Audio analysis control method for sound pickup atmosphere lamp and atmosphere lamp

Abstract

The present invention relates to the technical field of atmosphere lamp control, and discloses an audio analysis control method for a sound-collecting atmosphere lamp and an atmosphere lamp thereof, wherein the audio analysis control method for a sound-collecting atmosphere lamp comprises the atmosphere lamp collecting sound through a built-in sound receiving component, the sound collected by the sound receiving component includes music, the sound is analyzed and processed through audio analysis, the audio analysis comprises pre-processing the sound, and extracting the energy proportion of each frequency band of the sound by extracting the time domain features and the frequency domain features of the pre-processed sound, each of which includes a high-energy frequency band and a low-energy frequency band, and performing a moving average filter on the energy of the low-frequency band to generate an energy envelope. The present invention processes the collected music signal in real time through audio analysis to extract information such as the rhythm, frequency and intensity of the music. Audio analysis technology ensures that the lights can be highly synchronized with the music, thereby improving the user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of atmosphere lamp control, and in particular to an audio analysis control method for a sound pickup atmosphere lamp and the atmosphere lamp. Background Art

[0002] Ambient lighting is a decorative lighting system inside the car. It uses LED light sources to cast soft light on areas such as the dashboard, doors, and footwells, enhancing visual aesthetics and driving emotions while relieving driving fatigue. The color-changing principle is based on the use of RGB-LED three-primary color mixing technology. By adjusting the ratio of red / green / blue light, a spectrum of more than 256 colors is generated. It supports multi-mode switching such as static, breathing, and rhythmic. The control method includes manual adjustment through the central control screen or physical buttons to switch color / brightness, and intelligent linkage with music rhythm, driving mode, and air-conditioning temperature to achieve dynamic light and shadow interaction.

[0003] At present, the interior ambient lights of cars lack intelligent innovation. Currently, the interior ambient lights of cars are installed in areas such as doors and auxiliary dashboards, illuminating the interior of the car to provide ambient lighting effects, and cannot achieve higher intelligence. Summary of the Invention

[0004] The present invention provides an audio analysis control method for a sound-pickup atmosphere lamp and an atmosphere lamp, which have the beneficial effect of enabling the light to be highly synchronized with the music, and solves the problem mentioned in the above background technology that the existing in-car atmosphere lamps are all installed in areas such as doors and auxiliary instrument panels, irradiating light into the car to provide an atmosphere lighting effect, but cannot achieve higher intelligence.

[0005] The present invention provides the following technical solution: an audio analysis control method for a sound pickup atmosphere lamp, comprising the following steps:

[0006] The ambient light collects sound through the built-in radio component;

[0007] The sounds collected by the sound receiving component include music;

[0008] Analyzing and processing the sound through audio analysis, wherein the audio analysis includes preprocessing the sound and extracting the energy proportion of each frequency band of the sound by extracting the time domain features and the frequency domain features of the preprocessed sound;

[0009] Each of the frequency bands includes a high-energy frequency band and a low-energy frequency band, performing a moving average filter on the low-energy frequency band to generate an energy envelope, generating a dynamic value based on historical energy statistics, and determining a peak point based on the dynamic value as a candidate beat point;

[0010] The autocorrelation method is used to calculate the energy envelope sequence period, predict the current BPM value, and confirm the final beat point timestamp based on the peak intensity;

[0011] The fundamental frequency of audio is detected using harmonic product spectrum or autocorrelation function, and the continuous fundamental frequency change is converted into a discrete note sequence to generate musical elements;

[0012] Dynamically adjusting the atmosphere light in real time synchronously with the real-time changing music elements;

[0013] Using audio optimization to perform targeted noise reduction and enhancement on the collected sound to obtain modified music elements;

[0014] The modified music element is linked to the lighting element of the atmosphere light.

[0015] As an optional solution of the audio analysis control method and atmosphere lamp of the present invention, the pre-processing sound includes:

[0016] Set the analog audio signal sampling rate and bit width, and remove sounds with lower sampling rate and bit width;

[0017] Use high-pass filter and low-pass filter to process the noise in the sound;

[0018] The time domain feature extraction includes:

[0019] Frame the sound and use window function calculation to reduce spectrum leakage;

[0020] Calculate the short-term energy of each frame of the sound signal and count the zero-crossing rate to assist in judging the onset of percussion music;

[0021] The frequency domain feature extraction includes:

[0022] Perform 1024-point FFT transformation on the sound frame signal to obtain spectrum information, divide it into several key frequency bands, and calculate the energy proportion of each frequency band;

[0023] Calculate the spectrum centroid to represent the brightness of the sound.

[0024] As an optional solution of the audio analysis control method and atmosphere lamp of the present invention, the audio synchronization method includes:

[0025] By associating music elements with mood lighting parameters;

[0026] Set the rhythm threshold, frequency threshold, melody threshold and BPM threshold. When the music elements meet the rhythm threshold, frequency threshold, melody threshold and BPM threshold, adjust the lighting parameters of the corresponding threshold in real time.

