Light follow-up sound based on data analysis and control system thereof

Abstract

The invention relates to the technical field of sound equipment, and discloses a light follow-up sound equipment based on data analysis and a control system thereof, and the system comprises an audio signal processing module which is used for carrying out the noise filtering of audio data, and extracting the real-time audio signal intensity; the volume regulation and control module is connected with the audio signal processing module and used for regulating and controlling the volume according to the intensity of the real-time audio signal after noise filtering; the frequency analysis module is used for analyzing frequency characteristics of the audio data so as to determine corresponding light color parameters; according to the system, the audio is processed by adopting dynamic filtering and weighting algorithms, and the signal intensity is accurately extracted to regulate and control the volume. High synchronization of light and music is realized through delay compensation and adaptive threshold analysis frequency characteristics in combination with multi-stage dimming, and meanwhile, environment interference correction and system self-inspection are realized, so that the audio-visual experience of a user is improved.

Description

Technical Field

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

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

[0003] However, the system has some urgent problems 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 adjust the lighting color to achieve a highly synchronized effect between dynamic light and shadow and music rhythm; Secondly, noise interference in the live environment can affect the authenticity of the audio signal strength. Therefore, it is necessary to further optimize the noise filtering algorithm and dynamically adjust the volume based on the real-time processed audio signal strength to ensure the consistency and matching of the sound and visual effects. These two issues directly affect the overall performance of the system and the user experience. Summary of the Invention

[0004] In order to solve the problems raised by the above background technology, the present application provides a light-following sound system and a control system thereof based on data analysis.

[0005] The present application provides a light-following sound system and its control system based on data analysis, which adopts the following technical solutions: A light-following sound control system based on data analysis, comprising: Audio signal processing module, used to filter the audio data for noise and extract the real-time audio signal strength; A volume control module, connected to the audio signal processing module, is used to control the volume according to the intensity of the real-time audio signal after noise filtering; Frequency analysis module, used to analyze the frequency characteristics of audio data to determine the corresponding light color parameters; A lighting control module, connected to the frequency analysis module, for adjusting the color display of the lights based on the lighting color parameters to achieve synchronization with the music rhythm; The environmental sound interference evaluation module is used to use external environmental noise to correct the signal-to-noise ratio in the main sound data and improve the robustness of the system.

[0006] Preferably, the method of performing noise filtering on the audio data and extracting the real-time audio signal strength further includes: Apply a low-pass filter to the raw audio data to remove frequencies above Noise signal; Set the threshold of the filtered audio data signal ,in is a dynamic adjustment parameter with a range of [0.2, 0.5], is the average signal strength; When the real-time audio signal strength Meet the conditions , then the data point is retained as a valid signal; otherwise it is considered an invalid signal, and the data strength of the filtered valid signal is taken as the maximum value MaxSig for subsequent calculation of volume control.

[0007] Preferably, the step of adjusting the volume according to the intensity of the real-time audio signal after noise filtering further comprises: Extracting signal strength by noise filtering , set the initial volume ,in is the scaling factor, which controls the sound loudness ratio. ; when Exceeding the maximum adjustable volume limit , then press Limit the output; otherwise, keep the original value unchanged; Output volume for each frame of data Apply weighted moving average algorithm for smoothing adjustment, the calculation method is; ,in is the previous frame value, is the weighting coefficient, the default value is 0.7; Output of the weighted moving average algorithm Perform bin mapping: Definition volume levels and ; set up Indicates the step increment of each level; if the current weighted volume , corresponding to Otherwise, the exception handling mechanism is triggered and the volume is set to the default middle level.

