Dynamic bass enhancement method and system for a bluetooth device

Abstract

The application relates to the field of Bluetooth technology and discloses a dynamic bass enhancement method and system of a Bluetooth device, which comprises the following steps: separating a complex tone signal component and a pure tone signal component from an audio signal to calculate a harmonic proportion attenuation factor of the audio signal; determining an auditory transmission distance between the Bluetooth device and a listener, calculating a low-frequency attenuation amount of the audio signal in a transmission process; calculating a bass perceived loudness of the listener and obtaining a target bass enhancement intensity of the listener; determining a harmonic balance equivalent of an output sound field of the Bluetooth device, calculating an effective bass enhancement amount of the Bluetooth device; and performing bass enhancement processing on the audio signal based on the effective bass enhancement amount and the target bass enhancement intensity to obtain an enhanced audio signal. The application can improve the dynamic bass enhancement effect of the Bluetooth device.

Description

Technical Field

[0001] This invention relates to a dynamic bass enhancement method and system for Bluetooth devices, belonging to the field of Bluetooth technology. Background Technology

[0002] As a widely used audio playback medium, the bass performance of Bluetooth devices directly determines the user's listening experience and product competitiveness. Currently, most mainstream bass enhancement technologies adopt a static adjustment mode based on preset gain curves, which relies on fixed frequency response parameters and gain thresholds. This makes it difficult to adapt to the dynamic differences in the harmonic structure of different audio signal sources and the real-time changes in the acoustic characteristics of the listening environment.

[0003] In actual playback, due to the rigid fixed enhancement parameters and the lack of accurate adaptation to signal characteristics and auditory perception, the bass enhancement effect is poor, resulting in a lack of bass power or over-enhancement, causing harmonic distortion, muddy sound, and even damage to speaker units. It cannot meet the user's demand for high-quality bass, and it is easy to cause auditory fatigue due to sound field imbalance, thus reducing the effect of bass enhancement. Summary of the Invention

[0004] This invention provides a method and system for dynamic bass enhancement in Bluetooth devices, the main purpose of which is to improve the dynamic bass enhancement effect of Bluetooth devices.

[0005] To achieve the above objectives, the present invention provides a dynamic bass enhancement method for a Bluetooth device, comprising: The audio signal played by the Bluetooth device is collected, and the polyphonic signal component and the pure tone signal component are separated from the audio signal to calculate the harmonic ratio attenuation factor of the audio signal. Determine the audible transmission distance between the Bluetooth device and the listener, and in conjunction with the harmonic ratio attenuation factor, calculate the low-frequency attenuation of the audio signal during transmission; Based on the auditory transmission distance, the listener's perceived bass loudness is calculated, and the listener's target bass enhancement intensity is obtained; By combining the low-frequency attenuation and the perceived bass loudness, the harmonic balance equivalent of the output sound field of the Bluetooth device is determined. The harmonic balance equivalent is the amplitude matching coefficient between the harmonic components and the fundamental frequency components in the output sound field of the Bluetooth device. The effective bass enhancement of the Bluetooth device is calculated by combining the harmonic proportional attenuation factor. Based on the effective bass enhancement amount and the target bass enhancement intensity, bass enhancement processing is performed on the audio signal to obtain an enhanced audio signal.

[0006] Optionally, separating the polyphonic signal components and the pure tone signal components from the audio signal includes: The audio signal is decomposed in the frequency domain to obtain the energy distribution characteristics of different frequency bands; Identify the harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band within the energy distribution characteristics; Construct the distribution boundaries of the harmonic cluster and the fundamental frequency region in the time-frequency domain; Based on the distribution boundary, polyphonic signal components and pure tone signal components are separated from the audio signal.

[0007] Optionally, identifying the harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band within the energy distribution characteristics includes: Analyze the spectral peak distribution in the energy distribution characteristics to obtain significant harmonic components; Verify the harmonic sequence structure in the energy distribution characteristics to obtain the cluster continuity index; By combining the significant harmonic components and the cluster continuity index, the harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band in the energy distribution characteristics are identified.

[0008] Optionally, calculating the harmonic ratio attenuation factor of the audio signal by combining the polyphonic signal components and the pure tone signal components includes: The energy intensities corresponding to the polyphonic signal components and the pure tone signal components are measured respectively to obtain the polyphonic energy value and the pure tone energy value; The ratio of the polyphonic energy value to the pure tone energy value is calculated to obtain the real-time harmonic ratio; Analyze the dynamic change trend of the real-time harmonic ratio within a preset time window; Based on the aforementioned proportional relationship and the dynamic change trend, the harmonic ratio attenuation factor of the audio signal is calculated.

[0009] Optionally, determining the audible transmission distance between the Bluetooth device and the listener, in conjunction with the harmonic ratio attenuation factor, to calculate the low-frequency attenuation of the audio signal during transmission includes: Query the audio output power corresponding to the Bluetooth device and collect the signal frequency spectrum of the audio signal; Based on the frequency spectrum, the proportion of low-frequency harmonics corresponding to the audio signal is calculated; The low-frequency attenuation of the audio signal during transmission is calculated by combining the auditory transmission distance, the harmonic ratio attenuation factor, the audio output power, and the low-frequency harmonic ratio.