[0027] The atmosphere lamp adopts a crystal lampshade, and uses an algorithm to increase brightness compensation and adjust the light effect of crystal scattering through the refraction characteristics of the crystal lampshade.

[0028] As an optional solution of the audio analysis control method and atmosphere lamp of the present invention, the audio optimization method includes:

[0029] When the music elements are in the intermission period, the ambient noise spectrum is analyzed by FFT, and the noise received by the sound receiving component is smoothed by spectral subtraction and Wiener filtering;

[0030] Processing of musical elements through AGC control and DRC compression;

[0031] Setting a low-frequency range, when the frequency of the musical element is in the low-frequency range, increasing the decibel level to enhance the energy of the musical element;

[0032] Continuously monitoring the energy of the silent segment through the sound receiving component;

[0033] Set noise threshold;

[0034] When the noise is greater than the set noise threshold, increase the noise reduction factor;

[0035] When the noise level is lower than the set noise threshold, processing is reduced to preserve music details.

[0036] As an optional solution of the audio analysis control method and the atmosphere lamp of the present invention, the following steps are also included:

[0037] Acquire song information based on the music elements and determine the song type;

[0038] A song type duration threshold is set, and when the duration of the same type of songs in the sound collected by the sound receiving component is equal to the song type duration threshold, the current preferred song type is determined;

[0039] The sounds collected by the sound receiving component include historical conversations between people and current conversations between people;

[0040] Establish personnel files, collect historical personnel conversations through the audio receiving component and classify them into personnel files;

[0041] The sound receiving component identifies the current conversation and classifies it according to the historical conversations;

[0042] The current preferred song type is combined with the determination of the current human conversation classification to optimize the prediction of the human body state.

[0043] As an optional solution of the audio analysis control method and the atmosphere lamp of the present invention, the following steps are also included:

[0044] Obtain vehicle operation information;

[0045] Determining a driving state by combining the vehicle operation information with the predicted human body state;

[0046] Establishing several adjustment plans, including lighting plans and voice plans;

[0047] According to the driving state, corresponding lighting solutions and voice solutions are executed to induce psychological resonance of the person.

[0048] As an optional solution of the audio analysis control method and the atmosphere lamp of the present invention, the following steps are also included:

[0049] Acquire a vehicle operation route, and acquire environment change information by combining the vehicle operation information with the vehicle operation route;

[0050] Setting a regulation node, and adjusting the regulation node in real time according to the environmental change information;

[0051] The lighting elements are adjusted according to the adjustment node.

[0052] As an optional solution of the audio analysis control method and atmosphere lamp of the present invention, the personnel file includes human body information data;

[0053] A human body light change threshold is set according to the human body information data, and the light element change amplitude is smaller than the human body light change threshold;

[0054] The human body information data is adjusted through the human body state prediction to optimize the human body light change threshold.

[0055] As an optional solution of the audio analysis control method and the atmosphere lamp of the present invention, the following steps are also included:

[0056] Scan the driver's sitting posture and calculate the distance and angle between the ambient light and the driver's eyes;

[0057] The lighting angle and intensity of the lamp beads in the atmosphere light are adjusted according to the human body information data and the distance and angle between the atmosphere light and the eyes of the person.

[0058] A processing atmosphere lamp using an audio analysis control method for a sound pickup atmosphere lamp comprises:

[0059] lamp housing;

[0060] A battery and a magnet, wherein the battery and the magnet are installed inside the lamp housing;

[0061] A PCB board is installed inside the lamp housing and located above the battery and the magnet. The battery is used to supply power to the PCB board.

[0062] A light-distributing film is provided on the upper end of the PCB board. The light-distributing film is used to diffuse the light source. A light bracket is also provided on the outer surface of the light-distributing film. The light bracket is used to fix and limit the light-distributing film, the light bracket and the PCB board. The lower end of the light bracket is snapped into the interior of the lamp housing.

[0063] A crystal mask, the crystal mask being mounted on the upper end surface of the lamp housing;

[0064] The bracket has a patch installed on its upper end surface, the lamp housing and the bracket are connected via the patch, and a film is adhered to the lower end of the bracket, and the lamp housing is fixedly installed in the car using the film.

[0065] The present invention has the following beneficial effects:

[0066] 1. This audio analysis control method and ambient light for sound-collecting ambient lighting processes collected music signals in real time through audio analysis, extracting information such as the music's rhythm, frequency, and intensity. This audio analysis technology ensures that the lighting is highly synchronized with the music, enhancing the user experience.

[0067] 2. The audio analysis control method and atmosphere light of the crystal sound pickup atmosphere light match the analyzed audio information with the lighting effect through an audio synchronization method, ensuring that the lighting can respond to changes in the audio rhythm in real time, bringing users an immersive audio-visual experience.