[0008] Preferably, the method in which the frequency analysis module analyzes the frequency characteristics of the audio data to determine the corresponding light color parameters includes: Decompose the noise-filtered sound data into multiple sub-bands , , and calculate the spectrum energy for each sub-band ,in is the amplitude spectrum; Calculating total power , and set the threshold ; Filter active sub-bands based on this threshold in The expression determines the color change rate and the correlation of the spectrum distribution. The parameter is the adaptive weight; if it exceeds , then mark this part as the dominant color gamut; Added delay compensation factor to the active main frequency band judgment rule ,in is the sampling rate differential, Express the delay window length difference parameter to improve synchronization issues; That is, whenever a frequency band is detected to exceed the threshold, the delay impact weight is increased. Bit.

[0009] 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: against Color mapping function for the dominant area , indicating the color coordinates Relationship matrix with sub-band active status is the color table function, and They are all system optimization configurations; Among them When the display is turned on, it enters high-brightness enhanced display mode; At the same time, define the color switching smoothing rules , ensuring smooth color transition.

[0010] Preferably, the lighting control module introduces a multi-level dynamic dimming mode when adjusting the lighting color, that is, when the number of detected main frequency areas K>ThresholdFreqBand, the advanced color mixing mode is activated. , where the threshold adjustment factor controls the global light increase and decrease logic.

[0011] Preferably, the environmental sound interference assessment module utilizes external environmental noise To correct the signal-to-noise ratio in the main sound data , which indirectly affects the accuracy of the linkage between music and light and shadow, and the correction term is the deviation correction amplitude.

[0012] Preferably, the system provides a method for dynamically updating the frequency feature library to adapt to the needs of more complex music types, and uses a periodic learning method to adjust the formula ,in Generate error correction values ​​derived from historical data, It is the weighted historical spectrum contribution that ensures continuous improvement in the synchronization of lighting and different types of music.

[0013] Preferably, the system adds special light display logic for extreme high-frequency burst sounds, defining the mutation threshold If the detection result at a certain moment exceeds this mutation amount, a short flashing light warning action sequence will be triggered immediately, enhancing the visual shock effect of the on-site experience while solving the technical pain point of audio and video asynchrony.

[0014] Preferably, a light-following audio system based on data analysis is provided with a system self-checking 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 interference evaluation module; For the audio signal processing module, check whether the low-pass filter parameter settings are within a reasonable range, verify the noise filtering effect and the accuracy of real-time audio signal strength extraction. If the deviation exceeds 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 and check whether the calculation results of the weighted moving average algorithm meet expectations. If there is a sudden change in volume or a mismatch with the audio signal strength, adjust the weighting factor λ or scaling factor γ. For the frequency analysis module, check the stability of sub-band decomposition and the accuracy of spectrum energy calculation. If it is found that the dominant color gamut screening is inaccurate or the color change rate is abnormal, readjust the adaptive weight t or 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 ambient sound interference assessment module, check the accuracy of the signal-to-noise ratio calculation and the effectiveness of the correction term. If the accuracy of the music and light-shadow linkage is found to be less than expected, re-evaluate the impact of external ambient noise and adjust the parameters related to the deviation correction amplitude. At the same time, the module records the results of each inspection and optimization to form a system operation log, providing data support for subsequent in-depth optimization and troubleshooting.

[0015] In summary, this application includes at least one of the following beneficial technical effects: The data-analysis-based light-following audio control system of the disclosed embodiment effectively overcomes the challenges of existing technologies through multi-module collaborative design and optimization algorithms. In the audio signal processing module, a dynamic threshold low-pass filtering algorithm is used to precisely filter out ambient noise interference, ensuring the authenticity and 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 step-by-step mapping mechanism to achieve smooth and precise volume adjustment and control, ensuring stable sound output. The frequency analysis module innovatively introduces a delay compensation factor and an adaptive weight threshold screening mechanism to deeply analyze audio frequency characteristics and accurately determine lighting color parameters. The lighting control module uses a color mapping function and smooth switching rules, combined with multi-level dynamic dimming modes, to achieve precise synchronization of lighting color with music rhythm, enhancing visual expression. In addition, the ambient 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 enhancing the system's robustness and adaptability, significantly improving the user's audio-visual experience and providing an immersive audio-visual interactive experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of the sound control system; Figure 2 For parameter embodiment; Figure 3 For experimental data. DETAILED DESCRIPTION

[0017] Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings.

