Room sound calibration method based on hearing preference control and related device

Abstract

The present application relates to the technical field of sound calibration, and discloses a room sound calibration method based on hearing tendency control and related equipment, which is used for improving the matching degree of calibration results and user hearing preferences. The room sound calibration method based on hearing tendency control comprises the following steps: obtaining a hearing tendency parameter selected by a user through an interactive interface and a room impulse response of a current room; determining a group of frequency-related window control parameters according to the hearing tendency parameter and the room impulse response; determining a window length varying with frequency windowing strategy based on the window control parameters; performing windowing processing on the room impulse response by using the windowing strategy to extract an effective frequency response curve used for sound calibration; calculating the difference between the effective frequency response curve and a target frequency response curve to obtain correction filter coefficients; and calibrating the audio signal of an audio playback system based on the correction filter coefficients.

Description

Technical Field

[0001] This invention relates to the field of acoustic calibration technology, and in particular to a room acoustic calibration method and related equipment based on auditory tendency control. Background Technology

[0002] Currently, room acoustic calibration methods typically rely on global or fixed-band analysis of impulse responses, processing acoustic data only under a single measurement condition and ignoring the differences in time-domain characteristics corresponding to acoustic problems in different frequency bands. The analysis and extraction of room acoustic parameters and the control of user listening preferences are often two independent modules, lacking an effective integration mechanism. This separation limits the calibration effect, making it difficult for users to achieve a balance between technical calibration and subjective listening experience. This results in a significant deviation between calibration results and user listening preferences, addressing only a single problem, producing rigid effects, and failing to meet personalized needs. Summary of the Invention

[0003] This invention provides a room acoustic calibration method and related equipment based on listening preference control, to solve the problem in the prior art that the use of fixed window length to analyze impulse response leads to the inability to take into account both frequency resolution and time resolution during full-band calibration, resulting in low matching degree between calibration results and user listening preferences.

[0004] The first aspect of this invention provides a room acoustic calibration method based on auditory preference control, comprising: acquiring auditory preference parameters selected by a user through an interactive interface and the room impulse response of the current room; determining a set of frequency-related window control parameters based on the auditory preference parameters and the room impulse response; determining a windowing strategy with a window length varying with frequency based on the window control parameters; performing windowing processing on the room impulse response using the windowing strategy to extract an effective frequency response curve for acoustic calibration; calculating correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve; and calibrating the audio signal of an audio playback system based on the correction filter coefficients.

[0005] In one feasible implementation, determining a set of frequency-related window control parameters based on the listening preference parameter and the room impulse response includes: mapping the listening preference parameter to an initial window period number for three independent frequency bands based on a preset mapping relationship, wherein the three independent frequency bands include a low-frequency band, a mid-frequency band, and a high-frequency band; analyzing the room impulse response to obtain room environment indicators; correcting the initial window period number based on the room environment indicators to obtain a target window period number; calculating a window length parameter that varies with frequency based on the target window period number, and using the window length parameter as the window control parameter.

[0006] In one feasible implementation, mapping the listening preference parameter to the initial window period number of three independent frequency bands based on a preset mapping relationship includes: providing at least two predefined window period number templates, each template containing a set of reference window period numbers for the low-frequency band, mid-frequency band, and high-frequency band, and each template corresponding to a different listening preference; performing interpolation calculation between the reference window period numbers of the at least two templates according to the value or level of the listening preference parameter; and determining the initial window period number of the low-frequency band, mid-frequency band, and high-frequency band based on the interpolation calculation result.

[0007] In one feasible implementation, the analysis of the room impulse response to obtain room environmental indicators includes: performing time-domain or frequency-domain analysis on the room impulse response to obtain at least one reverberation time parameter, wherein the reverberation time parameter characterizes the attenuation rate of sound energy in the room; selecting a background noise interval from the tail of the room impulse response and calculating the root mean square value or equivalent sound pressure level of the signal within the background noise interval as a background noise level indicator; identifying an early time window after the arrival of direct sound in the room impulse response and calculating the ratio of signal energy to direct sound energy within the early time window as an early reflection intensity indicator.