[0068] 3. The audio analysis control method and ambient light for this sound-collecting atmosphere light utilize audio optimization methods to reduce noise and enhance the collected audio signals, ensuring the accuracy and stability of audio analysis. This audio optimization technology enhances product performance and ensures high synchronization between lighting and audio. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is a flow chart of the audio analysis control method of the present invention.

[0070] Figure 2 Schematic diagram of the structure of the atmosphere lamp of the present invention.

[0071] In the picture: 1. Lamp housing; 2. Battery; 3. Magnet; 4. PCB board; 5. Light bracket; 6. Light uniformity film; 7. Crystal mask; 8. Bracket; 9. SMD; 10. Film. DETAILED DESCRIPTION

[0072] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0073] Example 1

[0074] See also Figure 1 , wherein an audio analysis control method for a sound pickup atmosphere lamp comprises the following steps:

[0075] The ambient light collects sound through the built-in radio component;

[0076] The sounds collected by the radio component include music;

[0077] The sound is analyzed and processed through audio analysis. Audio analysis includes preprocessing the sound and extracting the energy proportion of each frequency band of the sound through time domain feature extraction and frequency domain feature extraction.

[0078] Each frequency band includes a high-energy band and a low-energy band. The low-energy band is subjected to moving average filtering to generate an energy envelope. A dynamic value is generated based on the historical energy statistics. The peak point is determined by the dynamic value and used as a candidate beat point.

[0079] The autocorrelation method is used to calculate the energy envelope sequence period, predict the current BPM value, and confirm the final beat point timestamp based on the peak intensity;

[0080] The fundamental frequency of audio is detected using harmonic product spectrum or autocorrelation function, and the continuous fundamental frequency change is converted into a discrete note sequence to generate musical elements;

[0081] Use real-time changing music elements to dynamically adjust the atmosphere lights in real time;

[0082] Use audio optimization to perform targeted noise reduction and enhancement on the collected sound to obtain modified musical elements;

[0083] Link the modified music elements with the lighting elements of the atmosphere light.

[0084] The sound receiving components include a microphone input device built into the ambient light;

[0085] The microphone input device collects the sounds inside the car in real time, including music, conversations, etc.

[0086] First, the sound is preprocessed. The analog audio signal is digitized using an ADC with a sampling rate of ≥44.1kHz and a bit width of ≥16 bits. A high-pass filter (>50Hz) is used to remove low-frequency noise, and a low-pass filter (<20kHz) is used to limit high-frequency noise. The digital signal is framed with a frame length of 20-50ms (e.g., 40ms) and a 50% overlap rate. A Hanning window is used to reduce spectral leakage.

[0087] Among them, the Hanning window is a commonly used window function in signal processing. It is a type of raised cosine window and is mainly used to reduce spectrum leakage in spectrum analysis.

[0088] It should be noted that the discrete-time expression of the Hanning window is: for a window function of length N, in the range of sequence n from 0 to N-1, the window value w(n) of each point is equal to 0.5 minus 0.5 times 2π times the cosine of n divided by N-1.

[0089] The pre-processed sound is subjected to time domain feature extraction and frequency domain feature extraction to obtain the energy proportion of each frequency band of the sound. Among them, time domain feature extraction is to calculate the short-time energy of each frame signal. The short-time energy includes the average value or RMS, which is used for lighting brightness synchronization and statistical zero-crossing rate to assist in judging the percussion sound head. Among them, frequency domain feature extraction is to perform a 1024-point FFT transform on the framed signal to obtain spectrum information and divide it into 7 key frequency bands, such as Sub-Bass20-60Hz, Briiance>6kHz, so as to obtain the energy proportion of each frequency band, and dynamically adjust the FFT window length according to the audio type. For example, electronic music uses a short window to improve rhythm resolution, and classical music uses a long window to retain melody details. The centroid of the spectrum is calculated to represent the "brightness" of the sound, which is used for light color emotional mapping;

[0090] The formula for the spectrum centroid is: The numerator is the sum of the amplitudes or energies of all the frequency components, multiplied by their corresponding amplitudes or energies, and then the sum of these products. The denominator is the sum of the amplitudes or energies of all the frequency components. The sum of the numerators is divided by the sum of the denominators to obtain the value of the spectrum centroid, which is expressed in Hertz.

[0091] Then, based on the energy proportions of each frequency band, a moving average filter is applied to the low-frequency energy to generate an energy envelope. The peak points are then detected using a dynamic threshold, which is used as candidate beat points. The dynamic threshold detection peak points are selected based on historical energy statistics.

[0092] The autocorrelation method is used to calculate the energy envelope sequence period to predict the current BPM value. The peak intensity is combined to confirm the final beat point timestamp. The energy envelope dynamic threshold peak detection and autocorrelation BPM tracking are combined to solve the beat recognition problem of complex rhythm music.