[0018] Throughout this specification, reference to the terms "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, the schematic representations 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 any one or more embodiments or examples.

[0019] The present application discloses a light-following sound system and its control system based on data analysis. Referring to the accompanying drawings, the following describes the implementation steps of the light-following sound control system based on data analysis of the present invention. A light-following sound control system based on data analysis includes: an audio signal processing module for filtering audio data for noise and extracting real-time audio signal strength; a volume control module, connected to the audio signal processing module, for adjusting the volume based on the real-time audio signal strength after noise filtering; a frequency analysis module, for analyzing the frequency characteristics of the audio data to determine corresponding light color parameters; a light control module, connected to the frequency analysis module, for adjusting the light color display 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 to improve system robustness. 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 pre-processes 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 volume with the audio content. The frequency analysis module provides color parameters for lighting control by analyzing the audio frequency characteristics, realizing the linkage between lighting and music. The lighting control module controls the display of lighting color according to these parameters to create an atmosphere consistent with the rhythm of music. The environmental sound interference assessment module takes into account 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.

[0020] Based on the noise filtering of audio data and extracting the real-time audio signal strength, the method further includes: using a low-pass filter to eliminate the original audio data with a frequency higher than Noise signal; Set the threshold of the filtered audio data signal ,in is a dynamic adjustment parameter with a range of [0.2, 0.5], is the average signal strength; When the real-time audio signal strength Meet the conditions , then the data point is retained as a valid signal; otherwise it is considered an invalid signal, and the data strength of the filtered valid signal is taken as the maximum value MaxSig for subsequent calculation of volume control; 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 dynamic adjustment parameter α enables the signal threshold to be flexibly adjusted according to different audio scenarios, thereby more accurately screening out valid signals. By comparing the real-time audio signal strength and the threshold, the valid signal is retained and the invalid signal is removed, avoiding the interference of invalid data on subsequent processing. Finally, the maximum strength of the valid signal is used for volume control to ensure that the volume can be reasonably adjusted according to the actual strength of the audio.

[0021] Controlling 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 is the scaling factor, which controls the sound loudness ratio. ; when Exceeding the maximum adjustable volume limit , then press Limit the output; otherwise, keep the original value unchanged; Output volume for each frame of data Apply weighted moving average algorithm for smoothing adjustment, the calculation method is; ,in is the previous frame value, is the weighting coefficient, the default value is 0.7; Output of the weighted moving average algorithm Perform bin mapping: Definition volume levels and ; set up Indicates the step increment of each level; if the current weighted volume , corresponding to Otherwise, the exception handling mechanism is triggered and the volume is set to the default middle level; 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 needs. The volume limit mechanism ensures that the output volume does not exceed the maximum tolerance of the system, protecting the hearing of the device and the user. The use of the weighted moving average algorithm makes volume adjustment smoother, avoiding the discomfort caused by sudden volume changes. The tiered mapping divides the volume into multiple levels, making it easier for users to intuitively understand and control the volume level. 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. The method of analyzing the frequency characteristics of the audio data to determine the corresponding light color parameters by the frequency analysis module includes: decomposing the noise-filtered sound data into multiple sub-bands , , and calculate the spectrum energy for each sub-band ,in is the amplitude spectrum; Calculating total power , and set the threshold ; Filter active sub-bands based on this threshold in The expression determines the color change rate and the correlation of the spectrum distribution. The parameter is the adaptive weight; if it exceeds , then mark this part as the dominant color gamut; Added delay compensation factor to the active main frequency band judgment rule ,in is the sampling rate differential, Express the delay window length difference parameter to improve synchronization issues; That is, whenever a frequency band is detected to exceed the threshold, the delay impact weight is increased. Bit; The working principle of the frequency analysis module is to decompose the audio data into multiple sub-bands and calculate their spectral energy, which can provide an in-depth understanding of the frequency distribution characteristics of the audio. By setting the threshold ThColor, active sub-bands are screened and marked as the dominant color domain, which provides a basis for determining the color of the light. The introduction of the adaptive weight t allows the color change rate and the correlation between the spectrum distribution and the light color to be adjusted according to actual conditions. The addition of the delay compensation factor solves the problem of the light and music rhythm being out of sync. By increasing the delay impact weight, the synchronization accuracy of the light and music is improved.

