A wall corridor lighting control method, device, electronic device and storage medium

Abstract

The present invention provides a wall corridor lighting control method, device, electronic device and storage medium, and relates to the field of lighting control technology. The wall corridor lighting control method includes the steps of: receiving audio information sent by a tour guide in real time; analyzing the audio information through a preset voice model to determine keyword information in the audio information; when a preparatory switching prompt word appears in the audio information, based on a preset database, determining the display effect of the light through the preparatory switching prompt word; after the preparatory switching prompt word appears in the audio information and when the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, switching the light to the corresponding display effect according to the execution switching prompt word. The wall corridor lighting control method of the present invention solves the problem that the traditional lighting control mode cannot create a suitable atmosphere according to the tour guide's commentary rhythm. It creates an immersive atmosphere by coordinating with the tour guide's commentary rhythm, which is conducive to improving the tourist experience.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting control, and in particular to a wall corridor lighting control method, device, electronic equipment and storage medium. Background Art

[0002] In places such as museums, cultural centers, and scenic spots, pictures and texts are usually arranged on the wall corridors and accompanied by tour guides' explanations to show the past history. Generally, the wall corridors located indoors are equipped with lighting equipment. The main function of the lighting equipment is to provide sufficient light so that tourists can view the pictures and texts on the wall corridors. In actual applications, the design of the lighting equipment's brightness and light color can also play a role in creating an atmosphere.

[0003] There are generally two control modes for lighting equipment on wall corridors:

[0004] One is to use static control, where the lighting equipment always maintains the brightness and color set last time. However, this control method often lacks an immersive experience for tourists and is difficult to arouse their interest.

[0005] The second is to adopt semi-automatic dynamic control, in which the lighting equipment changes in a cycle according to established rules. In actual application, tour guides generally introduce the pictures and texts on the wall corridor according to the historical process, and this cyclically changing lighting is often difficult to adapt to the tour guide's explanation rhythm, causing the lighting to create an inappropriate atmosphere, thus failing to achieve a complementary effect with the tour guide, which is undoubtedly not conducive to the tourists' immersive experience.

[0006] There is currently no effective technical solution to the above problems. Summary of the Invention

[0007] The purpose of the present invention is to provide a wall corridor lighting control method, device, electronic device and storage medium to solve the problem that traditional lighting control modes cannot create a suitable atmosphere according to the tour guide's commentary rhythm. By creating an immersive atmosphere in accordance with the tour guide's commentary rhythm, it is beneficial to improve the tourist experience.

[0008] In a first aspect, the present invention provides a wall corridor lighting control method, which is applied to a wall corridor lighting control system, comprising the following steps:

[0009] S1. Receive audio information sent by the tour guide in real time;

[0010] S2. Analyzing the audio information by a preset voice model to determine keyword information in the audio information, the keyword information includes a preparatory switching prompt word and an execution switching prompt word;

[0011] S3. When the preparatory switching prompt word appears in the audio information, the lighting display effect is determined based on the preparatory switching prompt word based on a preset database; the preparatory switching prompt word corresponds to at least one execution switching prompt word and the corresponding relationship is pre-stored in the database, and each execution switching prompt word corresponds to a display effect and the corresponding relationship is pre-stored in the database;

[0012] S4. After the preparatory switching prompt word appears in the audio information and when the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, the light is switched to a corresponding display effect according to the execution switching prompt word.

[0013] The wall corridor lighting control method provided by the present invention controls the lighting to adaptively change according to the tour guide's voice commentary, thereby cooperating with the tour guide to create a suitable atmosphere at the right time, greatly improving the tourist experience.

[0014] Furthermore, the specific steps in step S2 include:

[0015] S21 preprocesses the audio information;

[0016] S22. Converting the preprocessed audio information into text;

[0017] S23. Perform semantic interpretation on the text and mark all the preparatory switching prompt words and the execution switching prompt words.

[0018] This application greatly improves the adaptability and accuracy of the system by introducing a complete process of preprocessing, speech recognition and semantic analysis.

[0019] Furthermore, the specific steps in step S21 include:

[0020] S211. Remove background noise from the audio information;

[0021] S212. Dividing the audio information after removing background noise into short time frames;

[0022] S213. After adding a window function to the short-time frame, extract the feature information of each short-time frame to convert the audio information into a feature vector; the feature vector is used to represent the time-frequency characteristics of the audio information; the feature information includes Mel-frequency cepstral coefficients and linear predictive coding.

[0023] High-quality preprocessing output provides clearer and more effective input for the speech model, thereby improving the accuracy and stability of subsequent analysis.

[0024] Furthermore, the specific steps in step S3 include:

[0025] S3A1. When the audio information appears to prepare the switching prompt word, based on a preset database, the display effect of the light is determined by the prepared switching prompt word and the wall gallery lighting control system enters a ready state; in the ready state, the wall gallery lighting control system starts a timer and counts down according to a preset duration;

[0026] The specific steps in step S4 include:

[0027] S41. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, if the execution switching prompt word appears before the countdown ends, the light is switched to the corresponding display effect according to the execution switching prompt word, otherwise the control system exits the preparatory state and returns to execute step S1.

[0028] This design not only ensures the timeliness of lighting switching, but also provides a certain degree of flexibility for the tour guide's explanation rhythm, while avoiding erroneous lighting switching, effectively improving the accuracy and adaptability of lighting control, and enhancing the immersive experience of tourists.

[0029] Furthermore, the specific steps in step S3 also include:

[0030] S3B1 after determining the guide position by monitoring, obtain the text information corresponding to the guide position on the wall gallery; the text information is pre-arranged on the wall gallery and is recorded in the database, the text information includes the preparatory switch prompt word and the execution switch prompt word;

[0031] S3B2 based on the text information from the database to filter out the text information in the preparation of the switch prompt word and the corresponding relationship between the execution switch prompt word and the corresponding relationship between the display effect and extract as the target data;

[0032] S3B3. When the preparatory switching prompt word appears in the audio information, the display effect of the light is determined by the preparatory switching prompt word based on the target data.

[0033] Furthermore, the specific steps of switching the light to a corresponding display effect according to the execution switching prompt include:

[0034] S411. The guide and the tourists led by the guide are regarded as a team, and the lighting device corresponding to the team position and team length on the wall corridor is selected as the target device to ensure that the light emitted by the target device can be viewed by all tourists in the team;

[0035] S412. Keep the operating status of other lighting devices on the wall corridor unchanged except for the target device. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, only switch the light of the target device to the corresponding display effect according to the execution switching prompt word.