[0010] Optionally, calculating the low-frequency harmonic ratio corresponding to the audio signal based on the frequency spectrum includes: Divide the effective low-frequency bandwidth corresponding to the audio signal; Extract the spectral energy in the frequency spectrum that is associated with the effective low-frequency bandwidth; The ratio of the spectral energy to the total spectral energy of the frequency spectrum is calculated to obtain the low-frequency harmonic ratio of the audio signal.

[0011] Optionally, calculating the listener's perceived bass loudness based on the auditory transmission distance includes: Calculate the low-frequency energy concentration corresponding to the audio signal, and measure the ambient noise level corresponding to the listener; Based on the ambient noise level, the masking effect index of the listening environment in which the listener is located is calculated; The perceived loudness of bass frequencies is calculated by combining the low-frequency energy concentration, the masking effect index, and the auditory transmission distance.

[0012] Optionally, calculating the low-frequency energy concentration corresponding to the audio signal includes: The audio signal is decomposed by wavelet packet decomposition to obtain the low-frequency subband energy of different frequency bands; Analyze the energy statistical characteristics corresponding to the low-frequency subband energy to calculate the energy skewness and energy kurtosis of the low-frequency subband energy; By combining the energy skewness and the energy kurtosis, the low-frequency energy concentration corresponding to the audio signal is calculated.

[0013] Optionally, determining the harmonic balance equivalent of the Bluetooth device's output sound field by combining the low-frequency attenuation and the perceived bass loudness includes: Extract the harmonic energy and fundamental frequency energy of the sound field output by the Bluetooth device; Calculate the ratio between the harmonic energy and the fundamental frequency energy to obtain the harmonic-fundamental frequency ratio. By combining the low-frequency attenuation and the perceived bass loudness, the harmonic fundamental frequency ratio is corrected to determine the harmonic balance equivalent of the sound field output by the Bluetooth device.

[0014] To address the above problems, the present invention also provides a dynamic bass enhancement system for a Bluetooth device, the system comprising: The signal component analysis module is used to collect the audio signal played by the Bluetooth device and separate the polyphonic signal component and the pure tone signal component from the audio signal in order to calculate the harmonic ratio attenuation factor of the audio signal. The transmission attenuation calculation module is used to determine the audible transmission distance between the Bluetooth device and the listener, and to calculate the low-frequency attenuation of the audio signal during transmission by combining the harmonic ratio attenuation factor. The perceived loudness calculation module is used to calculate the bass perceived loudness of the listener based on the auditory transmission distance, and to obtain the target bass enhancement intensity of the listener. The bass enhancement calculation module is used to combine the low-frequency attenuation amount and the bass perceived loudness to determine the harmonic balance equivalent of the output sound field of the Bluetooth device. The harmonic balance equivalent is the amplitude matching coefficient between the harmonic components and the fundamental frequency components in the output sound field of the Bluetooth device. The module also combines the harmonic proportional attenuation factor to calculate the effective bass enhancement amount of the Bluetooth device. The bass enhancement processing module is used to perform bass enhancement processing on the audio signal based on the effective bass enhancement amount and the target bass enhancement intensity to obtain an enhanced audio signal.

[0015] Compared to the problems described in the background art, this invention, by separating the polyphonic signal components and pure tone signal components from the audio signal, can accurately analyze the composition of the audio signal, providing data support for the subsequent calculation of low-frequency attenuation during transmission. Then, by determining the audible transmission distance between the Bluetooth device and the listener, and combining this with the harmonic ratio attenuation factor, this invention can quantify the degree of energy loss in the low-frequency portion of the audio signal during transmission, providing an important reference for subsequent processing. Next, based on the audible transmission distance, this invention calculates the listener's perceived bass loudness, quantifying the listener's actual perceived intensity of bass in the actual listening environment. Afterwards… This invention, by combining the low-frequency attenuation amount with the perceived bass loudness to determine the harmonic balance equivalent, can quantitatively evaluate the sound quality balance of the output sound field. Furthermore, by combining the harmonic proportional attenuation factor to calculate the effective bass enhancement amount, it can accurately determine the optimal enhancement amplitude that compensates for auditory loss while maintaining sound quality purity, providing precise control for audio optimization. Finally, by performing bass enhancement processing based on the effective bass enhancement amount and the target bass enhancement intensity, this invention achieves precise bass effect enhancement while ensuring audio quality. This satisfies the user's auditory needs while avoiding audio distortion caused by excessive enhancement. Therefore, this invention can improve the dynamic bass enhancement effect of Bluetooth devices. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a dynamic bass enhancement method for a Bluetooth device according to an embodiment of the present invention. Figure 2 This is a schematic flowchart illustrating the signal separation process in a dynamic bass enhancement method for a Bluetooth device according to an embodiment of the present invention. Figure 3 This is a schematic diagram illustrating the identification process of energy distribution characteristics in a dynamic bass enhancement method for a Bluetooth device according to an embodiment of the present invention. Figure 4A schematic diagram of a module for implementing a dynamic bass enhancement method for a Bluetooth device according to an embodiment of the present invention; Figure 5 A schematic diagram of a computer device for a dynamic bass enhancement method for a Bluetooth device according to an embodiment of the present invention; The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0018] This application provides a dynamic bass enhancement method for a Bluetooth device. The execution entity of this dynamic bass enhancement method for a Bluetooth device includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the dynamic bass enhancement method for a Bluetooth device can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0019] Reference Figure 1 The diagram shown is a flowchart illustrating a dynamic bass enhancement method for a Bluetooth device according to an embodiment of the present invention. In this embodiment, the dynamic bass enhancement method for a Bluetooth device includes: S1. Acquire the audio signal played by the Bluetooth device, and separate the polyphonic signal component and the pure tone signal component from the audio signal to calculate the harmonic ratio attenuation factor of the audio signal.