[0022] The lighting control module calculates the lighting color mapping relationship of the active dominant color range based on the sub-band as follows: Color mapping function for the dominant area , indicating the color coordinates Relationship matrix with sub-band active status is the color table function, and They are all system optimization configurations; Among them When the display mode is high brightness, it will enter the enhanced display mode; at the same time, it will define the color switching smoothing rules. , ensure smooth color transition; How does the lighting control module map and switch lighting 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 the sub-band. By adjusting the system optimization configuration parameters αC and β, the color mapping effect can be optimized to make the lighting color more in line with the emotion and rhythm of the music. When the active state of the sub-band exceeds the threshold Sth, it enters the high-brightness enhanced display mode, enhancing the visual effect of the lighting. The color switching smoothing rule Cm ensures that the color transition is smooth when the light color switches, avoiding abrupt color changes, giving users a more comfortable visual experience.

[0023] 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 areas K>ThresholdFreqBand, the advanced color mixing mode is activated. , where the threshold adjustment factor controls the global light increase and decrease logic; The dimming mode of the lighting control module and the introduction of multi-level dynamic dimming mode enable the lighting system to perform more flexible color control according to the complexity of the audio. When the number of detected main frequency areas exceeds the threshold ThresholdFreqBand, the advanced color mixing mode is activated, and the color and brightness of the light are calculated using the advanced color mixing mode formula H(m,Kcolor,Thr). The threshold adjustment factor can control the increase and decrease logic of the global light, so that the lighting effect can better match the rhythm and emotion of the music.

[0024] The environmental sound interference assessment module uses external environmental noise To correct the signal-to-noise ratio in the main sound data , which indirectly affects the accuracy of the linkage between music and light and shadow, and the correction term is the deviation correction amplitude; The working principle of the environmental sound interference assessment module is that this module calculates the signal-to-noise ratio (SNR) of the main sound data by monitoring the external environmental noise Nenv in real time. The signal-to-noise ratio reflects the relative strength of the signal and noise in the main sound data. By correcting the signal-to-noise ratio, the impact of external environmental noise on the sound system can be reduced. The correction fcrrct is used as the deviation correction amplitude to adjust the control parameters of the light and volume, thereby indirectly affecting the accuracy of the linkage between music and light and shadow, ensuring that the sound system can maintain good performance under different environmental sound effects.

[0025] The system provides a method to dynamically update the frequency feature library to adapt to the needs of more complex music types, and uses a periodic learning method to adjust the formula ,in Generate error correction values ​​derived from historical data, It is the weighted historical spectrum contribution to ensure continuous improvement in the synchronization of lighting and different types of music; The system's dynamic update and learning capabilities, dynamic update of the frequency feature library enables the sound system to adapt to more complex music types. By continuously updating the frequency feature library, the system can better analyze and process different styles of music. The periodic learning method adjusts the formula Pftr_update is used to update the frequency characteristics, where Pbase is the basic frequency characteristic, Fw(Phist) takes into account the contribution of the historical spectrum, and αPEnvErr is the error correction value derived from historical data, which is used to correct the error of the system in different environments. In this way, the synchronization between lighting and different types of music can be continuously improved.

