up" and "cool down" ("warm up" corresponds to a decrease in color temperature value, and "cool down" corresponds to an increase in color temperature value); second, adjustment parameters, specifying specific adjustment dimensions such as brightness, color temperature, color, light focus, and the rotation or tilt angle of the light; and third, associated parameter values. For commands like "adjust to," it includes specific values ​​(e.g., 88%), while commands like "adjust up" and "adjust down" correspond to preset adjustment steps (e.g., 10%). For complex multi-parameter commands, they have been broken down into single sets of adjustment information during the semantic analysis stage to ensure that the content obtained in this step accurately corresponds to a single adjustment requirement.

[0085] Step S820: The smart wearable device acquires the current value of the target parameters of the target photography light.

[0086] In this step, the smart wearable device 100 can obtain the current values ​​of the adjustment parameters corresponding to the target photography light in two ways: first, by sending a status query command to the target photography light through the wireless communication module to obtain its current parameter data in real time; second, by directly calling the historical parameter information of the photography light stored in the local cache (this cache will be updated synchronously after each dimming to ensure data timeliness). The obtained current values ​​need to be compatible with parameter quantification standards. For example, the brightness value needs to correspond to the 0-255 or 0-100% range commonly used in Mesh models to provide a unified data foundation for subsequent calculations. At the same time, if the target parameter is an adjustment dimension not supported by the device capability model (such as the color adjustment of white light fixtures), it will be identified and marked synchronously at this stage to prepare for subsequent feedback of fault information.

[0087] In step S830, the smart wearable device calculates the target value of the target parameter corresponding to the target photography light based on the current value of the target parameter of the target photography light and the target parameter adjustment information.

[0088] In this step, the smart wearable device 100 calculates the target value according to the current value of the target parameter and the target parameter adjustment information, following the corresponding rules. Specifically, for a "raise to" type of instruction, the specific value in the instruction can be directly used as the target value (brightness needs to be converted according to the quantization range, such as converting 80% to the corresponding value in the 0-255 range); for a "raise" or "lower" type of step adjustment instruction, the current value is used as the base, and a preset step size is added or subtracted (e.g., if the current brightness is 50%, after raising it by 10%, the target value is 60%), ensuring that the adjustment range meets the user's expectations. During the calculation process, it will check whether the target value is within the maximum adjustable range of the parameter to avoid exceeding the device's adjustment limits. If it exceeds the limits, the maximum or minimum value will be automatically used as the target value.

[0089] In step S840, the smart wearable device generates a corresponding dimming control command based on the target value of the target parameter corresponding to the target photography light, and sends the dimming control command to the target photography light to drive the target photography light to perform the corresponding light adjustment operation.

[0090] In this step, the smart wearable device 100 combines the calculated target value of the target parameter with the unicast address (or multicast address, for group control scenarios) of the target lighting light to construct a dimming control command conforming to the communication protocol (such as the BLE Mesh protocol), clearly defining the recipient and execution standard of the command. Subsequently, the control command is precisely sent to the target lighting light via its built-in wireless communication module. Upon receiving the command, the target lighting light performs the corresponding light adjustment operation to ensure the parameters are adjusted to the target value. If the adjustment fails (e.g., signal timeout, device offline), it will report the fault information to the smart wearable device, which will then notify the user via voice or display.

[0091] In some embodiments, refer to Figure 9 , Figure 9 This is a flowchart of another step in the process of a smart wearable device according to an embodiment of the present application generating a corresponding dimming control command based on a user instruction and sending the dimming control command to the target photography light to drive the target photography light to perform a corresponding light adjustment operation, including but not limited to steps S910 to S920.

[0092] Step S910: The smart wearable device obtains the target parameter adjustment information corresponding to the target photography light to be dimmed according to the user's instructions; In step S920, the smart wearable device generates a corresponding dimming control command based on the target parameter adjustment information corresponding to the target photography light, and sends the dimming control command to the target photography light so that the target photography light calculates the target value of the target parameter corresponding to the target photography light based on the current value of the target parameter and the target parameter adjustment information, and performs the corresponding light adjustment operation based on the target value of the target parameter.