[0093] The energy envelope is calculated by framing the signal and summing the squares of all sampling points within each frame to obtain an energy sequence reflecting signal strength variations. For example, the audio signal is segmented and the squares of all data points within each segment are summed to obtain an energy curve. The autocorrelation function is calculated by using a Fast Fourier Transform (FFT) to calculate the spectrum of the energy sequence, squaring the spectral amplitude, and then performing an inverse transform to obtain an autocorrelation sequence reflecting the signal's periodicity. For example, the energy curve is converted into a spectrum, the spectral intensity is squared, and then converted back to the time domain to obtain a periodic characteristic curve. On the autocorrelation curve, the location of the first significant peak is found, excluding the zero-delay point. The delay time corresponding to this location is the signal's period. For example, on a periodic curve, the time interval between the first significant peak is the beat period. BPM is converted to beats per minute by dividing 60 seconds by the number of seconds of the period. For example, if a detected period of 0.5 seconds is found, then there are 120 beats per minute: 60 ÷ 0.5.

[0094] Using the Harmonic Product Spectrum (HPS) or Autocorrelation Function (ACF) to detect the audio fundamental frequency (F0), the continuous fundamental frequency changes are converted into a discrete note sequence, thereby obtaining musical elements, including melody, rhythm, harmony, timbre, dynamics, speed, mode and form;

[0095] It's important to note that the Harmonic Product Spectrum (HPS) detects the audio fundamental frequency (F0) by compressing the original spectrum by integer multiples, such as 2 or 3. This is equivalent to "folding" the high-frequency harmonics into the low-frequency region. For example, every two points in the spectrum are combined into one point to form a new compressed spectrum. The original spectrum is multiplied point by point with all the compressed spectra. This strengthens the locations where the fundamental frequency and harmonics overlap, while weakening other frequency components. For example, after compression, the 100Hz, 200Hz, and 300Hz harmonics in the original spectrum are all aligned at 100Hz. The frequency point with the strongest energy in the final product spectrum is found; this location is the fundamental frequency. For example, the product spectrum has a peak at 262Hz, which is determined to be the fundamental frequency of middle C. The actual fundamental frequency value is calculated based on the peak position and sampling parameters. For example, if the peak is at the 88th frequency point and the sampling rate is 44.1kHz, then the fundamental frequency = 88 × (44100 / 1024) ≈ 379Hz.

[0096] It's important to note that the autocorrelation function (ACF) detects the audio fundamental frequency (F0) by multiplying the audio signal by a delayed copy of itself, point by point, and then summing the results. The value at each time point is multiplied by the value at the corresponding point after a delay of τ. All these products are then summed. The autocorrelation result is searched for the first significant peak where τ = 0, excluding zero delay. The delay τ corresponding to this peak is the pitch period. For example, if a peak occurs at τ = 5ms, the fundamental frequency F0 = 1 / 0.005 = 200Hz. The detected pitch period T0 is converted to frequency: F0 = 1 / T0. For example, if the measured period is 0.01 seconds, the fundamental frequency is 100Hz.

[0097] By associating the acquired music elements with the ambient light, the light can be highly synchronized with the music, thus enhancing the user experience.

[0098] Audio synchronization methods include:

[0099] By associating music elements with mood lighting parameters;

[0100] Set the rhythm threshold, frequency threshold, melody threshold and BPM threshold. When the music elements meet the rhythm threshold, frequency threshold, melody threshold and BPM threshold, adjust the lighting parameters of the corresponding threshold in real time.

[0101] The atmosphere light uses a crystal lampshade, which uses an algorithm to increase brightness compensation and adjust the light effect of crystal scattering through the refractive characteristics of the crystal lampshade.

[0102] The domestically produced WNF178 chip is used as the main MCU, DMA is used to directly access memory and transfer data, and the audio processing tasks are scheduled through the RTOS real-time operating system to avoid delays. A custom control protocol is used to control the LED driver chip through PWM signals to reduce delays and ensure audio and light synchronization.

[0103] The rhythm threshold is associated with the brightness mapping. Strong beats trigger the light to be high (PWM duty cycle 100%), weak beats correspond to 30%-50% brightness pulses, and the response time is 5-10ms.

[0104] Frequency thresholds are associated with color mapping, with low frequencies (<250Hz) mapped to red / orange, mid-range frequencies (250Hz-4kHz) mapped to green / yellow, and high frequencies (>4kHz) mapped to blue / purple, with RGB values ​​mixed by the energy ratio of the frequency bands;

[0105] The melody threshold is associated with the dynamic effect. An ascending melody drives the light to flow upward (at a speed of 5-10 cms), a descending melody corresponds to a downward flow, and a steady melody triggers a color gradient.

[0106] The BPM threshold is linked to the tempo, automatically adjusting the light breathing rate based on the current BPM (e.g. 120 BPM corresponds to 2 breaths / second).