[0036] In a second aspect, the present invention provides a wall corridor lighting control device, which is applied to a wall corridor lighting control system, comprising:

[0037] A receiving module is used to receive audio information sent by the tour guide in real time;

[0038] an analysis module, configured to analyze the audio information using a preset voice model to determine keyword information in the audio information, wherein the keyword information includes a preparatory switching prompt word and an execution switching prompt word;

[0039] a preparation module configured to, when the preparatory switching prompt word appears in the audio information, determine a light display effect based on the preparatory switching prompt word based on a preset database; the preparatory switching prompt word corresponds to at least one execution switching prompt word, and the corresponding relationship is pre-stored in the database; and each execution switching prompt word corresponds to a display effect, and the corresponding relationship is pre-stored in the database;

[0040] The switching module is used to switch the light to a corresponding display effect according to the execution switching prompt word after the preparatory switching prompt word appears in the audio information and when the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information.

[0041] The wall gallery lighting control device provided by the present invention can make the lighting effects accurately match the content and rhythm of the tour guide's explanation, providing visitors with a more immersive experience. At the same time, due to the adoption of the dual mechanism of preparatory switching and execution switching, the system can effectively avoid false triggering caused by the tour guide accidentally mentioning certain words, thereby improving the accuracy and reliability of control.

[0042] Furthermore, the analysis module performs the following when analyzing the audio information using a preset speech model to determine keyword information in the audio information:

[0043] S21 preprocesses the audio information;

[0044] S22. Converting the preprocessed audio information into text;

[0045] S23. Perform semantic interpretation on the text and mark all the preparatory switching prompt words and the execution switching prompt words.

[0046] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps of the wall corridor lighting control method provided in the first aspect are executed.

[0047] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the wall corridor lighting control method provided in the first aspect are executed.

[0048] From the above, it can be seen that the wall corridor lighting control method provided by the present invention determines the tour guide's commentary rhythm through real-time analysis of the voice model and uses keyword information to achieve adaptive control of the lighting, thereby creating a suitable atmosphere at the right time, achieving a mutually beneficial effect of lighting equipment and people, and helping tourists to obtain a better immersive experience.

[0049] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the embodiments of the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flow chart of a corridor lighting control method provided in an embodiment of the present invention.

[0051] Figure 2 A schematic structural diagram of a wall corridor lighting control device provided in an embodiment of the present invention.

[0052] Figure 3 A schematic structural diagram of an electronic device provided by an embodiment of the present invention.

[0053] Description of labels:

[0054] 100, receiving module; 200, analyzing module; 300, preparatory module; 400, switching module; 13, electronic device; 1301, processor; 1302, memory; 1303, communication bus. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0056] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are used only to distinguish the description and should not be understood as indicating or implying relative importance.

[0057] The corridors of museums, cultural centers, scenic spots, and other places often feature illustrations and text, accompanied by tour guides' explanations, to showcase history. To provide a positive viewing experience, these corridors are equipped with lighting devices. These lighting devices not only provide ample light but also create an atmosphere by adjusting brightness and color. However, existing methods for controlling corridor lighting have significant shortcomings. In static control mode, the lighting devices maintain a fixed brightness and color, making it difficult to provide an immersive experience for visitors. While semi-automatic dynamic control modes can achieve cyclical changes in lighting, they often struggle to match the rhythm of the guide's explanations, resulting in a disharmony between the lighting effects and the content of the explanations, impacting the quality of the visitor experience.

[0058] Specifically, the problem of lighting control being out of sync with the tour guide's explanation is particularly prominent in practical applications. For example, in a historical museum, the wall gallery displays the rise and fall of a dynasty in chronological order. When explaining, the tour guide needs to adjust the tone and rhythm according to different historical stages to highlight important events and turning points. However, the existing lighting control system is unable to perceive the guide's progress and key points, resulting in a serious disconnect between the lighting effects and the content of the explanation. When the guide is describing a major battle, the lighting may remain calm; when the explanation enters a period of peace and prosperity, the lighting may suddenly shift to a fierce red. This disharmony not only fails to enhance the explanation, but also distracts visitors and reduces the overall visiting experience.

[0059] As can be seen, failure to effectively address the issue of the corridor lighting control being out of sync with the guide's commentary will lead to numerous technical consequences. First, the lighting will not accurately align with the content of the commentary, losing its crucial function of enhancing information transmission and emotional expression. Second, uncoordinated lighting changes can distract visitors and reduce the efficiency of information reception. Furthermore, this asynchrony will reduce the intelligence level of the entire display system and the quality of user experience. From a technical perspective, this issue highlights the shortcomings of existing corridor lighting control systems in terms of real-time responsiveness and contextual understanding. There is an urgent need for an intelligent control method that can accurately capture the guide's commentary and adjust the lighting effects in real time.

[0060] refer to Figure 1 The present invention provides a wall corridor lighting control method, which is applied to a wall corridor lighting control system and includes the following steps:

[0061] S1. Receive audio information sent by the tour guide in real time;

[0062] S2 analyzes the audio information by a preset voice model to determine the keyword information in the audio information, the keyword information includes the preparatory switch prompt word and the execution switch prompt word;

[0063] S3. When the audio information appears to prepare the switching prompt word, based on a preset database, the display effect of the light is determined by preparing the switching prompt word; the prepared switching prompt word corresponds to at least one execution switching prompt word and the corresponding relationship is pre-stored in the database, each execution switching prompt word corresponds to a display effect and the corresponding relationship is pre-stored in the database;

[0064] S4. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, the light is switched to the corresponding display effect according to the execution switching prompt word.

[0065] Audio information refers to the real-time voice data transmitted by the tour guide, which can be achieved using a microphone or other audio acquisition device. Specifically, audio acquisition devices are pre-prepared for each tour guide. Each audio acquisition device has a unique identification ID and is bound to the corresponding tour guide's identity, thereby distinguishing the voice data of different tour guides.

[0066] Among them, the speech model refers to the algorithm model used to analyze and recognize speech content, which can be implemented using deep learning or machine learning methods.

[0067] Among them, keyword information refers to important words extracted from audio, including preparatory switching prompt words and execution switching prompt words, which can be specifically implemented using natural language processing technology.

[0068] The preset database refers to a data storage system that stores the corresponding relationship between the preparatory switching prompt words, the execution switching prompt words and the display effects, and can be implemented by using a relational database or a non-relational database.

[0069] Among them, the display effect refers to the visual presentation of light brightness, color, change mode, etc., which can be achieved by using LED lights or other adjustable lighting equipment.

[0070] The core innovation of this application lies in the introduction of a dual mechanism for controlling the gallery lighting: pre-switching prompts and execution prompts. This mechanism analyzes the tour guide's audio information in real time, pre-determining the lighting display when the pre-switching prompt is recognized, and then actually switching the lights when the execution prompt is recognized. This design not only accurately synchronizes lighting changes with the tour guide's explanations, but also effectively reduces the probability of false triggering, improving system reliability and flexibility.

