A light following sound based on data analysis and a control system thereof

Abstract

The application relates to the technical field of sound, and relates to a light follow-up sound based on data analysis and a control system thereof.The light follow-up sound comprises an audio signal processing module, which is used for filtering noise of audio data and extracting real-time audio signal strength; a volume regulation module connected with the audio signal processing module, which is used for regulating the volume size according to the real-time audio signal strength after noise filtering; and a frequency analysis module, which is used for analyzing the frequency characteristics of the audio data to determine corresponding light color parameters; the system adopts dynamic filtering and weighted algorithm to process audio, accurately extracts signal strength to regulate the volume, analyzes the frequency characteristics through delay compensation and adaptive threshold, realizes high synchronization of light and music in combination with multi-stage dimming, has environment interference correction and system self-checking, and improves the audio-visual experience of users.

Description

Technical Field

[0001] This application relates to the field of audio technology, and in particular to a light-following audio system based on data analysis and its control system. Background Technology

[0002] A data analysis-based lighting and sound control system is an intelligent system that combines audio signal processing and lighting control technology. It can achieve a high degree of synchronization between lighting effects and sound effects by analyzing audio data.

[0003] However, the system has some problems that need to be solved: First, due to the complex frequency characteristics of audio data, it is still a challenge to accurately analyze the music rhythm and control the light color to achieve a high degree of synchronization between dynamic light and shadow and music rhythm.

[0004] Secondly, noise interference in the on-site environment may affect the realism of the audio signal strength. Therefore, it is necessary to further optimize the noise filtering algorithm and dynamically adjust the volume based on the processed real-time audio signal strength to ensure the consistency and matching degree of sound effects and visual effects. These two issues directly affect the overall performance of the system and the user experience. Summary of the Invention

[0005] To address the problems mentioned in the background, this application provides a data analysis-based light-following sound system and its control system.

[0006] This application provides a data analysis-based lighting and sound system and its control system, employing the following technical solution: A data analysis-based lighting and sound control system, comprising:

[0007] The audio signal processing module is used to filter noise from audio data and extract real-time audio signal strength.

[0008] A volume control module, connected to the audio signal processing module, is used to adjust the volume based on the real-time audio signal strength after noise filtering.

[0009] The frequency analysis module is used to analyze the frequency characteristics of audio data in order to determine the corresponding light color parameters;

[0010] The lighting control module, connected to the frequency analysis module, is used to adjust the color display of the lights based on the light color parameters in order to achieve synchronization with the music rhythm;

[0011] The environmental sound interference assessment module is used to correct the signal-to-noise ratio in the main sound data by utilizing external environmental noise, thereby improving the system robustness.

[0012] Preferably, the step of filtering noise from the audio data and extracting the real-time audio signal strength further includes:

[0013] Use a low-pass filter to remove frequencies above the specified frequency from the raw audio data. Noise signals;

[0014] Set the threshold of the filtered audio data signal ,in It is a dynamically adjustable parameter, ranging from [0.2, 0.5]. The average signal strength;

[0015] When the real-time audio signal strength Meet the conditions If the data point is valid, it is retained as a valid signal; otherwise, it is considered an invalid signal, and the maximum value MaxSig of the data strength of the filtered valid signal is taken for subsequent volume control calculation.

[0016] Preferably, the step of adjusting the volume based on the real-time audio signal strength after noise filtering further includes:

[0017] Signal strength is extracted through noise filtering. Set the initial volume ,in This is a scaling factor that controls the loudness ratio of the sound. ;

[0018] when Exceeding the maximum adjustable volume limit Then according to Limit the output; otherwise, leave the original value unchanged.

[0019] Output volume for each frame of data The weighted moving average algorithm is applied for smoothing adjustment, and the calculation method is as follows:

[0020] ,in The value of the previous frame. This is the weighting factor, with a default value of 0.7;

[0021] Output of the weighted moving average algorithm Perform graded mapping: Define Volume levels and ;

[0022] set up This represents the step increment for each level; if the current weighted volume... , corresponding to the Set the volume level; otherwise, trigger the exception handling mechanism and set the volume to the default middle level.