[0093] In this embodiment, after completing voice recognition and semantic parsing, the smart wearable device 100 can accurately extract the target parameter adjustment information corresponding to the target photography light to be dimmed from the extracted user commands. Next, based on the target parameter adjustment information obtained in step S910, the smart wearable device 100, combined with the unicast address (or multicast address, for group control scenarios) of the target photography light, constructs a dimming control command conforming to a communication protocol (such as the BLE Mesh protocol). The command clearly includes key information such as control actions, adjustment parameters, and associated parameter values, but does not need to carry the current and target values ​​of the parameters. Subsequently, the smart wearable device 100 can accurately send the control command to the target photography light through its built-in wireless communication module. After receiving the command, the target photography light first calls its own stored target parameter current value (or obtains the real-time current value through device status self-check), and then calculates the target value according to preset rules and the adjustment information in the command. Specifically, for commands like "increase to," the target light directly uses the specific value in the command as the target value (brightness must be compatible with the quantization range of the Mesh model, which is 0-255 or 0-100%). For step commands like "increase" or "decrease," the target light uses the current value as a base, adding or subtracting a preset step size to calculate the target value. During the calculation, it checks whether the target value is within its maximum adjustable range to avoid exceeding the device's adjustment limits. Finally, based on the calculated target parameter values, the target light executes the corresponding light adjustment operation, completing precise adjustments to dimensions such as brightness, color temperature, and color. If signal abnormalities or parameters exceeding the range occur during the adjustment process, the target light will report fault information to the smart wearable device 100, which will then inform the user via voice broadcast or display module (e.g., "Adjustment failed, please check if the light is online"). Understandably, smart wearable devices can pre-configure the light adjustment operation type, adjustment step size, and maximum adjustable value for each type of photographic light. Specifically, the smart wearable device 100 can target different types of photographic lights, such as stick lights, board lights, COB lights, gas lights, and flashes, based on their light source characteristics (e.g., dual-color temperature LED, RGB). Standardized configurations are pre-completed for LED, RGBW, RGBWW, and other supported control channels. Specifically, this includes configuring corresponding light adjustment operation types (such as basic brightness adjustment, color temperature adjustment for dual-color temperature lights, color adjustment for RGB series lights, and focal length, rotation, and tilt angle adjustment for lights with mechanical functions) according to the hardware capabilities of each type of photography light. Adjustment step sizes are preset for each adjustment type to adapt to the characteristics of the device (such as a default step size of 10% for brightness and color temperature adjustment, and a reasonable step size preset according to the mechanical precision of the device) and the maximum adjustable value range is configured according to the hardware parameter limits of each type of photography light (such as brightness following the quantization standard of 0-255 or 0-100% of the Mesh model, color temperature preset with upper and lower limits according to the actual coverage of the device, and angle adjustment with the physical limits of the mechanical structure as the boundary). These configurations are associated with the device identifier of each type of photography light and stored locally. They can be automatically matched and called after subsequent networking to ensure that the dimming operation is accurate, efficient, and in line with the characteristics of the device.

[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0095] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0096] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0097] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the methods according to the embodiments of this application.

[0098] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the appended claims.

Claims

1. A voice-controlled light dimming method, characterized in that, Applied to smart wearable devices, the method includes: The smart wearable device establishes wireless communication connections with multiple photography lights; The smart wearable device configures at least one semantic identifier for each of the photography lights to distinguish it from other photography lights; The smart wearable device collects the user's voice signal and performs speech recognition and semantic parsing on the user's voice signal to extract user commands; The smart wearable device determines the target photography light to be dimmed based on the user instructions and the semantic identifier of each photography light; The smart wearable device generates a corresponding dimming control command based on the user's instruction and sends the dimming control command to the target photography light to drive the target photography light to perform the corresponding light adjustment operation.

2. The method according to claim 1, characterized in that, The smart wearable device configures at least one semantic identifier for each of the photography lights to distinguish it from other photography lights, including: In response to user input or preset rules, the smart wearable device sets one or more text labels as semantic identifiers for each of the photography lights. The text labels are used to characterize the function or position of the photography light in the photography lighting scene.