[0071] The working principle of this application can be described in detail as follows:

[0072] First, the system receives the tour guide's audio information in real time through audio capture devices. These devices can be highly sensitive microphones to ensure clear capture of the guide's explanations. For example, the audio capture devices can use voiceprint comparison technology to distinguish the guide's voice from that of the tourists, thereby determining or identifying the guide's audio information. Since the guide is closer to the audio capture devices (for example, the microphone is typically mounted on the guide's body and moves with him), the system can also distinguish the guide's voice from the tourists' voice by volume, thereby determining or identifying the guide's audio information.

[0073] The system then analyzes the received audio using a pre-set speech model. This model, likely a deep learning-based neural network trained on a large amount of speech data, converts the audio into text and identifies key words, particularly the pre-switch and execute-switch cues.

[0074] When the system recognizes the pre-switching cue, it queries a pre-set database. This database stores the mapping between pre-switching cue words and execution cue words, as well as the mapping between execution cue words and specific lighting effects. This query process allows the system to determine the next possible lighting effect, but it doesn't immediately execute the switch.

[0075] When the system subsequently recognizes the execution switch prompt, it will query the database again to confirm whether the execution switch prompt corresponds to the previous preparation switch prompt. If a match is found, the system will switch the wall corridor lights to the predetermined display effect according to the corresponding relationship stored in the database.

[0076] Specifically, the preparatory switching prompt word can correspond to multiple execution switching prompt words. For example, the preparatory switching prompt word is the Warring States Period, and the corresponding execution switching prompt words include Shang Yang's Reforms, Hundred Schools of Thought, and Battle of Changping. Each execution switching prompt word corresponds to a lighting display effect. When the system recognizes "Warring States Period", if it subsequently recognizes "Shang Yang's Reforms", the light is controlled to switch to the corresponding display effect. If it first recognizes "Shang Yang's Reforms", then recognizes "Hundred Schools of Thought", and finally recognizes "Battle of Changping", and no other preparatory switching prompt words are recognized during this period, the light is controlled to switch to various display effects in sequence during this period.

[0077] This dual mechanism is designed to improve system accuracy and reliability. By pre-setting the switch cue, the system can prepare in advance, reducing response delays. By executing the switch cue, the system avoids false triggering caused by the tour guide accidentally mentioning a word, ensuring that the switch is executed only when the tour guide intends to.

[0078] The actual switching of lights is achieved by controlling the intelligent lighting devices installed on the wall corridor. These devices may be LED light groups with adjustable brightness and color, which can quickly switch to different display effects according to the system's instructions.

[0079] Throughout the entire process, the various system components work closely together: the audio capture device continuously inputs audio information, the speech model analyzes and identifies keywords in real time, the database provides the necessary correspondence information, the control module issues instructions based on the analysis results and database information, and finally, the intelligent lighting device executes the lighting switching. This coordinated operation ensures that the lighting changes precisely match the rhythm and content of the guide's explanation.

[0080] As a preferred embodiment, the present application can be applied to a wall gallery lighting control system of a historical museum. Specific examples are as follows:

[0081] A 50-meter-long corridor in the museum features 100 adjustable LED light strips, each 0.5 meters long and individually controllable in brightness and color. Ten high-sensitivity microphones are evenly distributed on both sides of the corridor to capture audio information from the tour guides.

[0082] The system uses a deep learning-based speech recognition model, which has been specifically trained to recognize preset pre-switching and execution cues with over 95% accuracy. A preset database stores 50 pairs of pre-switching and execution cues, as well as 100 different lighting effects.

[0083] For example, when the tour guide says "The bonfire party will begin next," the system recognizes "bonfire party" as a preparatory switching prompt. The system queries the database and determines that the next possible display effect is "flashing red," but the light will not be switched immediately.

[0084] Then, when the tour guide said "fireworks show," the system recognized this as the corresponding action switch prompt for "bonfire party." At this point, the system instructed all LED light strips to switch to red and flash at a frequency of 2 times per second, creating a joyful atmosphere.

[0085] In this way, the lighting effects can be precisely matched to the content and rhythm of the guide's explanation, providing visitors with a more immersive experience. Furthermore, by employing a dual mechanism of pre-switching and execution switching, the system effectively avoids false triggering caused by the guide's accidental mention of certain words, improving control accuracy and reliability.

[0086] In some embodiments, the specific steps in step S2 include:

[0087] S21 preprocesses the audio information;

[0088] S22. Converting the preprocessed audio information into text;

[0089] S23. Perform semantic interpretation on the text and mark all preparatory switching prompt words and execution switching prompt words.

[0090] The present application further proposes a technical solution for preprocessing audio information, converting the preprocessed audio information into text, semantically interpreting the text and marking all preparatory switching prompt words and execution switching prompt words.

[0091] The technical solution of this application achieves accurate recognition of keywords in audio information by converting audio information into text and performing semantic interpretation and keyword annotation on the text. This method effectively solves the problems of audio information analysis and keyword identification, providing an accurate triggering basis for subsequent lighting control. The core innovation of this solution lies in the combination of speech recognition technology and semantic analysis technology, achieving precise conversion from audio to keywords, improving the system's intelligence and response accuracy.

[0092] First, audio information is preprocessed to improve the accuracy of subsequent analysis. Preprocessing can include various methods, such as denoising, framing, and normalization. Denoising can be achieved through frequency-domain filtering or time-domain filtering. Framing divides continuous audio information into shorter time segments for easier processing. Normalization adjusts the amplitude of the audio information to a uniform range.

[0093] Secondly, converting preprocessed audio information into text is the foundation for semantic analysis. This step can be achieved through speech recognition technology, with common methods including hidden Markov models (HMMs) and deep neural networks (DNNs). Speech recognition systems typically include acoustic models and language models. The acoustic model maps audio features to phonemes, while the language model converts phoneme sequences into the most likely text sequence.

[0094] Finally, semantically interpreting text and tagging keywords is a core step in keyword recognition. This step can utilize natural language processing techniques, such as part-of-speech tagging and named entity recognition. For identifying pre-switch and execution cues, either rule-based or machine learning approaches can be used. Rule-based approaches use predefined dictionaries and grammatical rules to identify keywords, while machine learning approaches learn recognition patterns from training data.

[0095] These three steps work together to form a complete processing pipeline. Preprocessing provides high-quality input for subsequent analysis, text conversion lays the foundation for semantic analysis, and semantic interpretation and keyword tagging directly enable keyword identification. This process design effectively extracts the required key information from raw audio.

[0096] The technical solution of this application achieves accurate recognition of keywords in audio information by converting audio information into text and performing semantic interpretation and keyword annotation on the text. This method can effectively solve the problems of audio information analysis and keyword identification, providing an accurate trigger basis for subsequent lighting control.