[0023] Preferably, the method by which the frequency analysis module analyzes the frequency characteristics of the audio data to determine the corresponding light color parameters includes:

[0024] The noise-filtered audio data is decomposed into multiple sub-frequency bands. , And calculate the spectral energy for each sub-band. ,in The amplitude spectrum;

[0025] Calculate total power and set a threshold Active sub-bands are selected based on this threshold.

[0026] in The expression determines the correlation between the color change rate and the spectral distribution. The parameters are adaptive weights; if they exceed... If so, then mark this part as the dominant color gamut;

[0027] Add a delay compensation factor to the criteria for determining active frequency bands. ,in It is the sampling rate differential. The parameter representing the difference in delay window length is used to improve synchronization issues.

[0028] That is, whenever a frequency band is detected to exceed the threshold, the influence weight of this delay is increased. Bit.

[0029] Preferably, the lighting control module calculates the lighting color mapping relationship of the active dominant color gamut based on the sub-frequency band as follows:

[0030] against Color mapping establishment function for dominant region , representing color coordinates Relationship matrix between active states of sub-bands For color table functions, and These are all system optimization configurations;

[0031] Among them when When this happens, it enters high brightness enhancement display mode;

[0032] Simultaneously define color switching smoothing rules This ensures a smooth color transition.

[0033] Preferably, the lighting control module introduces a multi-level dynamic dimming mode when adjusting the light color, that is, when the number of detected main frequency regions K > ThresholdFreqBand, the advanced color mixing mode is activated. Here, the threshold adjustment factor controls the logic for increasing or decreasing global light intensity.

[0034] Preferably, the environmental sound interference assessment module utilizes external environmental noise. To correct the signal-to-noise ratio in the main audio data This indirectly affects the accuracy of the linkage between music and lighting, and the correction item This represents the deviation correction range.

[0035] Preferably, the system provides a method for dynamically updating the frequency feature library to adapt to the needs of more complex music genres, and employs a periodic learning method to adjust the formula. ,in Error correction values ​​are derived from historical data. It is a weighted historical spectrum contribution, ensuring that the synchronization between lights and different types of music continues to improve.

[0036] Preferably, the system adds special light display logic for extreme high-frequency burst sounds, defining a sudden change threshold. If the detection result exceeds this mutation amount at a certain moment, a short flashing light warning sequence will be immediately triggered, enhancing the visual impact of the on-site experience while solving the technical pain point of audio-visual asynchrony.

[0037] Preferably, a light-following sound system based on data analysis is provided with a system self-test and optimization module, which periodically performs functional checks and performance evaluations on the audio signal processing module, volume control module, frequency analysis module, light control module, and environmental sound effect interference evaluation module.

[0038] For the audio signal processing module, check whether the parameter settings of the low-pass filter are within a reasonable range, verify the noise filtering effect and the accuracy of real-time audio signal strength extraction. If the deviation is found to exceed the preset threshold, automatically adjust the filter parameters or recalibrate the signal extraction algorithm.

[0039] For the volume control module, evaluate the smoothness and accuracy of volume control, check whether the calculation results of the weighted moving average algorithm meet expectations, and adjust the weighting coefficient λ or scaling coefficient γ if there are sudden volume changes or mismatch with audio signal strength.

[0040] For the frequency analysis module, check the stability of sub-band decomposition and the accuracy of spectral energy calculation. If the dominant color gamut selection is found to be inaccurate or the color change rate is abnormal, readjust the adaptive weight t or the threshold ThColor.

[0041] For the lighting control module, check the execution of the color mapping function and the color switching smoothing rule. If abnormal color display or unstable transition occurs, adjust the system optimization configuration parameters αC, β or smoothing coefficient μ.

[0042] For the environmental sound interference assessment module, check the accuracy of the signal-to-noise ratio calculation and the effectiveness of the correction items. If it is found that the accuracy of the music and lighting linkage does not meet expectations, reassess the impact of external environmental noise and adjust the relevant parameters of the deviation correction amplitude.

[0043] Meanwhile, this module records the results of each inspection and optimization, forming a system operation log, which provides data support for subsequent in-depth optimization and troubleshooting.