[0107] When musical elements meet the rhythm threshold, frequency threshold, melody threshold, and BPM threshold, the lighting parameters corresponding to the threshold are adjusted in real time. Through experimentally verified frequency-color correspondences, such as low-frequency warm tones and high-frequency cool tones, the accuracy of emotional synchronization is improved. In this way, the analyzed audio information is matched with the lighting effects, ensuring that the lighting can respond to changes in audio rhythm in real time, bringing users an immersive audio-visual experience.

[0108] Furthermore, because the ambient light used in the control method uses a crystal lampshade, the refractive properties of the crystal lampshade are utilized to add a brightness compensation coefficient to the mapping algorithm. For example, the brightness of the edge area is increased by 20% to avoid glare and enhance the refractive effect. The light color is optimized through a color mixing algorithm, and the scattering properties of the crystal are used to achieve a softer gradient transition for the RGB lighting effect. By pre-measuring the crystal refraction parameters, the output values ​​of each LED channel are dynamically adjusted to achieve distortion-free light effect mapping.

[0109] It should be noted that the mapping algorithm includes output brightness = [logarithm with base (1 + compensation coefficient x input brightness)] - [logarithm with base (1 + compensation coefficient)]. The larger the compensation coefficient, the more obvious the brightness improvement. Gaussian blur is used to separate the illumination layer of the image, and then the compensation coefficient is set according to the average brightness of each small area. For example:

[0110] The dark area compensation coefficient is automatically increased (e.g. x1.5);

[0111] The bright area compensation coefficient is automatically reduced (e.g. x0.7 times).

[0112] Audio optimization methods include:

[0113] When the music elements are in the intermission period, the ambient noise spectrum is analyzed by FFT, and the noise received by the sound receiving component is smoothed by spectral subtraction and Wiener filtering;

[0114] Processing of musical elements through AGC control and DRC compression;

[0115] Set the low-frequency range. When the frequency of a musical element is in the low-frequency range, increase the decibel level to enhance the energy of the musical element.

[0116] Continuously monitor the energy of the silent segment through the radio receiver;

[0117] Set noise threshold;

[0118] When the noise is greater than the set noise threshold, increase the noise reduction factor;

[0119] When the noise level is lower than the set noise threshold, processing is reduced to preserve music details.

[0120] The spectral subtraction formula is:

[0121] |Y(f)|=max(|X(f)|²-α*|N(f)|²,0)^0.5;

[0122] α is the over-reduction factor, α=1.5;

[0123] N(f) is the noise amplitude spectrum value;

[0124] X(f) is the amplitude spectrum value of the noisy signal;

[0125] Through Wiener filtering and smoothing, the noise spectrum is dynamically updated to adapt to environmental changes, such as sudden changes in fan noise;

[0126] Wiener filtering is a filtering process where the estimated value of the filtered signal is equal to the input signal spectrum multiplied by a weighting function related to the signal-to-noise ratio. This weighting function enhances high signal-to-noise ratio bands and suppresses low signal-to-noise ratio bands. In the frequency domain, the Wiener filter can be expressed as an output signal spectrum equal to the input signal spectrum multiplied by a coefficient. This coefficient is the clean signal power spectrum divided by the sum of the clean signal power spectrum and the noise power spectrum, where:

[0127] The numerator part represents the power spectrum of the pure signal;

[0128] The denominator is the sum of the power spectra of the signal and the noise;

[0129] When the signal-to-noise ratio is high, the coefficient is close to 1 and the signal is basically preserved;

[0130] When the signal-to-noise ratio is low, the coefficient approaches 0 and the noise is greatly suppressed;

[0131] Processing of musical elements through AGC control and DRC compression;

[0132] Among them, AGC control is to calculate the RMS value of the input signal. If it is lower than -20dB, the gain is amplified (such as 6dB), and if it exceeds 0dB, the gain is attenuated (such as -3dB). The attack time is 10ms and the release time is 500ms.

[0133] DRC compression sets the compression threshold to -10dB and the compression ratio to 4:1. It dynamically compresses signals that exceed the threshold, improving the detectability of weak rhythmic components (such as shaker sounds).

[0134] The 20-250Hz low-frequency band is equalized by 5-8dB to enhance the energy significance of rhythm instruments such as bass and kick drum. Rhythm detection sensitivity is optimized, and the energy of silent segments is continuously monitored. When the noise level is >30dB, the noise reduction factor is automatically increased, with its a value increasing from 1.5 to 2.0. When the noise level is <20dB, processing is reduced to preserve musical details. By continuously monitoring changes in ambient noise and updating the noise model every 500ms, the poor adaptability of traditional spectral subtraction to time-varying noise is addressed. To meet the needs of lighting synchronization, rhythm-related frequency bands are selectively enhanced instead of global equalization to improve analysis efficiency.

[0135] In summary, the collected audio signals are subjected to noise reduction and enhancement processing to ensure the accuracy and stability of audio analysis.