[0020] This invention can accurately analyze the composition of an audio signal by separating the polyphonic signal components and the pure tone signal components from the audio signal, providing data support for the subsequent calculation of the low-frequency attenuation of the audio signal during transmission.

[0021] The audio signal refers to a sequence of electrical signals captured by a Bluetooth receiver that reflects the sound characteristics output by the device, such as waveform amplitude variations and frequency components. The polyphonic signal component refers to a complex audio portion obtained through signal processing, containing multiple superimposed harmonic components, such as the chord structure in a musical passage. The pure tone signal component refers to a simple audio portion obtained through signal processing, containing only fundamental frequency components, such as the main tone in a speech signal. Furthermore, the audio signal played by the Bluetooth device can be acquired through a high-precision audio acquisition interface and a digital filtering unit.

[0022] Figure 2This is a schematic diagram of the signal separation process in a dynamic bass enhancement method for a Bluetooth device according to an embodiment of the present invention.

[0023] As an embodiment of the present invention, separating the polyphonic signal component and the pure tone signal component from the audio signal includes: S201: Perform frequency domain decomposition on the audio signal to obtain the energy distribution characteristics of different frequency bands; S202: Identify the harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band in the energy distribution characteristics; S203: Construct the distribution boundary of the harmonic cluster and the fundamental frequency region in the time-frequency domain; S204: Based on the distribution boundary, separate the polyphonic signal component and the pure tone signal component from the audio signal.

[0024] The energy distribution characteristics refer to the set of quantitative data reflecting the intensity distribution of each frequency component, obtained through spectral analysis. The harmonic cluster refers to a densely distributed region composed of frequency components that are integer multiples of the fundamental frequency, identified through spectral peak detection. The fundamental frequency region refers to the core frequency band range containing the fundamental frequency of the signal and its neighboring components, determined through fundamental frequency estimation. The distribution boundary refers to the dividing line on the time-frequency plane that distinguishes harmonic components from fundamental frequency components, obtained through cluster analysis.

[0025] Optionally, the frequency domain decomposition of the audio signal can be achieved by fast Fourier transform to obtain the energy distribution characteristics of different frequency bands; the distribution boundaries of the harmonic cluster and the fundamental frequency region in the time-frequency domain can be constructed by Gaussian mixture model clustering and density peak detection; and the polyphonic signal components and pure tone signal components can be separated from the audio signal based on the distribution boundaries by time-frequency masking and adaptive filtering techniques.

[0026] Figure 3 This is a schematic diagram of the energy distribution feature identification process in a dynamic bass enhancement method for a Bluetooth device according to an embodiment of the present invention.

[0027] Optionally, identifying the harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band within the energy distribution characteristics includes: S301: Analyze the spectral peak distribution in the energy distribution characteristics to obtain significant harmonic components; S302: Verify the harmonic sequence structure in the energy distribution characteristics to obtain the cluster continuity index; S303: Combining the significant harmonic components and the cluster continuity index, identify the harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band in the energy distribution characteristics.

[0028] The significant harmonic components refer to the set of frequency components whose energy values ​​exceed the background noise level, obtained through spectral peak detection; the cluster continuity index refers to the quantitative value of structural coherence obtained by analyzing the distribution integrity of harmonic components in the frequency domain.

[0029] Optionally, the spectral peak distribution in the energy distribution characteristics can be analyzed using a multi-scale peak detection algorithm to obtain significant harmonic components; the harmonic sequence structure in the energy distribution characteristics can be verified by combining harmonic sequence integrity verification with fundamental frequency dominance assessment to obtain cluster continuity indices; and a spectral clustering algorithm can be used to combine the significant harmonic components and the cluster continuity indices to identify harmonic clusters in the energy distribution characteristics related to high-frequency bands and fundamental frequency regions in the low-frequency bands. Specifically, when analyzing the peak distribution of the spectrum, a multi-scale peak detection algorithm is used to identify peak points with significantly higher energy than the background level at different frequency domain resolutions. A set of candidate harmonic components is obtained through energy threshold screening and neighborhood comparison. When verifying the harmonic sequence structure, the integrity of the harmonic sequence is first checked to see if the candidate components conform to integer multiples of the fundamental frequency. Then, the fundamental frequency dominance is assessed to confirm the energy dominance of the fundamental frequency components in their respective frequency bands, outputting a cluster continuity index within the range of 0-1. In the combined identification stage, significant harmonic components are used as node features, and the cluster continuity index is used as connection weights. A frequency domain graph model is constructed using a spectral clustering algorithm, and partitioning is completed. Finally, accurate identification of harmonic clusters and fundamental frequency regions is achieved. This identification result directly serves subsequent distribution boundary construction and signal separation processing.