[0044] In summary, this application includes at least one of the following beneficial technical effects:

[0045] This disclosed embodiment of a data-driven lighting and sound control system effectively overcomes existing technical challenges through multi-module collaborative design and optimization algorithms. In the audio signal processing module, a dynamic threshold low-pass filtering algorithm is employed to accurately filter environmental noise interference, ensuring the reliability of the extracted real-time audio signal strength and providing an accurate basis for dynamic volume adjustment. The volume control module combines a weighted moving average algorithm with a graded mapping mechanism to achieve smooth volume adjustment and precise control, ensuring stable sound output. The frequency analysis module innovatively introduces a delay compensation factor and an adaptive weighted threshold screening mechanism to deeply analyze audio frequency characteristics and accurately determine lighting color parameters. The lighting control module, through a color mapping function and smooth switching rules, combined with multi-level dynamic dimming modes, achieves a high degree of synchronization between lighting color and music rhythm, enhancing visual appeal. Furthermore, the environmental sound interference assessment module corrects the signal-to-noise ratio in real time, and the system self-check and optimization module periodically maintains the performance of each module, further improving system robustness and adaptability, significantly enhancing the user's audiovisual experience, and providing users with an immersive audiovisual interactive experience. Attached Figure Description

[0046] Figure 1 This is a flowchart of the audio control system;

[0047] Figure 2 Example of a parameter;

[0048] Figure 3 These are experimental data. Detailed Implementation

[0049] The embodiments of this application are described in detail below, and examples of the embodiments are shown in the accompanying drawings.

[0050] In the description of this specification, the references to "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples" refer to specific features, structures, materials, or characteristics described in connection with the described embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0051] This application discloses a data analysis-based light-following sound system and its control system. Referring to the accompanying drawings, the following describes the implementation steps of the data analysis-based light-following sound control system of the present invention.

[0052] A data analysis-based light-and-sound control system includes: an audio signal processing module for filtering noise from audio data and extracting real-time audio signal intensity; a volume control module connected to the audio signal processing module for adjusting the volume based on the real-time audio signal intensity after noise filtering; a frequency analysis module for analyzing the frequency characteristics of the audio data to determine the corresponding light color parameters; a light control module connected to the frequency analysis module for adjusting the color display of the lights based on the light color parameters to achieve synchronization with the music rhythm; and an environmental sound interference assessment module for using external environmental noise to correct the signal-to-noise ratio in the main sound data and improve system robustness.

[0053] The basic components and core functions of this audio system are as follows: The audio signal processing module is the foundation of the entire system. It preprocesses the audio data, removes noise, and extracts key signal strength information. The volume control module dynamically adjusts the volume according to the processed signal strength to match the audio content. The frequency analysis module provides color parameters for lighting control by analyzing the audio frequency characteristics, enabling the linkage between lighting and music. The lighting control module controls the display of light colors based on these parameters to create an atmosphere that matches the rhythm of the music. The environmental sound interference assessment module considers the impact of the external environment on the audio system and improves the stability and reliability of the system in complex environments by correcting the signal-to-noise ratio.

[0054] Based on noise filtering of audio data and extraction of real-time audio signal strength, the method further includes: using a low-pass filter to eliminate frequencies higher than a certain value in the original audio data. Noise signals;

[0055] Set the threshold of the filtered audio data signal ,in It is a dynamically adjustable parameter, ranging from [0.2, 0.5]. The average signal strength;

[0056] When the real-time audio signal strength Meet the conditions If the data point is valid, it is retained as a valid signal; otherwise, it is considered an invalid signal, and the maximum value MaxSig of the data strength of the filtered valid signal is taken for subsequent volume control calculation.

[0057] The specific implementation method of the audio signal processing module is as follows: the use of a low-pass filter can effectively remove high-frequency noise and improve the quality of audio data. The introduction of the dynamically adjustable parameter α allows the signal threshold to be flexibly adjusted according to different audio scenarios, thereby more accurately filtering out effective signals. By comparing the real-time audio signal strength with the threshold, effective signals are retained and invalid signals are removed, avoiding interference from invalid data to subsequent processing. Finally, the maximum strength of the effective signal is used for volume control, ensuring that the volume can be reasonably adjusted according to the actual intensity of the audio.