[0008] In one feasible implementation, the step of correcting the initial window period number based on the room environment index to obtain the target window period number includes: calculating the corresponding reverberation time correction factor for each frequency band based on the reverberation time parameter; calculating the environmental interference factor by combining the background noise level index and the early reflection intensity index; and multiplying the initial window period number of each frequency band by the reverberation time correction factor and the environmental interference factor of the corresponding frequency band to obtain the target window period number.

[0009] In one feasible implementation, the step of calculating the frequency-varying window length parameter based on the target window period number and using the window length parameter as a window control parameter includes: calculating the period length corresponding to the center frequency of each frequency band for the target window period number corresponding to the low-frequency band, the mid-frequency band, and the high-frequency band; multiplying the target window period number of each frequency band by the corresponding period length to obtain the reference window length corresponding to the low-frequency band, the mid-frequency band, and the high-frequency band respectively; and performing smooth interpolation processing on the transition frequency region between the low-frequency band, the mid-frequency band, and the high-frequency band to generate a continuously varying window length parameter across the entire frequency band as a window control parameter.

[0010] In one feasible implementation, determining a windowing strategy with a window length varying with frequency based on the window control parameters includes: determining a functional relationship between the window length and frequency based on the window length parameter in the window control parameters; and determining an executable windowing rule as the windowing strategy based on the functional relationship and a preset window function type, wherein the windowing rule defines the window function duration used when performing time-domain truncation on different frequency signal components, and the window length value corresponding to high frequencies is less than the window length value corresponding to low frequencies.

[0011] In one feasible implementation, the step of using the windowing strategy to window the room impulse response to extract an effective frequency response curve for acoustic calibration includes: identifying the start time point of the direct sound component from the room impulse response; using the start time point as a reference, applying the windowing strategy to truncate the impulse response in the time domain; and performing frequency domain analysis on the truncated time domain signal segment to obtain the effective frequency response curve.

[0012] In one feasible implementation, identifying the starting time point of the direct sound component from the room impulse response includes: locating the position where the energy first shows a significant surge in the time-domain waveform of the room impulse response; verifying and correcting the position of the first energy surge by combining the phase characteristics or group delay characteristics of the impulse response, thereby determining the starting time point of the direct sound; if the position of the first energy surge is unclear, then making a comprehensive judgment based on the acoustic characteristics at multiple candidate time points to determine the starting time point of the direct sound.

[0013] In one feasible implementation, the step of applying the windowing strategy to truncate the impulse response in the time domain based on the starting time point includes: determining the corresponding time domain truncation window length according to the windowing strategy for different frequency components contained in the room impulse response; taking the starting time point as the starting position of the window, truncating each frequency component on the room impulse response according to its corresponding time domain truncation window length to obtain a set of frequency-related time domain signal segments.

[0014] In one feasible implementation, the step of performing frequency domain analysis on the truncated time-domain signal segments to obtain an effective frequency response curve includes: performing frequency domain transformation on each time-domain signal segment to obtain a corresponding frequency domain representation; extracting the amplitude spectrum information of the corresponding frequency or frequency band from the frequency domain representation of each time-domain signal segment; and splicing and smoothing the amplitude spectrum information of all frequencies or frequency bands in frequency order to form a continuous frequency response curve covering the target frequency band, which serves as the effective frequency response curve.

[0015] In one feasible implementation, the step of calculating the correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve includes: calculating the amplitude deviation of the effective frequency response curve relative to the target frequency response curve in each frequency band; determining the frequency response characteristics that the filter needs to correct based on the amplitude deviation, and selecting the corresponding filter type and structure; and limiting the correction amplitude and range of the filter in conjunction with the style constraints corresponding to the listening preference parameter, thereby generating the final correction filter coefficients.

[0016] A second aspect of the present invention provides a room acoustic calibration device based on auditory preference control, comprising: an acquisition module for acquiring auditory preference parameters selected by a user through an interactive interface and the room impulse response of the current room; a first determination module for determining a set of frequency-related window control parameters based on the auditory preference parameters and the room impulse response; a second determination module for determining a windowing strategy with a window length varying with frequency based on the window control parameters; a processing module for windowing the room impulse response using the windowing strategy to extract an effective frequency response curve for acoustic calibration; a calculation module for calculating correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve; and a calibration module for calibrating the audio signal of an audio playback system based on the correction filter coefficients.