[0136] Example 2

[0137] This embodiment is an improvement made on the basis of embodiment 1. For details, please refer to Figure 1 , further comprising the following steps:

[0138] Obtain song information based on music elements and determine the song type;

[0139] Set a song type duration threshold. When the duration of songs of the same type collected by the sound receiving component is equal to the song type duration threshold, the current preferred song type is determined.

[0140] The sounds collected by the sound receiving component include historical conversations with people and current conversations with people;

[0141] Establish personnel files, collect historical personnel conversations through the audio receiving component and classify them into personnel files;

[0142] The audio receiving component identifies the current conversation and classifies it according to the historical conversations;

[0143] The current preferred song type is combined with the current person conversation classification to optimize the prediction of human body state.

[0144] Determine song information based on the identified musical elements and determine the song genre, such as major categories such as pop, rock, jazz, classical, electronic, poly-village, and hip-hop;

[0145] Determine whether the song is happy or sad based on the song type;

[0146] Happy-style songs typically feature upbeat melodies and lyrics that bring joy and excitement to the listener. These songs often use upbeat beats, cheerful melodies, and inspiring lyrics, aiming to convey positive energy and optimism. Popular music, rock music, and electronic dance music are all examples of happy-style songs.

[0147] Melancholic songs often feature deep, melancholic melodies and lyrics that are deeply moving and express inner sorrow and longing. These songs often use slow tempos, melancholic melodies, and moving lyrics designed to resonate with the audience. Classical music, blues, and country music are all examples of these songs.

[0148] It should be noted that when the sound receiving component continuously collects songs of the same type for a duration equal to or greater than the song type duration threshold, the current preferred song type is determined. For example, the song type duration threshold is set to 8 minutes. When the sound receiving component continuously collects 8 minutes of happy-style songs, it is determined to be a happy-style song type. This determines that the driver's mood is high, thereby optimizing the frequency-color correspondence verified by the experiment in Example 2, such as low-frequency warm tones and high-frequency cool tones, improving the accuracy of emotional synchronization, ensuring that the lights can respond to changes in audio rhythm in real time, and bringing an immersive audio-visual experience to users.

[0149] Furthermore, the sound receiving component is also used to collect and store personnel conversations and create personnel files based on the sound. Among them, the personnel's language fluctuations can determine the current personnel's emotions, specifically,

[0150] Pitch: Pitch usually rises when excited, angry, or fearful; pitch usually falls when sad, tired, or relaxed.

[0151] Speech speed: When excited, anxious, or angry, speech speed usually increases; when sad, depressed, thinking, or trying to express complex content, speech speed usually slows down;

[0152] Volume: When you are angry, happy, or excited, the volume usually increases; when you are sad, ashamed, or whispering, the volume usually decreases.

[0153] Sound quality:

[0154] Tension (e.g., anxiety, anger): Voice sounds tense, sharp, or hoarse;

[0155] Relaxed (e.g., content, calm): Voice sounds mellow and smooth;

[0156] Trembling (e.g. fear, extreme sadness): the voice has a noticeable tremor;

[0157] Breathy (e.g. tired, sad, sexy): The voice contains more exhalation sounds;

[0158] Intonation / Prosody: Emotions strongly influence the melodic patterns of speech;

[0159] Excited, surprised: the tone of voice fluctuates more;

[0160] Frustrated, bored: the tone is flat and monotonous;

[0161] Sarcasm, suspicion: specific intonation patterns;

[0162] Pauses and Fluency: Anxiety may lead to more hesitation, repetition, and stuttering; extreme sadness may lead to long pauses or choppy speech; anger may lead to fewer pauses or a rapid outburst of speech.

[0163] Through long-term recording, we can comprehensively judge whether the language and emotions of people are linked. Then, when the sound emitted by people is collected and analyzed by the sound receiving component, we can predict the current state of people by looking for and comparing the emotions corresponding to the language in the people's files. In this way, we can further optimize the prediction of human body state by combining the current preferred song type with the determination of the current person's conversation classification, so that the flashing of the atmosphere light can improve the accuracy of emotional synchronization and put people in the same emotional range, thereby bringing excellent use effect.

[0164] Example 3

[0165] This embodiment is an improvement made on the basis of embodiment 2. For details, please refer to Figure 1 , further comprising the following steps:

[0166] Obtain vehicle operation information;

[0167] Determine driving status by combining vehicle operation information with predicted human body status;

[0168] Establish several adjustment plans, including lighting and voice plans;

[0169] Execute corresponding lighting and voice plans according to the driving status to induce psychological resonance in people.

[0170] The ambient light is equipped with GPS to obtain the vehicle's speed and determine the current driving state based on the predicted driver's emotions. The driving state includes normal state, fatigue state, alcohol-affected state, impatient state, aggressive state, etc.