[0058] Adjusting the volume based on the real-time audio signal strength after noise filtering further includes: extracting the signal strength through noise filtering. Set the initial volume ,in This is a scaling factor that controls the loudness ratio of the sound. ;

[0059] when Exceeding the maximum adjustable volume limit Then according to Limit the output; otherwise, leave the original value unchanged.

[0060] Output volume for each frame of data The weighted moving average algorithm is applied for smoothing adjustment, and the calculation method is as follows:

[0061] ,in The value of the previous frame. This is the weighting factor, with a default value of 0.7;

[0062] Output of the weighted moving average algorithm Perform graded mapping: Define Volume levels and ;

[0063] set up This represents the step increment for each level; if the current weighted volume... , corresponding to the Set the volume level; otherwise, trigger the exception handling mechanism and set the volume to the default middle level.

[0064] The specific workflow of the volume control module is as follows: First, the initial volume is set by the scaling factor γ. Users can adjust the loudness ratio of the sound according to their own needs. The volume limiting mechanism ensures that the output volume will not exceed the maximum capacity of the system, protecting the hearing of the device and the user. The use of the weighted moving average algorithm makes the volume adjustment smoother and avoids the discomfort caused to users by sudden changes in volume. The level mapping divides the volume into multiple levels, making it easy for users to intuitively understand and control the volume. At the same time, the exception handling mechanism ensures that the volume can be restored to a reasonable default value in the event of an abnormal situation.

[0065] The frequency analysis module analyzes the frequency characteristics of audio data to determine the corresponding light color parameters. Methods include: decomposing the noise-filtered sound data into multiple sub-frequency bands. , And calculate the spectral energy for each sub-band. ,in The amplitude spectrum;

[0066] Calculate total power and set a threshold Active sub-bands are selected based on this threshold.

[0067] in The expression determines the correlation between the color change rate and the spectral distribution. The parameters are adaptive weights; if they exceed... If so, then mark this part as the dominant color gamut;

[0068] Add a delay compensation factor to the criteria for determining active frequency bands. ,in It is the sampling rate differential. The parameter representing the difference in delay window length is used to improve synchronization issues.

[0069] That is, whenever a frequency band is detected to exceed the threshold, the influence weight of this delay is increased. Bit;

[0070] The frequency analysis module works by decomposing audio data into multiple sub-bands and calculating their spectral energy, providing a deeper understanding of the frequency distribution characteristics of the audio. By setting a threshold ThColor, active sub-bands are filtered and marked as the dominant color gamut, providing a basis for determining the color of the lights. The introduction of adaptive weight t allows the correlation between the color change rate and spectral distribution and the color of the lights to be adjusted according to the actual situation. The addition of a delay compensation factor solves the problem of the lights and music rhythm being out of sync. By increasing the weight of the delay effect, the synchronization accuracy between the lights and music is improved.

[0071] The lighting control module calculates the following color mapping relationship for the active dominant color gamut based on the sub-frequency bands: For Color mapping establishment function for dominant region , representing color coordinates Relationship matrix between active states of sub-bands For color table functions, and These are all system optimization configurations;

[0072] Among them when At this time, it enters a high-brightness enhanced display mode; simultaneously, it defines color switching smoothness rules. To ensure a smooth color transition;

[0073] The lighting control module maps and switches light colors based on the dominant color gamut. The color mapping function L(m,Sk) establishes the relationship between color coordinates and the active state of sub-bands. By adjusting the system optimization configuration parameters αC and β, the color mapping effect can be optimized, making the light colors more in line with the emotion and rhythm of the music. When the active state of a sub-band exceeds the threshold Sth, a high-brightness enhanced display mode is entered, enhancing the visual effect of the light. The color switching smoothness rule Cm ensures that the color transition is smooth when the light colors are switched, avoiding abrupt color changes and bringing users a more comfortable visual experience.