[0017] In one feasible implementation, the first determining module includes: a mapping unit, configured to map the listening tendency parameter to an initial window period number of three independent frequency bands based on a preset mapping relationship, wherein the three independent frequency bands include a low-frequency band, a mid-frequency band, and a high-frequency band; a first analysis unit, configured to analyze the room impulse response to obtain room environment indicators; a correction unit, configured to correct the initial window period number based on the room environment indicators to obtain a target window period number; and a calculation unit, configured to calculate a window length parameter that varies with frequency based on the target window period number, and use the window length parameter as a window control parameter.

[0018] In one feasible implementation, the mapping unit is specifically used to: provide at least two predefined window period number templates, each template containing a set of reference window period numbers for the low-frequency band, mid-frequency band, and high-frequency band, and each template corresponding to a different listening preference; perform interpolation calculation between the reference window period numbers of the at least two templates according to the value or level of the listening preference parameter; and determine the initial window period numbers for the low-frequency band, mid-frequency band, and high-frequency band based on the interpolation calculation result.

[0019] In one feasible implementation, the first analysis unit is specifically used for: performing time-domain or frequency-domain analysis on the room impulse response to obtain at least one reverberation time parameter, the reverberation time parameter characterizing the attenuation rate of sound energy in the room; selecting a background noise interval from the tail of the room impulse response, calculating the root mean square value or equivalent sound pressure level of the signal within the background noise interval as an indicator of the background noise level; identifying an early time window after the arrival of direct sound in the room impulse response, calculating the ratio of signal energy to direct sound energy within the early time window as an indicator of early reflection intensity.

[0020] In one feasible implementation, the correction unit is specifically used to: calculate the corresponding reverberation time correction factor for each frequency band based on the reverberation time parameter; calculate the environmental interference factor by combining the background noise level index and the early reflection intensity index; and multiply the initial window period number of each frequency band by the reverberation time correction factor and the environmental interference factor of the corresponding frequency band to obtain the target window period number.

[0021] In one feasible implementation, the calculation unit is specifically used to: calculate the period length corresponding to the center frequency of each frequency band for the target window period number corresponding to the low frequency band, the mid frequency band, and the high frequency band; multiply the target window period number of each frequency band by the corresponding period length to obtain the reference window length corresponding to the low frequency band, the mid frequency band, and the high frequency band respectively; and perform smooth interpolation processing on the transition frequency region between the low frequency band, the mid frequency band, and the high frequency band to generate a window length parameter that changes continuously over the entire frequency band as a window control parameter.

[0022] In one feasible implementation, the second determining module is specifically used to: determine a functional relationship between the window length and frequency according to the window length parameter in the window control parameters; and determine an executable windowing rule as a windowing strategy based on the functional relationship and the preset window function type, wherein the windowing rule defines the window function duration used when performing time-domain truncation on different frequency signal components, and the window length value corresponding to high frequency is less than the window length value corresponding to low frequency.

[0023] In one feasible implementation, the processing module includes: an identification unit for identifying the start time point of the direct sound component from the room impulse response; a truncation unit for applying the windowing strategy to truncate the impulse response in the time domain based on the start time point; and a second analysis unit for performing frequency domain analysis on the truncated time domain signal segment to obtain an effective frequency response curve.

[0024] In one feasible implementation, the identification unit is specifically used to: locate the position where the energy first shows a significant surge in the time domain waveform of the room impulse response; verify and correct the position of the first energy surge by combining the phase characteristics or group delay characteristics of the impulse response, thereby determining the starting time point of the direct sound; if the position of the first energy surge is unclear, make a comprehensive judgment based on the acoustic characteristics at multiple candidate time points to determine the starting time point of the direct sound.