[0030] This invention calculates the harmonic ratio attenuation factor of the audio signal to understand its structural attenuation characteristics, facilitating subsequent calculations of low-frequency attenuation during transmission. The harmonic ratio attenuation factor is based on the intensity comparison between the polyphonic signal components and the pure-tone signal components.

[0031] As an embodiment of the present invention, the step of calculating the harmonic ratio attenuation factor of the audio signal by combining the polyphonic signal components and the pure tone signal components includes: The energy intensities corresponding to the polyphonic signal components and the pure tone signal components are measured respectively to obtain the polyphonic energy value and the pure tone energy value; The ratio of the polyphonic energy value to the pure tone energy value is calculated to obtain the real-time harmonic ratio; Analyze the dynamic change trend of the real-time harmonic ratio within a preset time window; Based on the aforementioned proportional relationship and the dynamic change trend, the harmonic ratio attenuation factor of the audio signal is calculated.

[0032] Wherein, the proportional relationship is the instantaneous ratio of the polyphonic energy value to the pure tone energy value; the preset time window is the analysis period set according to the signal sampling rate and transmission characteristics; the dynamic change trend refers to the attenuation law of the harmonic ratio over time.

[0033] Optionally, when calculating the proportional relationship, the real-time ratio representing the relative intensity of harmonic components is obtained by dividing the polyphonic energy value by the pure tone energy value; when analyzing the dynamic trend, the time series data of the harmonic ratio is tracked using the sliding window technique, and its attenuation slope is calculated through linear regression analysis; in the comprehensive calculation stage, the real-time harmonic ratio is used as the basic reference value, and the attenuation slope is used as the change correction amount. The harmonic ratio attenuation factor in the range of 0-1 is obtained through weighted calculation. The larger the value, the more obvious the attenuation of the harmonic structure during signal transmission.

[0034] S2. Determine the audible transmission distance between the Bluetooth device and the listener, and calculate the low-frequency attenuation of the audio signal during transmission by combining the harmonic ratio attenuation factor.

[0035] This invention quantifies the energy loss of the low-frequency components of the audio signal during transmission by determining the audible transmission distance between the Bluetooth device and the listener, and combining this with a harmonic ratio attenuation factor, providing an important reference for subsequent processing. The listener is the recipient of the audio signal, i.e., a person or device that needs to receive the audio signal, such as a user in a room or a hearing aid. The audible transmission distance refers to the effective sound wave propagation distance between the Bluetooth device's sound unit and the listener's auditory receiving position. The low-frequency attenuation refers to the energy loss of the low-frequency components of the audio signal at a specific transmission distance. Furthermore, the audible transmission distance between the Bluetooth device and the listener can be determined using ultrasonic ranging technology.

[0036] As an embodiment of the present invention, determining the audible transmission distance between the Bluetooth device and the listener, and calculating the low-frequency attenuation of the audio signal during transmission in conjunction with the harmonic ratio attenuation factor, includes: Query the audio output power corresponding to the Bluetooth device and collect the signal frequency spectrum of the audio signal; Based on the frequency spectrum, the proportion of low-frequency harmonics corresponding to the audio signal is calculated; The low-frequency attenuation of the audio signal during transmission is calculated by combining the auditory transmission distance, the harmonic ratio attenuation factor, the audio output power, and the low-frequency harmonic ratio.

[0037] The audio output power refers to the total electrical power output by the Bluetooth device amplifier, which is the source of the audio signal strength and determines the initial energy available for transmission. For example, the rated output power of a Bluetooth speaker is 10 watts (W). The signal frequency spectrum refers to the amplitude or energy distribution of the audio signal at each frequency point obtained by Fast Fourier Transform (FFT). The low-frequency harmonic ratio refers to the weight of the low-frequency band (such as 20-200Hz) signal energy in the total energy of the full-frequency band signal.

[0038] Optionally, the audio output power can be obtained by consulting the product specification sheet of the Bluetooth device or by measuring it under standard load using an audio analyzer; the signal frequency spectrum can be obtained by performing real-time spectrum analysis on the collected audio samples.

[0039] Optionally, as another optional embodiment of the present invention, the low-frequency attenuation of the audio signal during transmission is calculated using the following formula, combining the auditory transmission distance, the harmonic ratio attenuation factor, the audio output power, and the low-frequency harmonic ratio:

[0040] Where A represents the low-frequency attenuation of the audio signal during transmission, P represents the audio output power, γ represents the low-frequency harmonic ratio, β represents the harmonic ratio attenuation factor, and D represents the auditory transmission distance.

[0041] This formula is based on the classic exponential decay model, which is widely applicable to calculating energy loss when sound waves, electromagnetic waves, and other electromagnetic waves propagate through a medium. It can more accurately describe the attenuation phenomenon in the real world: in the initial stage of propagation, the energy decays rapidly; as the distance increases, the rate of decay of the remaining energy gradually slows down.

[0042] Optionally, calculating the low-frequency harmonic ratio corresponding to the audio signal based on the frequency spectrum includes: Divide the effective low-frequency bandwidth corresponding to the audio signal; Extract the spectral energy in the frequency spectrum that is associated with the effective low-frequency bandwidth; The ratio of the spectral energy to the total spectral energy of the frequency spectrum is calculated to obtain the low-frequency harmonic ratio of the audio signal.