[0026] The system adds special lighting display logic for extreme high-frequency burst sounds and defines the mutation threshold If the detection result at a certain moment exceeds this mutation amount, a short flashing light warning action sequence will be immediately triggered, enhancing the visual impact of the on-site experience while solving the technical pain point of audio and video asynchrony. The system has a special processing mechanism for extremely high-frequency bursts. These can cause audio and video desynchronization and a poor user experience. By defining a mutation threshold (Dth), the system monitors sudden changes in the audio signal in real time. When the detection result exceeds the threshold, a short flashing light warning sequence is immediately triggered. This unique lighting display logic not only enhances the visual impact of the live experience, but also resolves the technical pain point of audio and video desynchronization, improving the user's visual and auditory experience.

[0027] A data analysis-based light-following audio system is equipped with a system self-check 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 interference evaluation module. For the audio signal processing module, check whether the low-pass filter parameter settings are within a reasonable range, verify the noise filtering effect and the accuracy of real-time audio signal strength extraction. If the deviation exceeds 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 and check whether the calculation results of the weighted moving average algorithm meet expectations. If there is a sudden change in volume or a mismatch with the audio signal strength, adjust the weighting factor λ or scaling factor γ. For the frequency analysis module, check the stability of sub-band decomposition and the accuracy of spectrum energy calculation. If it is found that the dominant color gamut screening is inaccurate or the color change rate is abnormal, readjust the adaptive weight t or 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 ambient sound interference assessment module, check the accuracy of the signal-to-noise ratio calculation and the effectiveness of the correction term. If the accuracy of the music and light-shadow linkage is found to be less than expected, re-evaluate the impact of external ambient noise and adjust the parameters related to the deviation correction amplitude. At the same time, the 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-inspection and optimization module plays an important role. This module periodically performs functional inspections and performance evaluations on each core module to ensure the stability and reliability of the entire audio system. Different modules have different inspection focuses and optimization methods. For example, for the audio signal processing module, the focus is on checking the 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 discovering and resolving problems and adjusting the corresponding parameters and algorithms, the system can continuously optimize its own performance. At the same time, the system operation log records provide valuable data support for subsequent in-depth optimization and troubleshooting, enabling the system to be continuously improved and perfected.

[0028] The system first analyzes and processes the audio data, including noise filtering to obtain real-time audio signal strength, extracting frequency characteristics from the audio data to control the light color display, and ultimately achieving perfect synchronization between the music rhythm and the changes in light and shadow, as well as a high degree of matching between the on-site sound effects and visual effects.

[0029] The first part of the work is based on the real-time acquisition of audio data and preliminary pre-processing of the data, especially 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, and obtain a relatively clean real-time audio signal by filtering out high-frequency noise or other unnecessary signal interference. The key goal of this step is to remove unnecessary background noise or human interference (such as ambient sound or internal electronic noise of the device) in the input audio data to the greatest extent possible, thereby ensuring that the basic data for subsequent regulation is of high quality and can accurately reflect the real sound content.

[0030] Next, after noise filtering is complete, the optimized audio signal strength is further extracted. Techniques employed at this stage may include envelope detection or sliding window average calculation, aiming to quantify the real-time strength of the currently playing audio. The data obtained will be used as one of the bases for adjusting the output power or volume of the audio equipment. For example, in a concert setting, if a strong drum beat suddenly occurs at a certain point in time, this step can accurately perceive this dramatic amplitude change, triggering a corresponding large gain adjustment feedback action, allowing the audience to experience a shocking 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 caused by the original unprocessed signal—the so-called control failure caused by excessive dynamic range.

[0031] Turning to the color management of the lighting system, we focused on the design concept and practical application of a mechanism that maps the analyzed frequency band information to specific color coding patterns. By carefully breaking down the entire sound wave range into three typical levels, such as the bass range (<1kHz), the human voice range (approximately 0k-4kHz), and the high-pitched and exciting range (>8kHz), we developed a corresponding HSV value conversion formula based on specific rules. This allows us to instantly calculate the optimal visual presentation color for any melody. For example, in one embodiment, when the low frequency range is high, the lighting gradually changes to a deep red to simulate a calm atmosphere. Simultaneously, if high frequencies are detected, the lighting switches to cooler colors such as light blue or turquoise to create a fresh feeling, complementing the light and lively nature of the notes.