[0025] In one feasible implementation, the interception unit is specifically used to: determine the corresponding time-domain interception window length according to the windowing strategy for different frequency components contained in the room impulse response; and, taking the starting time point as the starting position of the window, intercept each frequency component on the room impulse response according to its corresponding time-domain interception window length to obtain a set of frequency-related time-domain signal segments.

[0026] In one feasible implementation, the second analysis unit is specifically used to: perform frequency domain transformation on each time domain signal segment to obtain the corresponding frequency domain representation; extract the amplitude spectrum information of the corresponding frequency or frequency band from the frequency domain representation of each time domain signal segment; and splice and smoothly fuse the amplitude spectrum information of all frequencies or frequency bands in frequency order to form a continuous frequency response curve covering the target frequency band, which serves as the effective frequency response curve.

[0027] In one feasible implementation, the calculation module is specifically used to: calculate the amplitude deviation of the effective frequency response curve relative to the target frequency response curve in each frequency band; determine the frequency response characteristics that the filter needs to correct based on the amplitude deviation, and select the corresponding filter type and structure; and limit the correction amplitude and range of the filter in combination with the style constraints corresponding to the listening preference parameter, thereby generating the final correction filter coefficients.

[0028] A third aspect of the present invention provides an electronic device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor invokes the instructions in the memory to cause the electronic device to perform the above-described room acoustic calibration method based on auditory tendency control.

[0029] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described room acoustic calibration method based on auditory tendency control.

[0030] The technical solution provided by this invention involves acquiring the user's listening preference parameters and the room impulse response of the current room selected through an interactive interface; determining a set of frequency-related window control parameters based on the listening preference parameters and the room impulse response; determining a windowing strategy with a window length varying with frequency based on the window control parameters; using the windowing strategy to window the room impulse response to extract an effective frequency response curve for acoustic calibration; calculating the correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve; and calibrating the audio signal of the audio playback system based on the correction filter coefficients. In this embodiment, by introducing user listening preference parameters for control and generating frequency-related window control parameters accordingly, the window length of the room impulse response is dynamically adjusted with frequency, enabling adaptive balancing of time and frequency resolution for different frequency bands' acoustic characteristics and listening needs when extracting the effective frequency response curve. This method closely integrates subjective listening preferences with objective acoustic analysis, not only improving calibration accuracy but also achieving a high degree of matching between the calibration results and the user's personalized listening needs, ultimately outputting a more natural and optimized sound effect that better suits listening habits. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of an embodiment of the room acoustic calibration method based on auditory tendency control in this invention.

[0032] Figure 2 This is a schematic diagram of another embodiment of the room acoustic calibration method based on auditory tendency control in this invention;

[0033] Figure 3 This is a schematic diagram of another embodiment of the room acoustic calibration method based on auditory tendency control in the present invention;

[0034] Figure 4 This is a schematic diagram of one embodiment of the room acoustic calibration device based on auditory tendency control in this invention.

[0035] Figure 5 This is a schematic diagram of another embodiment of the room acoustic calibration device based on auditory tendency control in this invention.

[0036] Figure 6 This is a schematic diagram of one embodiment of the electronic device in this invention. Detailed Implementation

[0037] This invention provides a room acoustic calibration method and related equipment based on auditory preference control. By dynamically adjusting the frequency-varying window length and time reference of impulse response analysis in combination with the user's auditory preference and the room's acoustic characteristics, the accuracy, personalization, and naturalness of the final sound quality of acoustic calibration are improved.

[0038] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0039] It is understood that the executing entity of this invention can be a room acoustic calibration device based on auditory tendency control, or it can be a terminal or a server; the specific implementation is not limited here. This embodiment of the invention will be described using a server as an example.

[0040] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1 One embodiment of the room acoustic calibration method based on auditory tendency control in this invention includes:

[0041] 101. Obtain the listening preference parameters selected by the user through the interactive interface and the room impulse response of the current room;

[0042] When acquiring user listening preference parameters and room impulse response, a graphical user interface is provided, offering several preset listening mode options, such as clear vocals, powerful bass, or balanced and natural. After the user selects a mode using a slider or point-and-click, the system maps it to a set of predefined numerical parameters associated with the frequency response target. Simultaneously, the system plays a sweep frequency or maximum length sequence signal at the listening position through a connected measurement microphone and records the response, thereby acquiring the current room's true impulse response data.