[0074] When adjusting the light color, the lighting control module introduces a multi-level dynamic dimming mode, that is, when the number of main frequency regions K detected is greater than ThresholdFreqBand, the advanced color mixing mode is activated. Here, the threshold adjustment factor controls the global light increase / decrease logic;

[0075] The lighting control module's dimming mode, with its multi-level dynamic dimming mode, allows the lighting system to adjust colors more flexibly based on the complexity of the audio. When the number of detected main frequency regions exceeds the threshold ThresholdFreqBand, the advanced color mixing mode is activated. The advanced color mixing mode formula H(m,Kcolor,Thr) is used to calculate the color and brightness of the lights. The threshold adjustment factor can control the logic of increasing or decreasing global light, allowing the lighting effects to better match the rhythm and emotion of the music.

[0076] The environmental sound interference assessment module utilizes external environmental noise. To correct the signal-to-noise ratio in the main audio data This indirectly affects the accuracy of the linkage between music and lighting, and the correction item This refers to the deviation correction range;

[0077] The working principle of the environmental sound interference assessment module is as follows: This module monitors the external environmental noise (Nenv) in real time and calculates the signal-to-noise ratio (SNR) of the main sound data. The SNR reflects the relative intensity of the signal and noise in the main sound data. By correcting the SNR, the impact of external environmental noise on the audio system can be reduced. The correction fcrrct is used as the deviation correction amplitude to adjust the control parameters of lighting and volume, thereby indirectly affecting the accuracy of the linkage between music and lighting, ensuring that the audio system can maintain good performance under different environmental sound effects.

[0078] The system provides a method for dynamically updating the frequency feature library to adapt to the needs of more complex music genres, and employs a periodic learning method to adjust the formula. ,in Error correction values ​​are derived from historical data. It is a weighted historical spectrum contribution to ensure continuous improvement in the synchronization of lights with different types of music;

[0079] The system's dynamic updating and learning capabilities, including its dynamically updated frequency feature library, enable the audio system to adapt to more complex music genres. By continuously updating the frequency feature library, the system can better analyze and process music of different styles. The periodic learning method adjusts the formula...

[0080] Pftr_update updates the frequency characteristics, where Pbase is the base frequency characteristic, Fw(Phist) takes into account the contribution of historical spectrum, and αPEnvErr is an error correction value derived from historical data, used to correct the system's errors in different environments. In this way, the synchronization between the lights and different types of music can be continuously improved.

[0081] The system has added special light display logic for extreme high-frequency burst sounds and defined abrupt change thresholds. If the detection result exceeds this mutation amount at a certain moment, a short flashing light warning action sequence will be immediately triggered to enhance the visual impact of the on-site experience and solve the pain point of audio-visual asynchrony.

[0082] The system features a special handling mechanism for extreme high-frequency bursts of sound. Extreme high-frequency bursts can cause audio-visual desynchronization and a poor user experience. By defining a sudden change threshold Dth, the system can monitor sudden changes in the audio signal in real time. When the detected value exceeds the threshold, a short-flashing light warning sequence is immediately triggered. This unique light display logic not only enhances the visual impact of the live experience but also solves the technical pain point of audio-visual desynchronization, improving the user's audiovisual experience.

[0083] A light-responsive sound system based on data analysis is provided, which is equipped with a system self-test and optimization module. This module periodically performs functional checks and performance evaluations on the audio signal processing module, volume control module, frequency analysis module, light control module, and environmental sound interference evaluation module.

[0084] For the audio signal processing module, check whether the parameter settings of the low-pass filter are within a reasonable range, verify the noise filtering effect and the accuracy of real-time audio signal strength extraction. If the deviation is found to exceed the preset threshold, automatically adjust the filter parameters or recalibrate the signal extraction algorithm.

[0085] For the volume control module, evaluate the smoothness and accuracy of volume control, check whether the calculation results of the weighted moving average algorithm meet expectations, and adjust the weighting coefficient λ or scaling coefficient γ if there are sudden volume changes or mismatch with audio signal strength.

[0086] For the frequency analysis module, check the stability of sub-band decomposition and the accuracy of spectral energy calculation. If the dominant color gamut selection is found to be inaccurate or the color change rate is abnormal, readjust the adaptive weight t or the threshold ThColor.