3. The method according to claim 1, characterized in that, After the smart wearable device generates a corresponding dimming control command based on the user instruction and sends the dimming control command to the target photography light to drive the target photography light to perform the corresponding light adjustment operation, the method further includes: The smart wearable device announces the result of the light adjustment operation through a voice broadcast module, and / or the smart wearable device displays the result of the light adjustment operation through a display module.

4. The method according to claim 1, characterized in that, The smart wearable device collects the user's voice signal and performs speech recognition and semantic parsing on the user's voice signal to extract user commands, including: The smart wearable device collects the user's voice signal and converts the user's voice signal into text information through a local or cloud-based automatic speech recognition engine; The smart wearable device uses a natural language understanding module or a large model to perform semantic parsing on the text information in order to extract user instructions.

5. The method according to claim 1 or 4, characterized in that, The user instructions include at least one user intent, which represents a lighting adjustment operation on one of the plurality of camera lights.

6. The method according to claim 1 or 5, characterized in that, The lighting adjustment operation includes at least one of the following: lighting brightness adjustment, lighting color temperature adjustment, lighting color adjustment, lighting focal length adjustment, lighting rotation, and lighting tilt angle adjustment.

7. The method according to claim 1, characterized in that, The smart wearable device generates a corresponding dimming control command based on the user instruction, and sends the dimming control command to the target photography light to drive the target photography light to perform corresponding light adjustment operations, including: The smart wearable device obtains target parameter adjustment information corresponding to the target photography light to be dimmed according to the user's instructions; The smart wearable device acquires the current values ​​of the target parameters of the target photography light; The smart wearable device calculates the target value of the target parameter corresponding to the target photography light based on the current value of the target parameter of the target photography light and the target parameter adjustment information; The smart wearable device generates a corresponding dimming control command based on the target value of the target parameter corresponding to the target photography light, and sends the dimming control command to the target photography light to drive the target photography light to perform the corresponding light adjustment operation.

8. The method according to claim 1, characterized in that, The smart wearable device generates a corresponding dimming control command based on the user instruction, and sends the dimming control command to the target photography light to drive the target photography light to perform corresponding light adjustment operations, including: The smart wearable device obtains target parameter adjustment information corresponding to the target photography light to be dimmed according to the user's instructions; The smart wearable device generates a corresponding dimming control command based on the target parameter adjustment information corresponding to the target photography light, and sends the dimming control command to the target photography light, so that the target photography light calculates the target value of the target parameter corresponding to the target photography light based on the current value of the target parameter of the target photography light and the target parameter adjustment information, and performs corresponding light adjustment operation based on the target value of the target parameter.

9. The method according to claim 1, characterized in that, The method further includes: The smart wearable device pre-configures the lighting adjustment operation type, adjustment step size, and maximum adjustable value for each type of photographic light.

10. A smart wearable device, characterized in that, include: The smart wearable device communicates wirelessly with each camera light via a wireless communication module. A voice acquisition module, which is used to acquire user voice signals; The main control module is connected to the wireless communication module and the voice acquisition module respectively, and the main control module is used to execute the method according to any one of claims 1-9.

11. The smart wearable device according to claim 10, characterized in that, The smart wearable device also includes: A voice broadcast module, which is connected to the main control module, is used to broadcast the results of the lighting adjustment operation; and / or a display module, the display module being connected to the main control module, the display module being used to display the result of the light adjustment operation.

12. The smart wearable device according to claim 10, characterized in that, The smart wearable device also includes: An NFC module is connected to the main control module. When the smart wearable device approaches the photography light, the NFC module performs NFC communication and triggers the smart wearable device to establish a communication connection with the photography light.

13. A voice-controlled lighting dimming system, characterized in that, include: The smart wearable device according to any one of claims 10-12; Multiple photographic lights are wirelessly connected to the smart wearable device, which is configured to send messages to the multiple photographic lights.

Images