[0043] The effective low-frequency bandwidth is a key frequency range defined based on the target's auditory characteristics and the acoustic performance of the Bluetooth device, used to calculate the low-frequency energy weight; the spectral energy is the sum of the squares of the amplitudes of all frequency components within the effective low-frequency bandwidth, used to quantify the sound signal strength of that frequency band; the total spectral energy is the sum of the squares of the amplitudes of all frequency components within the entire audible frequency band, representing the total intensity of the audio signal.

[0044] Optionally, when dividing the effective low-frequency bandwidth, the corresponding reference frequency range can first be retrieved from the preset configuration library according to the type attribute of the audio signal. The type attribute includes voice, music, or podcast, and can be obtained by querying: if the signal type is "music", the reference frequency range is 20Hz-200Hz; if it is "voice", the reference frequency range is 80Hz-250Hz; then, the reference range is fine-tuned in combination with the low-frequency response lower limit of the Bluetooth device to obtain the final effective low-frequency bandwidth.

[0045] Optionally, when extracting spectral energy, the upper and lower cutoff points of the effective low-frequency bandwidth can be located first in the frequency spectrum data. Then, the amplitudes of all discrete frequency points within the cutoff point interval are squared and summed.

[0046] Optionally, when calculating the low-frequency harmonic ratio, the same amplitude square summation method can be used first to calculate the total spectral energy in the full frequency band from 20Hz to 20kHz. Then, the spectral energy and the total spectral energy are normalized and the ratio is calculated using the formula: Low-frequency harmonic ratio = spectral energy / total spectral energy, which finally yields the ratio coefficient representing the relative weight of the low-frequency components.

[0047] S3. Based on the auditory transmission distance, calculate the listener's perceived bass loudness and obtain the listener's target bass enhancement intensity.

[0048] This invention quantifies the listener's actual perceived bass intensity in a real listening environment by calculating the listener's perceived bass loudness based on the auditory transmission distance. The perceived bass loudness is an estimated value reflecting the listener's subjective perception of bass intensity, calculated using a loudness calculation function after comprehensively considering the audio signal characteristics, transmission environment, and individual listener differences. The target bass enhancement intensity is a quantified value of the amount of low-frequency energy compensation required to compensate for the gap between perceived loudness and desired loudness. Furthermore, by analyzing the listener's historical adjustment data and listening habits, a pre-trained recommendation model automatically generates a personalized target enhancement intensity.

[0049] As an embodiment of the present invention, calculating the listener's perceived bass loudness based on the auditory transmission distance includes: Calculate the low-frequency energy concentration corresponding to the audio signal, and measure the ambient noise level corresponding to the listener; Based on the ambient noise level, the masking effect index of the listening environment in which the listener is located is calculated; The perceived loudness of bass frequencies is calculated by combining the low-frequency energy concentration, the masking effect index, and the auditory transmission distance.

[0050] The low-frequency energy concentration is a core parameter characterizing the energy distribution density of low-frequency components in an audio signal. The masking effect index is a parameter that quantifies the degree to which environmental noise masks the target audio signal; a larger value indicates a more severe degree to which the bass signal is masked by noise.

[0051] Optionally, the ambient noise level corresponding to the listener can be measured using a sound level meter. When calculating the masking effect index, the spectral characteristics of the ambient noise can first be analyzed using a psychoacoustic model to determine its noise sound pressure level in the low-frequency band. Then, the masking threshold of the noise on the bass signal can be derived using the Zwicker loudness calculation method, which can be obtained by the formula: Masking effect index = min(1, Ambient noise sound pressure level / Bass signal reference sound pressure level), where the reference sound pressure level is usually taken as 60 dBSPL, thus obtaining the normalized masking effect index between 0 and 1.

[0052] Optionally, as another optional embodiment of the present invention, the calculation of the listener's perceived bass loudness using the following formula, combining the low-frequency energy concentration, the masking effect index, and the auditory transmission distance, includes:

[0053] Where M represents the listener's perceived bass loudness, κ represents the low-frequency energy concentration, S0 represents the reference signal strength, D represents the auditory transmission distance, and μ represents the masking effect index.

[0054] Optionally, calculating the low-frequency energy concentration corresponding to the audio signal includes: The audio signal is decomposed by wavelet packet decomposition to obtain the low-frequency subband energy of different frequency bands; Analyze the energy statistical characteristics corresponding to the low-frequency subband energy to calculate the energy skewness and energy kurtosis of the low-frequency subband energy; By combining the energy skewness and the energy kurtosis, the low-frequency energy concentration corresponding to the audio signal is calculated.

[0055] The wavelet packet decomposition is a time-frequency analysis result obtained by performing a 5-level decomposition of the audio signal using the sym4 wavelet basis function; the energy skewness is a statistical measure characterizing the asymmetry of the energy distribution of each low-frequency sub-band, with a positive value indicating that the energy is concentrated in a few sub-bands; the energy kurtosis is a statistical measure characterizing the sharpness of the energy distribution of each low-frequency sub-band, with a larger value indicating a more concentrated energy distribution.

[0056] Optionally, when performing wavelet packet decomposition, you can first select the sym4 wavelet basis function, set the number of decomposition layers to 5, select all sub-band nodes in the frequency range of 20Hz-150Hz in the 5th decomposition, calculate the sum of squares of the coefficients of each node as the sub-band energy, and form a low-frequency sub-band energy sequence.