[0043] 102. Based on the listening tendency parameters and room impulse response, determine a set of frequency-dependent window control parameters;

[0044] The room's impulse response is divided into frequency bands and its energy attenuation characteristics are analyzed. For example, the proportion of remaining energy at a specific time point after the direct sound has attenuated in each frequency band is calculated. Simultaneously, based on the user's selected listening preference parameters, a target energy attenuation profile is obtained from a preset mapping relationship. This profile defines the amount of reflected sound energy expected to be retained in different frequency bands. Next, the measured attenuation characteristics of each frequency band are compared with the target profile. For frequency bands where more reflected sound energy is required to be retained, a longer window control parameter value is assigned to ensure that more late reverberation components are included after windowing. Conversely, for frequency bands where the target is to focus on the direct sound, a shorter window control parameter value is assigned to highlight the early sound energy. Finally, by smoothing and interpolating the window length parameters of each frequency band, a set of frequency-dependent window length parameters that continuously vary across the entire frequency band is generated as the window control parameters.

[0045] 103. Determine a windowing strategy based on window control parameters that allows the window length to vary with frequency;

[0046] The target window length values ​​defined by the window control parameters at various frequency points are read, and a continuous smooth curve of the window length with respect to frequency is constructed using a spline interpolation algorithm. Based on this continuous smooth curve, the core rule of the windowing strategy is determined: for any frequency point to be analyzed, the time-domain length of its analysis window will be dynamically determined according to the value of the curve at that frequency, thereby ensuring that a longer analysis window is used in the low-frequency region to improve frequency resolution, while a shorter analysis window is used in the high-frequency region to enhance time resolution. This strategy also specifies the specific form of the window function used, such as the Kaiser window, and clarifies the specific alignment method of the window function when truncating the signal.

[0047] 104. Windowing strategy is used to window the room impulse response in order to extract the effective frequency response curve for acoustic calibration;

[0048] The arrival time of the direct sound in the room's impulse response is located and taken as the zero point of time. Next, according to a windowing strategy, for a series of discrete analysis frequency points, signal segments of appropriate lengths are extracted from the impulse response, starting from or centered at the zero point of time, and a specified window function is applied, based on their corresponding window lengths. Then, a Fourier transform is performed on each windowed signal segment to extract its amplitude spectrum information near the analysis frequency point. Finally, the amplitude values ​​obtained from all analysis frequency points are arranged in frequency order and smoothly connected to form a continuous effective frequency response curve.

[0049] 105. Calculate the correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve;

[0050] Over multiple frequency bands conforming to psychoacoustic models (e.g., one-third octave bands or other critical bandwidth-based bands), the average amplitude difference between the effective frequency response curve and the target frequency response curve is calculated. This difference is then used as the desired correction amount, combined with constraints derived from listening preference parameters, such as limiting the correction amount for certain frequency bands or setting different smoothness requirements. Finally, using frequency sampling or least-squares fitting algorithms, a finite impulse response filter is designed to make its frequency response as close as possible to the desired correction amount under constraints, thereby solving for the filter's tap coefficients, i.e., the correction filter coefficients.

[0051] 106. Calibrate the audio signal of the audio playback system based on the correction filter coefficients.

[0052] In this embodiment of the invention, by introducing user listening preference parameters and generating frequency-related window control parameters accordingly, the window length of the room impulse response is dynamically adjusted with frequency. This allows for adaptive balancing of time and frequency resolution when extracting the effective frequency response curve, taking into account the acoustic characteristics and listening needs of different frequency bands. This method closely integrates subjective listening preferences with objective acoustic analysis, which not only improves the accuracy of calibration but also achieves a high degree of matching between the calibration results and the user's personalized listening needs, ultimately outputting a more natural and optimized sound effect that better suits listening habits.