[0032] Specifically, after deploying this solution at a concert venue, its effectiveness can be verified by observing the following example operation process. Assume a classical piece is being performed, and all sensors and algorithm models are connected and ready to launch. As the musician strikes the opening chord, the backend system immediately detects this signal and executes all the previously defined processes. First, a filter removes irrelevant noise, such as conversations. Next, the sound pressure level of the initial segment is measured at approximately 70dB, determining that it needs to be raised to near the standard value to ensure sufficient coverage without being harsh. The system then identifies the individual wavelengths produced by each instrument, determines the emotional cues they carry, and transforms them into corresponding visual effects for each guest to witness as they witness the beginning of an immersive, multi-sensory feast. This experience greatly enriches the participants' sensory experience and significantly enhances the professionalism and technical content of the overall performance.

[0033] The present invention's data-analysis-based lighting and sound control system includes comprehensive analysis and multi-level processing of audio data to achieve a precise match between musical rhythm, dynamic lighting, and volume control. The overall steps are as follows: First, the system collects and preprocesses raw audio data. Using advanced digital signal processing algorithms, it filters out noise components in the data and extracts clean, real-time audio signal strength, thereby resolving the issue of unstable live sound effects caused by noise interference. Next, based on the extracted audio signal strength, the system dynamically adjusts the sound system's output volume to ensure it aligns with user needs and the on-site atmosphere, resolving the mismatch between sound and visual effects seen in traditional devices.

[0034] In order to achieve the function of changing the color of the lights in sync with the rhythm of the music, the system further analyzes the frequency characteristics of the audio data. Frequency characteristics are one of the core elements in audio information, covering the distribution characteristics of high and low frequencies, such as low-frequency drum beats, medium-frequency melodies, and high-frequency notes. Based on the precise capture and analysis of frequency characteristics, the system dynamically generates lighting color parameters that match the current music segment. For example, low-frequency drum beats are associated with red light or other warm colors, while high-frequency notes are mapped to blue light or cool-toned lights. In addition, these light displays will also achieve light and dark changes in conjunction with the strength of specific audio signals, enhancing the integrated audio-visual experience, thereby solving the problem of insufficient synchronization between light and shadow and music rhythm in traditional solutions.

[0035] Overall, the control system achieves the effect of audio-driven lighting from multiple dimensions, and uses scientific algorithms to optimize the overall coordination of sound and lighting, bringing revolutionary changes in user experience.

[0036] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A light-following sound control system based on data analysis, characterized in that: include: Audio signal processing module, used to filter the audio data for noise and extract the real-time audio signal strength; A volume control module, connected to the audio signal processing module, is used to control the volume according to the intensity of the real-time audio signal after noise filtering; Frequency analysis module, used to analyze the frequency characteristics of audio data to determine the corresponding light color parameters; A lighting control module, connected to the frequency analysis module, for adjusting the color display of the lights based on the lighting color parameters to achieve synchronization with the music rhythm; The environmental sound interference evaluation module is used to use external environmental noise to correct the signal-to-noise ratio in the main sound data and improve the robustness of the system.

2. The data analysis-based light-following sound control system according to claim 1, characterized in that: The method further comprises: filtering the audio data for noise and extracting the real-time audio signal strength. Apply a low-pass filter to the raw audio data to remove frequencies above Noise signal; Set the threshold of the filtered audio data signal ,in is a dynamic adjustment parameter with a range of [0.2, 0.5], is the average signal strength; When the real-time audio signal strength Meet the conditions , then the data point is retained as a valid signal; otherwise it is considered an invalid signal, and the data strength of the filtered valid signal is taken as the maximum value MaxSig for subsequent calculation of volume control.