[0057] Optionally, when calculating energy skewness and energy kurtosis, the low-frequency subband energy sequence can first be standardized so that its sum is 1. Then, the third central moment of the standardized sequence is calculated to obtain the energy skewness, and the fourth central moment is calculated to obtain the energy kurtosis. The formula is: Energy skewness = μ³ / σ 3 Energy kurtosis = μ4 / σ 4 , where μ3 and μ4 are the third and fourth order central moments, respectively, and σ is the standard deviation of the subband energy sequence.

[0058] Optionally, when calculating the low-frequency energy concentration by combining energy skewness and energy kurtosis, the absolute value of energy skewness can be taken first to eliminate the influence of direction. Then, the weighted fusion formula is used: Low-frequency energy concentration = 0.6 × |energy skewness| + 0.4 × energy kurtosis, where the weight coefficients 0.6 and 0.4 are determined based on experimental results of a large number of audio samples. Finally, a quantified value of low-frequency energy concentration in the range of 0-2 is obtained.

[0059] S4. Combining the low-frequency attenuation and the perceived bass loudness, determine the harmonic balance equivalent of the output sound field of the Bluetooth device, wherein the harmonic balance equivalent is the amplitude matching coefficient between the harmonic components and the fundamental frequency components in the output sound field of the Bluetooth device, and calculate the effective bass enhancement of the Bluetooth device by combining the harmonic proportional attenuation factor.

[0060] This invention, by combining the low-frequency attenuation and the perceived bass loudness to determine the harmonic balance equivalent, can quantitatively evaluate the sound quality balance of the output sound field. Furthermore, by combining the harmonic proportional attenuation factor to calculate the effective bass enhancement, it can accurately determine the optimal enhancement level that compensates for auditory loss while maintaining sound quality purity, providing precise control for audio optimization. The effective bass enhancement refers to the maximum safe enhancement level that, considering harmonic attenuation characteristics, effectively improves the perceived bass loudness while ensuring no perceptible distortion in sound quality. Further, by combining the harmonic proportional attenuation factor and the harmonic balance equivalent, the effective bass enhancement of the Bluetooth device is calculated. First, the attenuation level of the bass signal during transmission is determined based on the harmonic proportional attenuation factor, and the basic compensation requirement is calculated. Then, the harmonic balance equivalent is used as the upper limit of sound quality constraints, and the basic compensation amount is adjusted through a weighted model to ensure that the enhanced sound field does not produce perceptible distortion, ultimately outputting an effective bass enhancement within a safe range.

[0061] As an embodiment of the present invention, determining the harmonic balance equivalent of the Bluetooth device's output sound field by combining the low-frequency attenuation and the perceived bass loudness includes: Extract the harmonic energy and fundamental frequency energy of the sound field output by the Bluetooth device; Calculate the ratio between the harmonic energy and the fundamental frequency energy to obtain the harmonic-fundamental frequency ratio. By combining the low-frequency attenuation and the perceived bass loudness, the harmonic fundamental frequency ratio is corrected to determine the harmonic balance equivalent of the sound field output by the Bluetooth device.

[0062] Wherein, the harmonic energy is the sum of the squares of the amplitudes of the second to fifth harmonic components in the output sound field; the fundamental frequency energy is the square of the amplitude of the fundamental frequency component in the output sound field; the harmonic-fundamental frequency ratio is the dimensionless ratio of the harmonic energy to the fundamental frequency energy; and the harmonic balance equivalent is a standardized harmonic balance index after correction for transmission loss and auditory characteristics.

[0063] Optionally, when extracting harmonic energy and fundamental frequency energy, a high-resolution spectrum can be obtained by first performing a 4096-point fast Fourier transform on the output sound field signal, identifying the position of the fundamental frequency peak through a peak detection algorithm, and then extracting harmonic components within a ±5Hz bandwidth centered on integer multiples of the fundamental frequency. The square of the amplitude of each harmonic component is calculated and summed to obtain the harmonic energy. At the same time, the square of the amplitude within a ±2Hz bandwidth at the fundamental frequency peak is calculated as the fundamental frequency energy.

[0064] Optionally, when combining low-frequency attenuation and perceived bass loudness for correction, a harmonic balance correction function can be established first. The formula is: Harmonic balance equivalent = Harmonic fundamental frequency ratio × [1 + α·(1 - Low-frequency attenuation)] × [1 + γ· Bass perceived loudness], where α is the transmission loss correction coefficient, ranging from 0.1 to 0.3, and γ is the listening compensation coefficient, ranging from 0.05 to 0.15. This function can be used to dynamically weight and correct the original harmonic fundamental frequency ratio, thus obtaining a harmonic balance equivalent that meets the requirements of the current listening environment.

[0065] Optionally, when determining the transmission loss correction coefficient, a mapping table between different transmission environment types and correction coefficients can be established first. The environment types include typical scenarios such as free space, indoor reverberation, and outdoor open space. By querying the type of the current listening environment, the corresponding transmission loss correction coefficient value can be directly obtained from the mapping table.