[0087] For the lighting control module, check the execution of the color mapping function and the color switching smoothing rule. If abnormal color display or unstable transition occurs, adjust the system optimization configuration parameters αC, β or smoothing coefficient μ.

[0088] For the environmental sound interference assessment module, check the accuracy of the signal-to-noise ratio calculation and the effectiveness of the correction items. If it is found that the accuracy of the music and lighting linkage does not meet expectations, reassess the impact of external environmental noise and adjust the relevant parameters of the deviation correction amplitude.

[0089] Meanwhile, this module records the results of each inspection and optimization, forming a system operation log, providing data support for subsequent in-depth optimization and troubleshooting. The system self-check and optimization module plays a crucial role, periodically performing functional checks and performance evaluations on each core module to ensure the stability and reliability of the entire audio system. The focus of the inspection and optimization methods differ for different modules. For example, for the audio signal processing module, the focus is on checking filter parameters and the accuracy of signal extraction; for the volume control module, the focus is on the smoothness and accuracy of volume adjustment. By promptly identifying and resolving problems and adjusting corresponding parameters and algorithms, the system can continuously optimize its performance. Furthermore, the system operation log provides valuable data support for subsequent in-depth optimization and troubleshooting, enabling the system to continuously improve and refine.

[0090] The system first analyzes and processes the audio data, including noise filtering to obtain real-time audio signal strength, extracting frequency features from the audio data to control the color display of the lights, and finally achieving perfect synchronization between the music rhythm and the changes in light and shadow, as well as a high degree of matching between the live sound effects and visual effects.

[0091] The first part of the work involves real-time acquisition of audio data and preliminary preprocessing, particularly noise filtering. Specifically, this process involves using modern digital signal processing techniques, such as Fast Fourier Transform (FFT) or wavelet transform, to analyze the time-frequency characteristics of the audio data, obtaining a cleaner real-time audio signal by filtering out high-frequency noise or other unwanted signal interference. The key objective of this step is to eliminate unnecessary background noise or human interference (such as ambient sound or internal electronic noise) from the input audio data to the greatest extent possible, thereby ensuring high-quality foundational data for subsequent adjustments and accurately reflecting the true sound content.

[0092] Next, after noise filtering, the intensity of the optimized audio signal is extracted. Techniques used in this stage may include envelope detection or sliding window averaging to quantify the real-time strength of the currently playing audio. The obtained data will be used as one of the bases for adjusting the output power or size of the audio equipment. For example, in a concert setting, if a strong drumbeat suddenly occurs at a certain point, this step can accurately detect this drastic amplitude change and trigger a correspondingly large gain adjustment feedback action, allowing the audience to experience a powerful and stable live effect, avoiding discomfort or even equipment damage caused by fluctuations in the original audio. This also directly addresses the uncertainty and error problems caused by the original unprocessed signal—the so-called control failure due to an excessively large dynamic range.

[0093] Furthermore, regarding the color management of the lighting system, we focused on the design concept of mapping different frequency band information to specific color coding modes and put it into practice. This involves meticulously breaking down the entire sound wave coverage into three main zones: the bass range (<1kHz), the vocal range (approximately 0k-4kHz), and the high-pitched, energetic portion (>8kHz). Then, we establish specific HSV value conversion formulas for each zone according to certain rules. This allows us to instantly calculate the optimal visual color for any given melody. For example, in one embodiment, when the low-frequency range is highly active, the light gradually changes to a deep red tone to simulate a calm atmosphere. Simultaneously, if high frequencies are detected, the light switches to cool colors such as light blue or cyan to create a refreshing feel, matching the light and lively characteristics of the notes.

[0094] Specifically, after deploying this solution at a concert venue, the following example operation process can be observed to verify its effectiveness. Assume a classic piece is being played and all sensors and algorithm models are connected and ready to launch. The moment the musician strikes the opening chord, the backend system immediately captures this signal and executes all the aforementioned pre-defined processes sequentially: first, a filter removes irrelevant noise such as conversations from surrounding people; then, the initial sound pressure level is measured at approximately 70dB, indicating it needs to be boosted to near the normal standard value to ensure sufficient coverage without being overly noisy or harsh; next, the independent wavelengths produced by each instrument are identified to determine their respective emotional cues, which are then translated into corresponding visual effects and presented to each guest, allowing them to witness the start of an immersive, multi-sensory feast. This experience greatly enriches the participants' sensory experience and significantly improves the overall professionalism and technical sophistication of the performance.