3. The data analysis-based light-following sound control system according to claim 1, characterized in that: The step of adjusting the volume according to the intensity of the real-time audio signal after noise filtering further includes: Extracting signal strength by noise filtering , set the initial volume ,in is the scaling factor, which controls the sound loudness ratio. ; when Exceeding the maximum adjustable volume limit , then press Limit the output; otherwise, keep the original value unchanged; Output volume for each frame of data Apply weighted moving average algorithm for smoothing adjustment, the calculation method is; ,in is the previous frame value, is the weighting coefficient, the default value is 0.7; Output of the weighted moving average algorithm Perform bin mapping: Definition volume levels and ; set up Indicates the step increment of each level; if the current weighted volume , corresponding to Otherwise, the exception handling mechanism is triggered and the volume is set to the default middle level.

4. The data analysis-based light-following sound control system according to claim 2, characterized in that: The method of analyzing the frequency characteristics of the audio data by the frequency analysis module to determine the corresponding light color parameters includes: Decompose the noise-filtered sound data into multiple sub-bands , , and calculate the spectrum energy for each sub-band ,in is the amplitude spectrum; Calculating total power , and set the threshold ; Filter active sub-bands based on this threshold in The expression determines the color change rate and the correlation of the spectrum distribution. The parameter is the adaptive weight; if it exceeds , then mark this part as the dominant color gamut; Added delay compensation factor to the active main frequency band judgment rule ,in is the sampling rate differential, Express the delay window length difference parameter to improve synchronization issues; That is, whenever a frequency band is detected to exceed the threshold, the delay impact weight is increased. Bit.

5. The data analysis-based light-following sound control system according to claim 3, characterized in that: The lighting control module calculates the lighting color mapping relationship of the active dominant color range based on the sub-band as follows: against Color mapping function for the dominant area , indicating the color coordinates Relationship matrix with sub-band active status is the color table function, and They are all system optimization configurations; Among them When the display is turned on, it enters high-brightness enhanced display mode; At the same time, define the color switching smoothing rules .

6. The data analysis-based light-following sound control system according to claim 4, characterized in that: 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 areas K>ThresholdFreqBand, the advanced color mixing mode is activated. .

7. The data analysis-based light-following sound control system according to claim 5, characterized in that: The environmental sound interference evaluation module utilizes external environmental noise To correct the signal-to-noise ratio in the main sound data , which indirectly affects the accuracy of the linkage between music and light and shadow, and the correction term is the deviation correction amplitude.

8. The data analysis-based light-following sound control system according to claim 6, characterized in that: The system provides a method to dynamically update the frequency feature library to adapt to the needs of more complex music types, and uses a periodic learning method to adjust the formula ,in Generate error correction values ​​derived from historical data, is the weighted historical spectrum contribution.

9. The data analysis-based light-following sound control system according to claim 7, characterized in that: The system adds special lighting display logic for extreme high-frequency burst sounds and defines the mutation threshold If the detection result exceeds this mutation amount at a certain moment, a short flashing light warning action sequence will be triggered immediately to enhance the visual shock effect of the on-site experience.

10. A light-following sound system based on data analysis, using a light-following sound control system based on data analysis as claimed in any one of claims 1 to 9, characterized in that: A system self-check and optimization module is provided, which periodically performs function checks and performance evaluations on the audio signal processing module, volume control module, frequency analysis module, lighting control module, and environmental sound interference evaluation module; For the audio signal processing module, check whether the low-pass filter parameter settings are within a reasonable range, verify the noise filtering effect and the accuracy of real-time audio signal strength extraction. If the deviation exceeds 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 and check whether the calculation results of the weighted moving average algorithm meet expectations. If there is a sudden change in volume or a mismatch with the audio signal strength, adjust the weighting factor λ or scaling factor γ. For the frequency analysis module, check the stability of sub-band decomposition and the accuracy of spectrum energy calculation. If it is found that the dominant color gamut screening is inaccurate or the color change rate is abnormal, readjust the adaptive weight t or 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, 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 linkage between music and light shadows does not meet expectations, re-evaluate the impact of external environmental noise and adjust the relevant parameters of the deviation correction amplitude. At the same time, the module records the results of each inspection and optimization to form a system operation log.

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