[0097] Specifically, the preprocessing step improves the quality of the audio information, reduces noise and interference, and provides better input for subsequent speech recognition. The text conversion step converts the audio information into a processable text form, enabling the system to apply text analysis techniques. The semantic interpretation and keyword tagging steps directly enable the recognition of pre-switch cues and execution cues.

[0098] This process design not only improves the accuracy of keyword recognition but also enhances the robustness of the system. For example, even in environments with a certain amount of background noise, the system can still effectively identify keywords through the combination of preprocessing and speech recognition. Furthermore, the introduction of the semantic interpretation step enables the system to understand the context, thereby more accurately identifying the true keywords and avoiding the potential misjudgment caused by purely keyword matching.

[0099] As a preferred embodiment, the preprocessing step may include the following specific operations: First, a high-pass filter is used to remove low-frequency noise from the audio information. The filter cutoff frequency can be set to 100 Hz. Then, the audio information is segmented into 20ms short time frames, and a Hamming window function is applied to each short time frame to reduce spectral leakage. Next, Mel-Frequency Cepstral Coefficient (MFCC) features are extracted for each short time frame, typically 13-dimensional MFCC features.

[0100] For the text conversion step, you can use deep learning-based end-to-end speech recognition models, such as the Transformer or Conformer models. These models can directly map audio feature sequences to text sequences without requiring explicit acoustic and language models. The model input is the MFCC feature sequence extracted in the previous step, and the output is the corresponding text sequence.

[0101] For semantic interpretation and keyword tagging, a pre-trained language model such as BERT can be fine-tuned. First, a part-of-speech tagging tool is used to preliminarily process the text. Then, a fine-tuned BERT model is used to perform semantic understanding of the text. Finally, a linear classification layer is used to annotate each word to determine whether it is a pre-switching prompt word or an execution prompt word.

[0102] Through this implementation, the technical solution of the present application can effectively process various complex audio inputs, accurately identify keywords, and provide a reliable trigger basis for subsequent lighting control.

[0103] Compared with existing technologies, the technical solution of this application has significant advantages. Traditional audio analysis methods generally rely on simple keyword matching or fixed voice commands, which are difficult to adapt to complex speech environments and diverse expressions. However, this application introduces a complete process of preprocessing, speech recognition, and semantic analysis, greatly improving the adaptability and accuracy of the system.

[0104] For example, in a museum tour scenario, traditional methods may only be able to identify preset fixed phrases as trigger words, but the method of this application can understand the guide's natural language expression. Even if the guide uses synonyms or different expressions, the system can accurately identify key information. This not only increases the system's flexibility, but also enhances the user experience.

[0105] Furthermore, the method of this application can better handle homophones or polysemy through semantic understanding. For example, when introducing historical figures, the system can correctly distinguish between "general" (as a name) and "general" (as a verb) based on the context, thus avoiding incorrect light triggering.

[0106] In general, the technical solution of this application achieves efficient and accurate analysis of audio information by combining a variety of advanced speech processing and natural language processing technologies, provides reliable technical support for intelligent lighting control systems, and effectively solves the problems existing in the existing technology.

[0107] In some embodiments, the specific steps in step S21 include:

[0108] S211. Remove background noise from audio information;

[0109] S212. Dividing the audio information after removing background noise into short time frames;

[0110] S213. After adding the window function to the short-time frame, extract the feature information of each short-time frame to convert the audio information into a feature vector; the feature vector is used to represent the time-frequency characteristics of the audio information; the feature information includes Mel-frequency cepstral coefficients and linear predictive coding.

[0111] This application effectively addresses the technical challenges of audio preprocessing through a series of audio preprocessing steps, including background noise removal, short-time frame segmentation, windowing, and feature extraction. These preprocessing steps improve the quality of the audio and convert it into a feature vector form that is easy to analyze and process, laying the foundation for subsequent speech recognition and semantic analysis. This preprocessing improves the system's accuracy in identifying keywords in the audio, thereby enabling better intelligent control of the corridor lighting.

[0112] The audio information preprocessing solution of this application includes multiple key steps, each of which has its specific function and implementation method.

[0113] First, removing background noise from audio is an important step in improving audio quality. This can be achieved through a variety of methods, such as frequency-domain filtering, adaptive noise cancellation, or deep learning-based noise suppression algorithms. Specifically, frequency-domain filtering can filter out noise in specific frequency bands by setting frequency thresholds; adaptive noise cancellation can dynamically adjust filtering parameters based on the characteristics of the ambient noise; and deep learning methods can identify and remove complex background noise through trained models.

[0114] Secondly, the denoised audio information is divided into short time frames and windowed for time-domain analysis. The short time frame length is typically chosen between 10 and 30 milliseconds because the audio information can be considered quasi-stationary within this time range. The choice of window function is also important; commonly used window functions include the Hamming window and the Hanning window. The window function reduces spectral leakage and improves the accuracy of spectral analysis.

[0115] Finally, extracting feature information and converting it into feature vectors is the core step in audio preprocessing. This application uses Mel-Frequency Cepstral Coefficients (MFCCs) and Linear Predictive Coding (LPC) as feature information. MFCCs effectively simulate the human auditory perception, while LPCs effectively represent the spectral envelope of speech. The combination of these two features comprehensively describes the time-frequency characteristics of audio information.

[0116] These preprocessing steps are closely intertwined and interactive. Denoising provides high-quality input signals for subsequent short-term frame segmentation and feature extraction. Short-term frame segmentation and windowing create suitable analysis units for feature extraction. Feature extraction, in turn, converts audio information into numerical form that can be directly processed by machine learning algorithms.

[0117] The preprocessing scheme of this application, combined with the aforementioned speech model analysis steps, can significantly improve the system's accuracy in recognizing keywords in audio information. The high-quality preprocessing output provides clearer and more effective input to the speech model, thereby improving the accuracy and stability of subsequent analysis. This improvement directly impacts the system's recognition of pre-switching and execution cues, thereby increasing the responsiveness and accuracy of the entire corridor lighting control system.

[0118] In practical applications, the audio information preprocessing solution of this application can be implemented according to the following steps:

[0119] 1. Noise Removal: An adaptive filter is used to process the input audio information. The filter parameters can be dynamically adjusted based on the characteristics of the ambient noise. For example, a minimum mean square error (LMS) algorithm can be used to update the filter coefficients to minimize the impact of background noise.

[0120] 2. Short-frame division: The denoised audio information is divided into 25ms short-frames, with a 10ms overlap between adjacent frames. This setting ensures sufficient analysis of the audio information while also taking into account computational efficiency.