[0053] Please see Figure 2 Another embodiment of the room acoustic calibration method based on auditory tendency control in this invention includes:

[0054] 201. Obtain the listening preference parameters selected by the user through the interactive interface and the room impulse response of the current room;

[0055] 202. Based on the preset mapping relationship, the listening preference parameter is mapped to the initial window period number of three independent frequency bands, including the low frequency band, mid frequency band and high frequency band;

[0056] Provide at least two predefined window cycle number templates, each template containing a set of reference window cycle numbers for low frequency, mid frequency and high frequency bands, and each template corresponds to a different listening preference; perform interpolation calculation between the reference window cycle numbers of at least two templates based on the value or level of the listening preference parameter; determine the initial window cycle number for low frequency, mid frequency and high frequency bands based on the interpolation calculation results.

[0057] Multiple reference window cycle number templates are pre-stored internally. Each template corresponds to a specific listening style preference. For example, a template aiming to create a warm and mellow sound will set fewer cycles for the low-frequency range, a medium number of cycles for the mid-frequency range, and more cycles for the high-frequency range. Another template aiming for a clear and bright sound will set more cycles for the low-frequency range, a medium number of cycles for the mid-frequency range, and fewer cycles for the high-frequency range. The listening preference parameter selected by the user is normalized to a continuous value between zero and one, where zero represents a complete bias towards the listening characteristics of the first template, and one represents a complete bias towards the listening characteristics of the second template. Next, the system reads the reference window cycle numbers stored in the two predefined templates for the low-frequency, mid-frequency, and high-frequency ranges, respectively. For the low-frequency range, the low-frequency cycle number of the first template is multiplied by one and the result of subtracting the normalization parameter is added to the low-frequency cycle number of the second template multiplied by the normalization parameter itself. The sum is the interpolated cycle number for that frequency range. The exact same calculation process is applied simultaneously to the mid-frequency and high-frequency bands, meaning each band uses a weighted sum based on the corresponding template's period count. Finally, the weighted sums calculated for each of the three frequency bands are rounded to the nearest integer to obtain the initial window period counts for the low-frequency, mid-frequency, and high-frequency bands. The window period count refers to the number of sound wave cycles corresponding to the center frequency of that frequency band included within the time-domain window length. For example, for a 100Hz low-frequency signal, one sound wave cycle is 0.01 seconds; if the window period count is 10, the corresponding time-domain window length is 0.1 seconds.

[0058] 203. Analyze the room impulse response to obtain room environmental indicators;

[0059] Time-domain or frequency-domain analysis of the room impulse response is performed to obtain at least one reverberation time parameter, which characterizes the attenuation rate of sound energy in the room. A background noise interval is selected from the tail end of the room impulse response, and the root mean square value or equivalent sound pressure level of the signal in the background noise interval is calculated as an indicator of the background noise level. In the room impulse response, the early time window after the arrival of the direct sound is identified, and the ratio of the signal energy to the direct sound energy in the early time window is calculated as an indicator of the early reflection intensity.

[0060] The acquired room impulse response is processed using Schrödinger inverse integration. By linearly fitting its decay curve across multiple octave bands in the low, mid, and high frequencies, reverberation time parameters such as T20 or T60, characterizing the rate of sound energy decay, are calculated. Subsequently, a segment clearly within the steady-state noise region is selected at the end of the impulse response waveform, typically after all discernible reflections. The root mean square (RMS) value is obtained by taking the square root of the mean square of the voltage values ​​at the sampling points within this segment. This electrical signal value is then converted into an equivalent sound pressure level based on the sensitivity of the measurement system, thus obtaining an objective index of the background noise level. Next, starting from the moment the direct sound peak occurs in the impulse response, a fixed time window encompassing early reflections is extracted. The sum of the squares of the amplitudes of all sampling points within this window is calculated as the early reflection energy. This sum is then compared to the direct sound peak energy or the energy within a very short time window near the direct sound. This ratio is typically converted to decibels (dB) and ultimately used as an index of early reflection intensity to quantify the early acoustic activity of the room.