[0095] This invention discloses a data analysis-based lighting and sound control system, comprising: comprehensive analysis and multi-level processing of audio data to achieve a high degree of matching between music rhythm and dynamic lighting and volume control. The overall steps are as follows: First, the system acquires and preprocesses the raw audio data, filtering out noise components through advanced digital signal processing algorithms to extract clean real-time audio signal strength, thereby solving the problem of unstable sound effects caused by noise interference. Next, based on the extracted audio signal strength, the system dynamically adjusts the output volume of the sound system to ensure it matches user needs and the atmosphere of the event, solving the problem of mismatch between sound and visual effects in traditional equipment.

[0096] To achieve synchronized light color changes with the music rhythm, the system further analyzes the frequency characteristics of the audio data. Frequency characteristics are one of the core elements of audio information, encompassing the distribution characteristics of high and low frequencies, such as low-frequency drumbeats, mid-frequency melodies, and high-frequency notes. Based on the precise capture and analysis of frequency characteristics, the system dynamically generates light color parameters that match the current music segment. For example, low-frequency drumbeats are associated with red light or other warm tones, while high-frequency notes are mapped to blue light or cool-toned lights. Furthermore, these light displays also adjust their brightness in accordance with the intensity of specific audio signals, enhancing the integrated audiovisual experience and thus solving the problem of insufficient synchronization between light and shadow and music rhythm in traditional solutions.

[0097] Overall, the control system achieves the effect of audio-driven lighting from multiple dimensions and uses scientific algorithms to optimize the overall coordination between sound and light, bringing revolutionary changes to the user experience.

[0098] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A light-and-sound control system based on data analysis, characterized in that, include: The audio signal processing module is used to filter noise from audio data and extract real-time audio signal strength. The noise filtering and real-time audio signal strength extraction include: using a low-pass filter to eliminate noise signals above frequency Fc from the original audio data; and setting a threshold value Vt = α × 1000 for the filtered audio data signal. Where α is a dynamically adjusted parameter, ranging from [0.2, 0.5]. The average signal strength is used. If the real-time audio signal strength V(i) satisfies the condition |V(i)|≥Vt, then the data point is retained as a valid signal; otherwise, it is considered an invalid signal, and the maximum value MaxSig of the data strength of the filtered valid signal is taken for subsequent calculation of volume control. The audio signal processing module is used to filter noise from audio data and extract real-time audio signal strength. A volume control module, connected to the audio signal processing module, is used to adjust the volume based on the real-time audio signal strength after noise filtering. The frequency analysis module is used to analyze the frequency characteristics of audio data in order to determine the corresponding light color parameters; The lighting control module, connected to the frequency analysis module, is used to adjust the color display of the lights based on the light color parameters in order to achieve synchronization with the music rhythm; The environmental sound interference assessment module is used to correct the signal-to-noise ratio in the main sound data by utilizing external environmental noise, thereby improving the system robustness.

2. The light-following sound control system based on data analysis according to claim 1, characterized in that, The method of adjusting the volume based on the real-time audio signal strength after noise filtering further includes: Signal strength is extracted through noise filtering. Set the initial volume ,in This is a scaling factor that controls the loudness ratio of the sound. ; when Exceeding the maximum adjustable volume limit Then according to Limit the output; otherwise, leave the original value unchanged. Output volume for each frame of data The weighted moving average algorithm is applied for smoothing adjustment, and the calculation method is as follows: ,in The value of the previous frame. This is the weighting factor, with a default value of 0.7; Output of the weighted moving average algorithm Perform graded mapping: Define Volume levels and ; set up This represents the step increment for each level; if the current weighted volume... , corresponding to the Set the volume level; otherwise, trigger the exception handling mechanism and set the volume to the default middle level.