[0171] For example, if the driver is currently in an excited mood and the vehicle's speed approaches or exceeds the road speed limit several times, it indicates that the driver is currently driving in an aggressive psychological state. The adjustment plan records the color of the light and voice broadcast indicating the aggressive psychological state, so that the driver is reminded of the red light warning through the ambient light and the alarm is issued through the voice broadcast information, allowing the driver to gradually switch from aggressive driving to normal driving. In this way, the corresponding lighting plan and voice plan are executed through the driving state to induce psychological resonance in the person, thereby improving driving safety.

[0172] The following steps are also included:

[0173] Obtain vehicle operation routes, and combine vehicle operation information with vehicle operation routes to obtain environmental change information;

[0174] Set the adjustment node and adjust the adjustment node in real time based on the environment change information;

[0175] Adjust lighting elements based on adjustment nodes.

[0176] The vehicle route is determined by obtaining the current driving route and the destination name recorded by the radio component through GPS. When changes to the external natural light such as bridge holes, tunnels, and underground parking entrances and exits are involved, the determined vehicle route is marked in advance, and the time node of the natural light environment change is determined according to the current vehicle speed and the waiting time for the red light. When the vehicle reaches a position where the external natural light is changed such as a bridge hole, tunnel, and underground parking entrance and exit, and corresponds to the time node, the ambient light is adjusted in advance. For example, the light intensity of the ambient light is adjusted to reduce the impact of the strong ambient light on the driver, thereby improving the use effect and adapting the ambient light to the vehicle operation through continuously adjusted ambient lights.

[0177] Personnel files include human body information data;

[0178] The human body light change threshold is set according to the human body information data, and the light element change amplitude is smaller than the human body light change threshold;

[0179] The human body information data is adjusted through human body state prediction to optimize the human body light change threshold.

[0180] The following steps are also included:

[0181] Scan the driver's sitting posture and calculate the distance and angle between the ambient light and the driver's eyes;

[0182] Adjust the lighting angle and intensity of the lamp beads in the ambient light according to the human body information data and the distance and angle between the ambient light and the person's eyes.

[0183] Example 4

[0184] An ambient light using an audio analysis control method for a sound pickup ambient light comprises:

[0185] Lamp housing 1;

[0186] The battery 2 and the magnet 3 are installed inside the lamp housing 1;

[0187] PCB board 4, which is installed inside the lamp housing 1 and located above the battery 2 and the magnet 3. The battery 2 is used to supply power to the PCB board 4;

[0188] The light-homogenizing film 6 is arranged on the upper end of the PCB board 4. The light-homogenizing film 6 is used to diffuse the light source. The outer surface of the light-homogenizing film 6 is also covered with a light bracket 5. The light bracket 5 is used to fix and limit the light-homogenizing film 6, the light bracket 5 and the PCB board 4. The lower end of the light bracket 5 is snapped into the interior of the lamp housing 1;

[0189] A crystal mask 7 is mounted on the upper end surface of the lamp housing 1;

[0190] The bracket 8 has a patch 9 installed on its upper end surface. The lamp housing 1 and the bracket 8 are connected via the patch 9. The lower end of the bracket 8 is adhered with a film 10. The film 10 is used to fix the lamp housing 1 in the car.

[0191] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0192] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. An audio analysis control method for a sound pickup atmosphere lamp, characterized in that: The following steps are involved: The ambient light collects sound through the built-in radio component; The sounds collected by the sound receiving component include music; Analyzing and processing the sound through audio analysis, wherein the audio analysis includes preprocessing the sound and extracting the energy proportion of each frequency band of the sound by extracting the time domain features and the frequency domain features of the preprocessed sound; Each of the frequency bands includes a high-energy frequency band and a low-energy frequency band, performing a moving average filter on the low-energy frequency band to generate an energy envelope, generating a dynamic value based on historical energy statistics, and determining a peak point based on the dynamic value as a candidate beat point; The autocorrelation method is used to calculate the energy envelope sequence period, predict the current BPM value, and confirm the final beat point timestamp based on the peak intensity; The fundamental frequency of audio is detected using harmonic product spectrum or autocorrelation function, and the continuous fundamental frequency change is converted into a discrete note sequence to generate musical elements; Dynamically adjusting the atmosphere light in real time synchronously with the real-time changing music elements; Using audio optimization to perform targeted noise reduction and enhancement on the collected sound to obtain modified music elements; The modified music element is linked to the lighting element of the atmosphere light.

2. The audio analysis control method of the sound pickup atmosphere lamp according to claim 1, characterized in that: The pre-processing sound includes: Set the analog audio signal sampling rate and bit width, and remove sounds with lower sampling rate and bit width; Use high-pass filter and low-pass filter to process the noise in the sound; The time domain feature extraction includes: Frame the sound and use window function calculation to reduce spectrum leakage; Calculate the short-term energy of each frame of the sound signal and count the zero-crossing rate to assist in judging the onset of percussion music; The frequency domain feature extraction includes: Perform 1024-point FFT transformation on the sound frame signal to obtain spectrum information, divide it into several key frequency bands, and calculate the energy proportion of each frequency band; Calculate the spectrum centroid to represent the brightness of the sound.