[0121] 3. Window Function Application: Apply a Hamming window function to each short-time frame. The mathematical expression for the Hamming window is: w(n) = 0.54 - 0.46 * cos(2πn / (N-1)), where w(n) represents the value of the Hamming window at the nth sampling point, n represents the nth sampling point, and N is the window length. The Hamming window can effectively reduce spectral leakage and improve the accuracy of spectrum analysis.

[0122] 4. Feature extraction:

[0123] 41. MFCC Extraction: Perform a Fast Fourier Transform (FFT) on each windowed short-time frame, and then map the spectrum to the Mel-frequency scale. Typically, 13-dimensional MFCC features are extracted.

[0124] 42. LPC extraction: Use the Levinson-Durbin recursive algorithm to calculate the LPC coefficients. Usually, the 10-12 order LPC coefficients are selected.

[0125] 5. Feature vector construction: Combine MFCC and LPC features into a feature vector. For example, a 23-dimensional feature vector can be constructed, which contains 13-dimensional MFCC and 10-dimensional LPC features.

[0126] Through this detailed preprocessing scheme, the present application can effectively convert raw audio information into high-quality feature vectors, providing reliable input for subsequent speech recognition and semantic analysis. This preprocessing method not only improves the system's accuracy in keyword recognition, but also enhances the system's robustness in different environments. For example, in noisy environments, the noise removal step can significantly improve the signal-to-noise ratio, while the combination of MFCC and LPC features can maintain good recognition performance under different acoustic conditions.

[0127] Compared with the existing technology, the audio information preprocessing solution of this application has the following advantages:

[0128] 1. More comprehensive feature extraction: By combining MFCC and LPC features, this application can more comprehensively describe the time-frequency characteristics of audio information. Compared with methods that only use a single feature, this combination can provide richer information, which is conducive to improving the accuracy of subsequent recognition.

[0129] 2. Adaptive noise removal: The adaptive filtering method used in this application can dynamically adjust parameters according to the characteristics of the environmental noise. Compared with the filtering method with fixed parameters, it can better adapt to different noise environments.

[0130] 3. Optimized short-time frame division: The 25ms frame length and 10ms frame shift settings adopted in this application not only ensure analysis accuracy but also take into account computational efficiency, which is very important for real-time processing of audio information.

[0131] 4. Efficient feature vector construction: By reasonably selecting the dimensions of MFCC and LPC, the feature vector constructed in this application contains sufficient information while avoiding the computational burden caused by excessively high dimensions.

[0132] These improvements enable the audio information preprocessing solution of this application to better support the real-time and accuracy requirements of the wall corridor lighting control system, and provide strong technical support for the realization of intelligent and personalized lighting control.

[0133] In some embodiments, the specific steps in step S3 include:

[0134] S3A1. When the audio information appears to prepare the switching prompt word, based on a preset database, the display of the light is determined by preparing the switching prompt word and the wall gallery lighting control system enters a ready state; in the ready state, the wall gallery lighting control system starts the timer and counts down according to the preset duration;

[0135] The specific steps in step S4 include:

[0136] S41. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, if the execution switching prompt word appears before the countdown ends, the light is switched to the corresponding display effect according to the execution switching prompt word, otherwise the control system exits the preparatory state and returns to execute step S1.

[0137] The technical solution of the present application effectively solves the problem of the lighting switching effect being out of sync with the tour guide's explanation by introducing a dual mechanism of preparatory switching prompt words and execution switching prompt words, combined with the preparatory state and countdown functions. The system enters the preparatory state when it recognizes the preparatory switching prompt words, and waits for the execution switching prompt words to appear within the specified time. This design not only ensures the timeliness of the lighting switch, but also provides a certain degree of flexibility for the tour guide's explanation rhythm. If the execution switching prompt words do not appear within the preset time, the system will exit the preparatory state, avoiding incorrect lighting switching. This method can effectively improve the accuracy and adaptability of lighting control and enhance the immersive experience of tourists.

[0138] The technical solution of this application involves multiple key features, including pre-switching prompt words, execution switching prompt words, preset database, pre-switching state, timer and countdown mechanism. The relationship and interaction between these features constitute a complete lighting control system.

[0139] Preliminary and execution transition cues serve as triggers for the system to identify key moments in a guide's presentation. Preliminary transition cues can be used to signal the introduction of new content, such as "Next, we'll see" or "Let's move on to the next exhibition area." Execution transition cues can be used to signal the start of specific content, such as "This painting depicts" or "This artifact originated from."

[0140] The preset database stores the mapping between pre-switching prompts and execution prompts, as well as the mapping between execution prompts and lighting effects. For example, the database may include the following mapping: - pre-switching prompt "Next we will see" corresponds to execution prompt "This painting depicts" - execution prompt "This painting depicts" corresponds to lighting effect "warm yellow spotlight."

[0141] The "Ready" state is an intermediate state of the system, triggered by the recognition of the "Ready" transition cue. In this state, the system starts a timer and begins a countdown. The preset countdown duration can be adjusted based on actual conditions, for example, to 10 or 15 seconds. This time window provides a buffer for the guide's presentation rhythm.

[0142] The timer and countdown mechanism are the core control logic of this solution. When the system enters the standby state, the timer begins. If the switch prompt is recognized before the countdown ends, the system will immediately switch the lighting effect. If the switch prompt is not recognized before the countdown ends, the system will exit the standby state to avoid incorrect lighting switching.

[0143] The synergy between these features creates a flexible and accurate lighting control system. The introduction of pre-switching cues enables the system to prepare in advance, while the recognition of execution cues ensures the accuracy of lighting transitions. The design of the pre-switching state and countdown mechanism provides the necessary flexibility to accommodate even subtle changes in the tour guide's pace.

[0144] In practical application, the technical solution of this application can be operated as follows:

[0145] 1. The system continuously receives and analyzes the tour guide’s audio information.

[0146] 2. When the system recognizes the preparatory switching prompt word "Next we will see", it will query the preset database to determine the possible execution switching prompt words and corresponding lighting display effects.

[0147] 3. The system enters the ready state, starts the timer, and begins a 15-second countdown.

[0148] 4. During the countdown, the system continues to analyze the audio information. If it recognizes the execution switch prompt "This painting depicts" at 10 seconds, the system immediately switches the lighting to the preset "warm yellow spotlight" effect.

[0149] 5. If the execution switch prompt word is not recognized after the 15-second countdown, the system exits the standby state and continues to monitor audio information, waiting for the next standby switch prompt word.

[0150] This design allows lighting switching to better adapt to the actual rhythm of the guide's explanation. Even if the guide pauses briefly when introducing new content or inserts additional explanation, the system can complete the lighting switch within the appropriate time window, avoiding the problem of the lighting effects being out of sync with the explanation content.