[0066] Optionally, when determining the sound compensation coefficient, a personalized configuration profile based on the user's listening preferences can be constructed first. By analyzing the bass enhancement tendency in the user's historical adjustment records, a linear regression algorithm can be used to calculate the most suitable sound compensation coefficient for the user, and it can be stored in the user's personalized configuration file for later use.

[0067] S5. Based on the effective bass enhancement amount and the target bass enhancement intensity, perform bass enhancement processing on the audio signal to obtain an enhanced audio signal.

[0068] This invention performs bass enhancement processing based on the effective bass enhancement amount and the target bass enhancement intensity, thereby achieving precise bass effect enhancement while ensuring audio quality. This satisfies the user's listening needs and avoids audio distortion caused by excessive enhancement.

[0069] Optionally, based on the effective bass enhancement amount and the target bass enhancement intensity, bass enhancement processing is performed on the audio signal to obtain an enhanced audio signal. The specific steps are as follows: First, the effective bass enhancement amount and the target bass enhancement intensity are compared, and the smaller value is selected as the actual application enhancement amount to ensure that the enhancement operation is within the safe range of the device; Second, dynamic range control technology is used to selectively boost the low-frequency components in the audio signal according to the actual application enhancement amount, while keeping the mid-high frequency components unchanged; Finally, phase alignment and harmonic compensation processing are used to eliminate the phase distortion that may occur during the enhancement process, and an enhanced audio signal with both a strong bass effect and the original sound quality characteristics is output.

[0070] like Figure 4 The diagram shown is a functional block diagram of a dynamic bass enhancement system for a Bluetooth device according to the present invention.

[0071] The dynamic bass enhancement system 400 for a Bluetooth device described in this invention can be installed in an electronic device. Depending on the functions implemented, the dynamic bass enhancement system 400 for a Bluetooth device may include a signal component analysis module 401, a transmission attenuation calculation module 402, a perceived loudness calculation module 403, a bass enhancement amount calculation module 404, and a bass enhancement processing module 405. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0072] In this embodiment of the invention, the functions of each module / unit are as follows: The signal component analysis module 401 is used to collect the audio signal played by the Bluetooth device and separate the polyphonic signal component and the pure tone signal component from the audio signal to calculate the harmonic ratio attenuation factor of the audio signal. The transmission attenuation calculation module 402 is used to determine the audible transmission distance between the Bluetooth device and the listener, and to calculate the low-frequency attenuation of the audio signal during transmission in combination with the harmonic ratio attenuation factor. The perceived loudness calculation module 403 is used to calculate the bass perceived loudness of the listener based on the auditory transmission distance, and to obtain the target bass enhancement intensity of the listener. The bass enhancement calculation module 404 is used to combine the low-frequency attenuation amount and the bass perceived loudness to determine the harmonic balance equivalent of the output sound field of the Bluetooth device, wherein the harmonic balance equivalent is the amplitude matching coefficient between the harmonic components and the fundamental frequency components in the output sound field of the Bluetooth device, and to calculate the effective bass enhancement amount of the Bluetooth device in combination with the harmonic proportional attenuation factor. The bass enhancement processing module 405 is used to perform bass enhancement processing on the audio signal based on the effective bass enhancement amount and the target bass enhancement intensity to obtain an enhanced audio signal.

[0073] In detail, the modules in the dynamic bass enhancement system 400 of a Bluetooth device described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method used is the same as the dynamic bass enhancement method for Bluetooth devices described above, and can produce the same technical effect, so it will not be repeated here.

[0074] In one embodiment, a computer device is provided, which may be a server or a client, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a dynamic bass enhancement method for a Bluetooth device on the server or client side.

[0075] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0076] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0077] Finally, it should be noted that in the above embodiments, each embodiment can be combined with each other or independent. Deleting any one of them will not affect the technical implementation of other embodiments. The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A dynamic bass enhancement method for a Bluetooth device, characterized by, The method includes: The audio signal played by the Bluetooth device is collected, and the polyphonic signal component and the pure tone signal component are separated from the audio signal to calculate the harmonic ratio attenuation factor of the audio signal. Determine the audible transmission distance between the Bluetooth device and the listener, and in conjunction with the harmonic ratio attenuation factor, calculate the low-frequency attenuation of the audio signal during transmission; Based on the auditory transmission distance, the listener's perceived bass loudness is calculated, and the listener's target bass enhancement intensity is obtained; By combining the low-frequency attenuation and the perceived bass loudness, the harmonic balance equivalent of the output sound field of the Bluetooth device is determined. The harmonic balance equivalent is the amplitude matching coefficient between the harmonic components and the fundamental frequency components in the output sound field of the Bluetooth device. The effective bass enhancement of the Bluetooth device is calculated by combining the harmonic proportional attenuation factor. Based on the effective bass enhancement amount and the target bass enhancement intensity, bass enhancement processing is performed on the audio signal to obtain an enhanced audio signal.

2. The method of claim 1, wherein the dynamic bass enhancement is performed by the Bluetooth device. The step of separating the polyphonic signal components and the pure tone signal components from the audio signal includes: The audio signal is decomposed in the frequency domain to obtain the energy distribution characteristics of different frequency bands; Identify the harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band within the energy distribution characteristics; Construct the distribution boundaries of the harmonic cluster and the fundamental frequency region in the time-frequency domain; Based on the distribution boundary, polyphonic signal components and pure tone signal components are separated from the audio signal.