3. The audio analysis control method of the sound pickup atmosphere lamp according to claim 2, characterized in that: The audio synchronization method comprises: By associating music elements with mood lighting parameters; Set the rhythm threshold, frequency threshold, melody threshold and BPM threshold. When the music elements meet the rhythm threshold, frequency threshold, melody threshold and BPM threshold, adjust the lighting parameters of the corresponding threshold in real time. The atmosphere lamp adopts a crystal lampshade, and uses an algorithm to increase brightness compensation and adjust the light effect of crystal scattering through the refraction characteristics of the crystal lampshade.

4. The audio analysis control method of the sound pickup atmosphere lamp according to claim 3, characterized in that: The audio optimization method comprises: When the music elements are in the intermission period, the ambient noise spectrum is analyzed by FFT, and the noise received by the sound receiving component is smoothed by spectral subtraction and Wiener filtering; Processing of musical elements through AGC control and DRC compression; Setting a low-frequency range, when the frequency of the musical element is in the low-frequency range, increasing the decibel level to enhance the energy of the musical element; Continuously monitoring the energy of the silent segment through the sound receiving component; Set noise threshold; When the noise is greater than the set noise threshold, increase the noise reduction factor; When the noise level is lower than the set noise threshold, processing is reduced to preserve music details.

5. The audio analysis control method of the sound pickup atmosphere lamp according to claim 4, characterized in that: The following steps are also included: Acquire song information based on the music elements and determine the song type; A song type duration threshold is set, and when the duration of the same type of songs in the sound collected by the sound receiving component is equal to the song type duration threshold, the current preferred song type is determined; The sounds collected by the sound receiving component include historical conversations between people and current conversations between people; Establish personnel files, collect historical personnel conversations through the audio receiving component and classify them into personnel files; The sound receiving component identifies the current conversation and classifies it according to the historical conversations; The current preferred song type is combined with the determination of the current human conversation classification to optimize the prediction of the human body state.

6. The audio analysis control method of the sound pickup atmosphere lamp according to claim 5, characterized in that: The following steps are also included: Obtain vehicle operation information; Determining a driving state by combining the vehicle operation information with the predicted human body state; Establishing several adjustment plans, including lighting plans and voice plans; According to the driving state, corresponding lighting solutions and voice solutions are executed to induce psychological resonance of the person.

7. The audio analysis control method of the sound pickup atmosphere lamp according to claim 6, characterized in that: The following steps are also included: Acquire a vehicle operation route, and acquire environment change information by combining the vehicle operation information with the vehicle operation route; Setting a regulation node, and adjusting the regulation node in real time according to the environmental change information; Adjust the lighting elements according to the adjustment node.

8. The audio analysis control method of the sound pickup atmosphere lamp according to claim 7, characterized in that: The personnel file includes human body information data; A human body light change threshold is set according to the human body information data, and the light element change amplitude is smaller than the human body light change threshold; The human body information data is adjusted through the human body state prediction to optimize the human body light change threshold.

9. The audio analysis control method of the sound pickup atmosphere lamp according to claim 8, characterized in that: The following steps are also included: Scan the driver's sitting posture and calculate the distance and angle between the ambient light and the driver's eyes; The lighting angle and intensity of the lamp beads in the atmosphere light are adjusted according to the human body information data and the distance and angle between the atmosphere light and the eyes of the person.

10. An atmosphere lamp using the audio analysis control method of a sound pickup atmosphere lamp according to any one of claims 1 to 9, characterized in that: include: Lamp housing (1); A battery (2) and a magnet (3), wherein the battery (2) and the magnet (3) are installed inside the lamp housing (1); A PCB board (4), the PCB board (4) being mounted inside the lamp housing (1) and located above the battery (2) and the magnet (3), the battery (2) being used to supply power to the PCB board (4); A light-uniform film (6), the light-uniform film (6) is arranged on the upper end of the PCB board (4), the light-uniform film (6) is used to diffuse the light source, the outer surface of the light-uniform film (6) is also provided with a light bracket (5), the light bracket (5) is used to fix and limit the light-uniform film (6), the light bracket (5) and the PCB board (4), and the lower end of the light bracket (5) is snapped into the interior of the lamp housing (1); A crystal mask (7), wherein the crystal mask (7) is mounted on the upper end surface of the lamp housing (1); A bracket (8) is provided with a patch (9) on the upper end surface of the bracket (8), the lamp housing (1) and the bracket (8) are connected via the patch (9), and a film (10) is adhered to the lower end of the bracket (8), and the lamp housing (1) is fixedly installed in the vehicle using the film (10).

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