[0151] The technical solution of the present application has significant advantages over the existing technology. The traditional static control method cannot dynamically adjust the lighting effects according to the content of the tour guide's explanation, and although the semi-automatic dynamic control can achieve lighting changes, it is often difficult to accurately match the rhythm of the tour guide's explanation. The present application introduces a dual recognition mechanism of preparatory switching prompt words and execution switching prompt words, combined with the preparatory state and countdown functions, to achieve precise synchronization of lighting effects with the tour guide's explanation. This method not only improves the accuracy of lighting control, but also provides a certain degree of flexibility for the tour guide's explanation, thereby significantly enhancing the tourists' immersive experience.

[0152] In some embodiments, the specific steps in step S3 further include:

[0153] S3B1 after determining the guide position by monitoring, obtain the text information corresponding to the guide position on the wall gallery; text information is pre-arranged on the wall gallery and is recorded in the database, the text information includes the preparation of the switch prompt word and the execution of the switch prompt word;

[0154] S3B2 based on text information from the database to filter out the correspondence between the preparatory switching prompt words and the execution switching prompt words and the execution switching prompt words and the corresponding relationship between the display effect and extract as the target data;

[0155] S3B3. When a preparatory switching prompt word appears in the audio information, the display effect of the light is determined based on the target data through the preparatory switching prompt word.

[0156] In museums, cultural centers, scenic spots, and other places, wall corridors are often decorated with graphic information to showcase history alongside tour guides' explanations. Traditional wall corridor lighting control methods include static control and semi-automatic dynamic control. Static control struggles to provide an immersive experience, while semi-automatic dynamic control struggles to match the pace of the guide's explanations, hindering the creation of a suitable atmosphere.

[0157] To address the slow dynamic response of lighting control systems, this application proposes an improved wall gallery lighting control method. This method first determines the guide's location through monitoring, then retrieves textual information corresponding to the guide's location on the wall gallery. This textual information, pre-placed on the wall gallery and recorded in a database, includes both pre-switching prompts and execution prompts.

[0158] Based on the acquired text, the system filters the database to identify the correspondence between pre-switching prompts and execution prompts, as well as the correspondence between execution prompts and display effects, and extracts this information as target data. When pre-switching prompts appear in audio, the system uses these target data to determine the lighting effect using the pre-switching prompts.

[0159] The core of this approach is to predict the likely content of the tour guide's commentary based on their location information, allowing them to pre-plan the corresponding lighting effects. Specifically, the system can monitor the guide's location using various methods, such as positioning devices, camera tracking, or GPS information from the guide's handheld device. Textual information on the wall can be pre-placed in the form of QR codes, RFID tags, or other electronic identifiers, allowing the system to quickly read and identify it.

[0160] The information stored in the database can include multiple levels of correspondence. For example, the correspondence between the guide's location and the wall text, the correspondence between the preparatory switching prompts in the text and the execution switching prompts, and the correspondence between the execution switching prompts and specific lighting display effects. This multi-level correspondence enables the system to more accurately predict and prepare lighting effects.

[0161] In practice, when the system detects a tour guide entering a specific area, it immediately retrieves the textual information displayed on the walls of that area. For example, if the tour guide enters an area showcasing ancient civilizations, the system will retrieve this textual information, which might include "Ancient Civilizations" as a preparatory transition prompt and "Stone Age" as an execution prompt. The system then extracts the lighting effects corresponding to these phrases from a database, such as adjusting the lighting to a stone-brown color to create a mysterious atmosphere.

[0162] When the guide's audio message mentions the preparatory switch prompt "I'm about to talk about modern civilization," the system has already prepared the corresponding lighting effects. This way, when the guide actually says the execution switch prompt "Industrial Revolution," the system can immediately switch to the preset lighting effects, achieving a quick response.

[0163] Through this prediction and preparation mechanism, this application significantly improves the responsiveness of the lighting control system. Compared to traditional methods, this technical solution can better align with the tour guide's narration, providing a more synchronized and immersive experience. Furthermore, because the system only needs to process data related to the current location, rather than the entire database, it also reduces the amount of data processing, further improving responsiveness.

[0164] As a preferred implementation, this application can be implemented in a museum's "Ancient Civilization" exhibition area. The wall corridors in this area depict the development of historical civilizations from ancient times to modern times. The system pre-stores text information, prompts, and lighting effects related to each period.

[0165] For example, when a tour guide enters the "Ancient Egyptian Civilization" area, the system retrieves textual information about the area, including the pre-transition prompt "Introduction to the Pyramids" and the execution prompt "Pharaoh's Tombs." The system then extracts relevant information from the database and prepares to adjust the lighting to a golden color, simulating the pyramids under the desert sun.

[0166] When the guide mentions "We're about to introduce the pyramids" during his explanation, the system enters a standby state. Then, when the guide mentions "The Pharaoh's Tomb," the lighting immediately switches to a preset golden color, creating an ancient Egyptian atmosphere. This rapid response not only enhances the visitor's sense of immersion but also makes the guide's explanation more engaging.

[0167] Compared to traditional lighting control methods, the technical solution of this application offers significant advantages. Traditional methods may require manual operation or preset fixed change patterns, making it difficult to adapt to the tour guide's explanation rhythm in real time. However, this application achieves precise synchronization of lighting effects and tour guide explanations through a prediction and preparation mechanism, significantly improving the overall effect of the exhibition and the visitor experience.

[0168] Furthermore, the method in this application is highly adaptable and scalable. By updating the database's correspondence between text information and lighting effects, the system can easily adapt to exhibitions with different themes or newly added content without requiring significant hardware modifications. This flexibility allows museums to update exhibition content more frequently, increasing their appeal and repeat visitor rates.

[0169] In some embodiments, the specific steps of switching the light to a corresponding display effect according to the execution switching prompt include:

[0170] S411. Consider the tour guide and the tourists she leads as a team, and select the lighting fixtures on the wall gallery that correspond to the team's position and length as target fixtures to ensure that the light emitted by the target fixtures can be seen by all tourists in the team;

[0171] S412. Keep the operating status of other lighting devices on the wall corridor unchanged except for the target device. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, only the light of the target device is switched to the corresponding display effect according to the execution switching prompt word.

[0172] The technical solution proposed in this application achieves precise positioning of lighting effects by treating the tour guide and tourists as a whole and selecting target lighting devices based on the group's position and length. Furthermore, by switching only the lighting of the target device, while keeping the status of other devices unchanged, unnecessary interference is avoided, energy consumption is reduced, and the accuracy of lighting control is improved. This method ensures that the lighting effects are synchronized with the tour guide's explanation, enhancing the tourists' immersive experience and effectively solving the technical problem of accurately controlling light switching in the wall corridor lighting control.