3. The dynamic bass enhancement method for a Bluetooth device as described in claim 2, characterized in that, The identification of harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band of the energy distribution characteristics includes: Analyze the spectral peak distribution in the energy distribution characteristics to obtain significant harmonic components; Verify the harmonic sequence structure in the energy distribution characteristics to obtain the cluster continuity index; By combining the significant harmonic components and the cluster continuity index, the harmonic clusters in the high-frequency band and the fundamental frequency region in the low-frequency band in the energy distribution characteristics are identified.

4. The dynamic bass enhancement method for a Bluetooth device as described in claim 1, characterized in that, The calculation of the harmonic ratio attenuation factor of the audio signal includes: The energy intensities corresponding to the polyphonic signal components and the pure tone signal components are measured respectively to obtain the polyphonic energy value and the pure tone energy value; The ratio of the polyphonic energy value to the pure tone energy value is calculated to obtain the real-time harmonic ratio; Analyze the dynamic change trend of the real-time harmonic ratio within a preset time window; Based on the aforementioned proportional relationship and the dynamic change trend, the harmonic ratio attenuation factor of the audio signal is calculated.

5. The dynamic bass enhancement method for a Bluetooth device as described in claim 1, characterized in that, Determining the audible transmission distance between the Bluetooth device and the listener, and calculating the low-frequency attenuation of the audio signal during transmission in conjunction with the harmonic ratio attenuation factor, includes: Query the audio output power corresponding to the Bluetooth device and collect the signal frequency spectrum of the audio signal; Based on the frequency spectrum, the proportion of low-frequency harmonics corresponding to the audio signal is calculated; The low-frequency attenuation of the audio signal during transmission is calculated by combining the auditory transmission distance, the harmonic ratio attenuation factor, the audio output power, and the low-frequency harmonic ratio.

6. The dynamic bass enhancement method for a Bluetooth device as described in claim 5, characterized in that, The step of calculating the low-frequency harmonic ratio of the audio signal based on the frequency spectrum includes: Divide the effective low-frequency bandwidth corresponding to the audio signal; Extract the spectral energy in the frequency spectrum that is associated with the effective low-frequency bandwidth; The ratio of the spectral energy to the total spectral energy of the frequency spectrum is calculated to obtain the low-frequency harmonic ratio of the audio signal.

7. The dynamic bass enhancement method for a Bluetooth device as described in claim 1, characterized in that, The calculation of the listener's perceived bass loudness based on the auditory transmission distance includes: Calculate the low-frequency energy concentration corresponding to the audio signal, and measure the ambient noise level corresponding to the listener; Based on the ambient noise level, the masking effect index of the listening environment in which the listener is located is calculated; The perceived loudness of bass frequencies is calculated by combining the low-frequency energy concentration, the masking effect index, and the auditory transmission distance.

8. The dynamic bass enhancement method for a Bluetooth device as described in claim 7, characterized in that, The calculation of the low-frequency energy concentration corresponding to the audio signal includes: The audio signal is decomposed by wavelet packet decomposition to obtain the low-frequency subband energy of different frequency bands; Analyze the energy statistical characteristics corresponding to the low-frequency subband energy to calculate the energy skewness and energy kurtosis of the low-frequency subband energy; By combining the energy skewness and the energy kurtosis, the low-frequency energy concentration corresponding to the audio signal is calculated.

9. The dynamic bass enhancement method for a Bluetooth device as described in claim 1, characterized in that, The determination of the harmonic balance equivalent of the Bluetooth device's output sound field by combining the low-frequency attenuation and the perceived bass loudness includes: Extract the harmonic energy and fundamental frequency energy of the sound field output by the Bluetooth device; Calculate the ratio between the harmonic energy and the fundamental frequency energy to obtain the harmonic-fundamental frequency ratio. By combining the low-frequency attenuation and the perceived bass loudness, the harmonic fundamental frequency ratio is corrected to determine the harmonic balance equivalent of the sound field output by the Bluetooth device.

10. A dynamic bass enhancement system for a Bluetooth device, characterized in that, The system includes: The signal component analysis module is used to collect the audio signal played by the Bluetooth device and separate the polyphonic signal component and the pure tone signal component from the audio signal in order to calculate the harmonic ratio attenuation factor of the audio signal. The transmission attenuation calculation module is used to determine the audible transmission distance between the Bluetooth device and the listener, and to calculate the low-frequency attenuation of the audio signal during transmission by combining the harmonic ratio attenuation factor. The perceived loudness calculation module is used to calculate the bass perceived loudness of the listener based on the auditory transmission distance, and to obtain the target bass enhancement intensity of the listener. The bass enhancement calculation module is used to combine the low-frequency attenuation amount and the bass perceived loudness to determine the harmonic balance equivalent of the output sound field of the Bluetooth device. The harmonic balance equivalent is the amplitude matching coefficient between the harmonic components and the fundamental frequency components in the output sound field of the Bluetooth device. The module also combines the harmonic proportional attenuation factor to calculate the effective bass enhancement amount of the Bluetooth device. The bass enhancement processing module is used to perform bass enhancement processing on the audio signal based on the effective bass enhancement amount and the target bass enhancement intensity to obtain an enhanced audio signal.

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