3. The light-following sound control system based on data analysis according to claim 1, characterized in that, The frequency analysis module analyzes the frequency characteristics of audio data to determine the corresponding light color parameters, including the following methods: The noise-filtered audio data is decomposed into multiple sub-frequency bands. , And calculate the spectral energy for each sub-band. ,in The amplitude spectrum; Calculate total power and set a threshold Active sub-bands are selected based on this threshold. in The expression determines the correlation between the color change rate and the spectral distribution. The parameters are adaptive weights; if they exceed... If so, then mark this part as the dominant color gamut; Add a delay compensation factor to the criteria for determining active frequency bands. ,in It is the sampling rate differential. The parameter representing the difference in delay window length is used to improve synchronization issues. That is, whenever a frequency band is detected to exceed the threshold, the delay impact weight based on that delay compensation factor is increased. Bit.

4. The light-following sound control system based on data analysis according to claim 2, characterized in that, The lighting control module calculates the lighting color mapping relationship of the active dominant color gamut based on the sub-frequency band as follows: against Color mapping establishment function for dominant region , representing color coordinates Relationship matrix between active states of sub-bands For color table functions, and These are all system optimization configurations; Among them when When this happens, it enters high brightness enhancement display mode; Simultaneously define color switching smoothing rules .

5. A data analysis-based lighting and sound control system according to claim 3, characterized in that, The lighting control module introduces a multi-level dynamic dimming mode when adjusting the light color. Specifically, when the number of detected main frequency regions K > ThresholdFreqBand, the advanced color mixing mode is activated. .

6. A light-following sound control system based on data analysis according to claim 4, characterized in that, The environmental first-effect interference assessment module utilizes external environmental noise. To correct the signal-to-noise ratio in the main audio data This indirectly affects the accuracy of the linkage between music and lighting, and the correction item... This represents the deviation correction range.

7. A light-following sound control system based on data analysis according to claim 5, characterized in that, The system provides a method for dynamically updating the frequency feature library to adapt to the needs of more complex music genres, and employs a periodic learning method to adjust the formula. ,in Error correction values ​​are derived from historical data. It is the weighted historical spectrum contribution.

8. A data analysis-based lighting and sound control system according to claim 6, characterized in that, The system has added special light display logic for extreme high-frequency burst sounds and defined abrupt change thresholds. If the detection result exceeds this mutation amount at any time, a short flashing light warning sequence will be immediately triggered to enhance the visual impact of the on-site experience.

9. A data-analysis-based light-following sound system, employing a data-analysis-based light-following sound control system as described in any one of claims 1-8, characterized in that, The system is equipped with a self-test and optimization module, which periodically performs functional checks and performance evaluations on the audio signal processing module, volume control module, frequency analysis module, lighting control module, and environmental sound effect interference evaluation module. For the audio signal processing module, check whether the parameter settings of the low-pass filter are within a reasonable range, verify the noise filtering effect and the accuracy of real-time audio signal strength extraction. If the deviation is found to exceed the preset threshold, automatically adjust the filter parameters or recalibrate the signal extraction algorithm. For the volume control module, evaluate the smoothness and accuracy of volume control, check whether the calculation results of the weighted moving average algorithm meet expectations, and adjust the weighting coefficient λ or scaling coefficient γ if there are sudden volume changes or mismatch with audio signal strength. For the frequency analysis module, check the stability of sub-band decomposition and the accuracy of spectral energy calculation. If the dominant color gamut selection is found to be inaccurate or the color change rate is abnormal, readjust the adaptive weight t or the threshold ThColor. For the lighting control module, check the execution of the color mapping function and the color switching smoothing rule. If abnormal color display or unstable transition occurs, adjust the system optimization configuration parameters αC, β or smoothing coefficient μ. For the environmental sound interference assessment module, the accuracy of the signal-to-noise ratio calculation and the effectiveness of the correction items are checked. If the accuracy of the music and lighting linkage is found to be less than expected, the impact of external environmental noise is reassessed and the relevant parameters of the deviation correction amplitude are adjusted. At the same time, this module records the results of each check and optimization, forming a system operation log.

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