[0173] Specifically, the technical solution of this application includes the following key features:

[0174] Treating the guide and tourists as a team: This feature can be implemented in many ways, such as using cameras or sensors to detect the position and length of the guide and tourists.

[0175] Select the lighting fixtures that correspond to the position and length of the team as target fixtures: This step can be achieved using a pre-set algorithm that calculates the most suitable lighting fixture combination based on the position and length of the team. For example, a coverage range can be set to ensure that the selected lighting fixtures can illuminate the entire area where the team is located.

[0176] Keep other lighting devices in their operating state unchanged: This feature can be achieved through a control system that can individually control the switching and brightness of each lighting device.

[0177] Only switch the lighting of the target device to the corresponding display effect: This step can be achieved through the preset lighting effect library. Select the corresponding lighting effect according to the execution switch prompt and apply it only to the target device.

[0178] These features are closely related and interactive. By treating tour guides and tourists as a whole, the system can more accurately determine the areas that need lighting. The process of selecting the target device is directly dependent on the position and length information of the team, ensuring the precise positioning of the lighting effects. The two features of keeping the status of other devices unchanged and switching only the lights of the target device work together to ensure the lighting effects of the target area while avoiding interference with other areas. It is particularly suitable for application scenarios where multiple different teams visit the same corridor one after another. Each team is independently provided with corresponding lighting effects based on the commentary content of their respective guides, rather than controlling all lights in the entire corridor to make the same changes, so that tourists from each team can have an undisturbed immersive experience; or when there is only one team in the corridor, only the lighting equipment at the corresponding position of the team is controlled to produce lighting effects, while the lighting equipment at other positions in the corridor remains off, so as to save energy.

[0179] This approach not only solves the problem of precise control over lighting switching but also offers additional benefits. For example, by controlling only essential lighting, energy consumption can be significantly reduced. Furthermore, this precise control can minimize disruption to other visitors, improving the overall visitor experience.

[0180] In practical applications, the technical solution of this application can be implemented as follows:

[0181] First, the system receives real-time audio information from the tour guide. Using a pre-set voice model, it analyzes the audio information to identify key words, including pre-switching and execution cues. When a pre-switching cues appear in the audio information, the system uses a pre-set database to determine the lighting effect.

[0182] Next, the system uses monitoring equipment to determine the location and length of the tour guide and tourist group. For example, let's say the group is 10 meters long and located between 20 and 30 meters along the wall corridor. The system then selects the lighting fixtures within this area as target devices, such as the LED light strips numbered L20 to L30.

[0183] When the audio prompt appears, the system will switch only the LED strips L20 through L30 to the corresponding display effect. For example, if the prompt corresponds to "Warm Yellow," the system will adjust the LED strips L20 through L30 to a warm yellow light with a color temperature of 3000K and 50% brightness. Meanwhile, the lighting in other areas of the corridor (such as L1 through L19 and L31 through L50) remains unchanged.

[0184] This approach ensures that lighting effects precisely follow the guide's explanations, providing the best viewing experience for all visitors in the group. Furthermore, since only a portion of the lighting fixtures are altered, energy is saved and disruption to visitors in other areas is avoided.

[0185] Compared with the existing technology, the technical solution of the present application has significant advantages. Traditional static control methods cannot dynamically adjust the lighting according to the content of the tour guide's explanation, and although semi-automatic dynamic control can change the lighting, it is often difficult to synchronize with the rhythm of the tour guide's explanation. The method of the present application achieves a perfect coordination between the lighting effects and the content of the tour guide's explanation through precise positioning and control, greatly enhancing the immersive experience of tourists. In addition, the method of the present application can also effectively reduce energy consumption and reduce interference with other tourists, which are difficult to achieve with existing technologies.

[0186] Through this precise lighting control method, the present application effectively solves the technical problem of precise control of lighting switching in wall corridor lighting control, and provides a more intelligent and efficient display method for museums, cultural centers, scenic spots and other places.

[0187] Please refer to Figure 2 , Figure 2 In some embodiments of the present invention, a wall gallery lighting control device is applied to a wall gallery lighting control system. The wall gallery lighting control device is integrated into a back-end control device in the form of a computer program, and includes:

[0188] Receiving module 100, for receiving audio information sent by the tour guide in real time;

[0189] An analysis module 200 is configured to analyze audio information using a preset voice model to determine keyword information in the audio information, wherein the keyword information includes a preparatory switching prompt word and an execution switching prompt word;

[0190] The preparation module 300 is configured to determine a lighting display effect based on a preset database when a preparatory switching prompt word appears in the audio information, using the preparatory switching prompt word; the preparatory switching prompt word corresponds to at least one execution switching prompt word, and the corresponding relationship is pre-stored in the database; each execution switching prompt word corresponds to a display effect, and the corresponding relationship is pre-stored in the database;

[0191] The switching module 400 is configured to switch the light to a corresponding display effect according to the execution switching prompt word after the preparatory switching prompt word appears in the audio information and when the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information.

[0192] In some embodiments, when the analysis module 200 is used to analyze audio information using a preset speech model to determine keyword information in the audio information, the following steps are performed:

[0193] S21 preprocesses the audio information;

[0194] S22. Converting the preprocessed audio information into text;

[0195] S23. Perform semantic interpretation on the text and mark all preparatory switching prompt words and execution switching prompt words.

[0196] In some embodiments, when the analysis module 200 is used to pre-process the audio information, it performs:

[0197] S211. Remove background noise from audio information;

[0198] S212. Dividing the audio information after removing background noise into short time frames;

[0199] S213. After adding the window function to the short-time frame, extract the feature information of each short-time frame to convert the audio information into a feature vector; the feature vector is used to represent the time-frequency characteristics of the audio information; the feature information includes Mel-frequency cepstral coefficients and linear predictive coding.

[0200] In some embodiments, when a preparatory switching prompt word appears in the audio information, the preparation module 300 is configured to determine the display effect of the light according to the preparatory switching prompt word based on a preset database and execute the following:

[0201] S3A1. When the audio information appears to prepare the switching prompt word, based on a preset database, the display of the light is determined by preparing the switching prompt word and the wall gallery lighting control system enters a ready state; in the ready state, the wall gallery lighting control system starts the timer and counts down according to the preset duration;

[0202] The switching module 400 is configured to execute the following steps when, after the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, the light is switched to the corresponding display effect according to the execution switching prompt word:

[0203] S41. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, if the execution switching prompt word appears before the countdown ends, the light is switched to the corresponding display effect according to the execution switching prompt word, otherwise the control system exits the preparatory state and returns to execute step S1.

[0204] In some embodiments, when the preparatory switching prompt word appears in the audio information, the preparatory module 300 further performs the following when determining the light display effect based on the preparatory switching prompt word based on a preset database:

[0205] S3B1 after determining the guide position by monitoring, obtain the text information corresponding to the guide position on the wall gallery; text information is pre-arranged on the wall gallery and is recorded in the database, the text information includes the preparation of the switch prompt word and the execution of the switch prompt word;

[0206] S3B2 based on text information from the database to filter out the correspondence between the preparatory switching prompt words and the execution switching prompt words and the execution switching prompt words and the corresponding relationship between the display effect and extract as the target data;

[0207] S3B3. When a preparatory switching prompt word appears in the audio information, the display effect of the light is determined based on the target data through the preparatory switching prompt word.

[0208] In some embodiments, the switching module 400 performs the following when switching the light to a corresponding display effect according to the execution switching prompt word:

[0209] S411. Consider the tour guide and the tourists she leads as a team, and select the lighting fixtures on the wall gallery that correspond to the team's position and length as target fixtures to ensure that the light emitted by the target fixtures can be seen by all tourists in the team;

[0210] S412. Keep the operating status of other lighting devices on the wall corridor unchanged except for the target device. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, only the light of the target device is switched to the corresponding display effect according to the execution switching prompt word.

[0211] Please refer to Figure 3 , Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present invention. The present invention provides an electronic device 13, including: a processor 1301 and a memory 1302. The processor 1301 and the memory 1302 are interconnected and communicate with each other via a communication bus 1303 and / or other forms of connection mechanisms (not shown). The memory 1302 stores computer-readable instructions executable by the processor 1301. When the electronic device is running, the processor 1301 executes the computer-readable instructions to execute the wall corridor lighting control method in any optional implementation of the above embodiment to achieve the following functions: receiving audio information sent by the tour guide in real time; and The speech model analyzes the audio information to determine the keyword information in the audio information, and the keyword information includes the preparatory switching prompt word and the execution switching prompt word; when the preparatory switching prompt word appears in the audio information, the display effect of the light is determined by the preparatory switching prompt word based on a preset database; the preparatory switching prompt word corresponds to at least one execution switching prompt word and the corresponding relationship is pre-stored in the database, and each execution switching prompt word corresponds to a display effect and the corresponding relationship is pre-stored in the database; after the preparatory switching prompt word appears in the audio information and when the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, the light is switched to the corresponding display effect according to the execution switching prompt word.

[0212] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the wall corridor lighting control method in any optional implementation of the above-mentioned embodiment is executed to achieve the following functions: receiving audio information sent by a tour guide in real time; analyzing the audio information through a preset voice model to determine keyword information in the audio information, the keyword information including a preparatory switching prompt word and an execution switching prompt word; when a preparatory switching prompt word appears in the audio information, determining a light display effect through the preparatory switching prompt word based on a preset database; the preparatory switching prompt word corresponds to at least one execution switching prompt word and the corresponding relationship is pre-stored in the database, each execution switching prompt word corresponds to a display effect and the corresponding relationship is pre-stored in the database; after the preparatory switching prompt word appears in the audio information and when the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, switching the light to the corresponding display effect according to the execution switching prompt word.

[0213] Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0214] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some communication interface, the indirect coupling or communication connection of the device or unit may be electrical, mechanical or other forms.

[0215] In addition, the units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0216] Furthermore, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0217] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any actual relationship or order between these entities or operations.

[0218] The foregoing description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A wall corridor lighting control method, applied to a wall corridor lighting control system, characterized in that: The following steps are involved: S1. Receive audio information sent by the tour guide in real time; S2. Analyzing the audio information by a preset voice model to determine keyword information in the audio information, the keyword information includes a preparatory switching prompt word and an execution switching prompt word; S3. When the preparatory switching prompt word appears in the audio information, the lighting display effect is determined based on the preparatory switching prompt word based on a preset database; the preparatory switching prompt word corresponds to at least one execution switching prompt word and the corresponding relationship is pre-stored in the database, and each execution switching prompt word corresponds to a display effect and the corresponding relationship is pre-stored in the database; S4. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, the light is switched to the corresponding display effect according to the execution switching prompt word; The specific steps in step S3 include the following steps S3A1 or steps S3B1-S3B3: S3A1. When the audio information appears to prepare the switching prompt word, based on a preset database, the display effect of the light is determined by the prepared switching prompt word and controls the wall gallery lighting control system to enter a ready state; In the standby state, the wall gallery lighting control system starts a timer and counts down according to a preset time length; S3B1 after determining the guide position by monitoring, obtain the text information corresponding to the guide position on the wall gallery; the text information is pre-arranged on the wall gallery and is recorded in the database, the text information includes the preparatory switch prompt word and the execution switch prompt word; S3B2 based on the text information from the database to filter out the text information in the preparation of the switch prompt word and the corresponding relationship between the execution switch prompt word and the corresponding relationship between the display effect and extract as the target data; S3B3 when the audio information appears to prepare the switch prompt word, based on the target data, the display effect of the light is determined by the prepared switch prompt word; The specific steps in step S4 include: S41. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, if the execution switching prompt word appears before the countdown ends, the lighting is switched to the corresponding display effect according to the execution switching prompt word; otherwise, the control system exits the preparatory state and returns to step S1; The specific steps for switching the light to the corresponding display effect according to the execution switching prompt include: S411. The guide and the tourists led by the guide are regarded as a team, and the lighting device corresponding to the team position and team length on the wall corridor is selected as the target device to ensure that the light emitted by the target device can be viewed by all tourists in the team; S412. Keep the operating status of other lighting devices on the wall corridor unchanged except for the target device. After the preparatory switching prompt word appears in the audio information and the execution switching prompt word corresponding to the preparatory switching prompt word appears in the audio information, only switch the light of the target device to the corresponding display effect according to the execution switching prompt word.

2. The wall corridor lighting control method according to claim 1, characterized in that: The specific steps in step S2 include: S21 preprocesses the audio information; S22. Converting the preprocessed audio information into text; S23. Perform semantic interpretation on the text and mark all the preparatory switching prompt words and the execution switching prompt words.

3. The wall corridor lighting control method according to claim 2, characterized in that: The specific steps in step S21 include: S211. Remove background noise from the audio information; S212. Dividing the audio information after removing background noise into short time frames; S213. After adding a window function to the short-time frame, extract the feature information of each short-time frame to convert the audio information into a feature vector; the feature vector is used to represent the time-frequency characteristics of the audio information; the feature information includes Mel-frequency cepstral coefficients and linear predictive coding.

4. An electronic device, characterized in that: The device comprises a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the wall corridor lighting control method according to any one of claims 1 to 3 are executed.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the wall corridor lighting control method according to any one of claims 1 to 3 are executed.

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