[0061] 204. Based on room environment indicators, the initial window cycle number is corrected to obtain the target window cycle number;

[0062] Based on the reverberation time parameter, the corresponding reverberation time correction factor is calculated for each frequency band; combined with the background noise level index and the early reflection intensity index, the environmental interference factor is calculated; the initial window period number of each frequency band is multiplied by the reverberation time correction factor and the environmental interference factor of the corresponding frequency band to obtain the target window period number.

[0063] Based on the reverberation time parameters obtained from the analysis of each frequency band, these parameters are compared with a preset ideal reverberation time value. If the measured value is greater than the ideal value, a correction factor greater than one is generated to increase the window length and cover more attenuating sound energy. If the measured value is less than the ideal value, a correction factor less than one is generated. This allows for the calculation of independent reverberation time correction factors for low, mid, and high frequencies. Next, the background noise level index and the early reflection intensity index are normalized and weighted summed. Higher background noise or stronger early reflections will increase the summation value. Then, a preset mapping function is used to convert this summation value into an overall environmental interference factor. This factor, also greater than one, increases the number of window periods to improve the signal-to-noise ratio and stability. Finally, the initial number of window periods for each frequency band is multiplied by its corresponding frequency band-specific reverberation time correction factor, and then multiplied by a uniform environmental interference factor. The resulting multiplication value is rounded to obtain the target number of window periods.

[0064] Formula for calculating reverberation time correction factor:

[0065]

[0066] Where b∈{L, M, H} is the frequency band identifier, and L, M and H correspond to the low frequency band, mid frequency band and high frequency band respectively; The measured reverberation time (in seconds) is for the b-th frequency band. The ideal reverberation time reference value preset for the system (unit: seconds); This is the shape control index, with a value range of (0, 1] and a default value of 0.5; the smaller the value, the more conservative the correction.

[0067] Formula for calculating environmental disturbance factors:

[0068]

[0069] ,

[0070] in, This is a normalized background noise level index, ranging from [0, 1]. is the root mean square equivalent sound pressure level (dB) in the background noise range. This is a normalized early reflection intensity index, ranging from [0, 1]. It is the ratio (linear value) of signal energy to direct sound energy within the early time window. and For the weighting coefficients, satisfying .

[0071] The target window period number is:

[0072] in, is the number of initial window periods obtained by mapping the listening preference parameter for the b-th frequency band.

[0073] By calculating reverberation time correction and environmental interference assessment separately and then combining them for the window period, the problem of applying a single correction factor to each frequency band is avoided. Low and high frequencies receive independent corrections that match their own acoustic characteristics, while the environmental interference factor provides overall robust compensation across the entire frequency band. This ensures that the final window length achieves a precise balance between user listening preferences, actual reverberation characteristics, and the noise environment, effectively improving the accuracy of extracting the effective frequency response curve in complex room environments.

[0074] 205. Calculate the window length parameter that varies with frequency based on the target window period number, and use the window length parameter as the window control parameter;

[0075] For the target window period number corresponding to the low-frequency, mid-frequency, and high-frequency bands, the period length corresponding to the center frequency of each frequency band is calculated respectively; the target window period number of each frequency band is multiplied by the corresponding period length to obtain the reference window length corresponding to the low-frequency, mid-frequency, and high-frequency bands respectively; smooth interpolation is performed on the transition frequency region between the low-frequency, mid-frequency, and high-frequency bands to generate a window length parameter that changes continuously over the entire frequency band as a window control parameter.

[0076] For the determined target window periods in the low-frequency, mid-frequency, and high-frequency bands, the standard center frequency of each band is selected (e.g., 100 Hz for low frequency, 1 kHz for mid-frequency, and 10,000 Hz for high frequency). The length of a single sound wave cycle corresponding to these center frequencies is calculated, i.e., the cycle length is equal to the reciprocal of the center frequency. Next, the target window period number for the low-frequency band is multiplied by the cycle length corresponding to 100 Hz to obtain the low-frequency reference window length in seconds. Similarly, the target window periods for the mid-frequency and high-frequency bands are multiplied by the cycle length of their respective center frequencies to obtain the reference window lengths for the mid-frequency and high-frequency bands. Finally, with frequency as the horizontal axis and window length as the vertical axis, the calculated reference window length data points for the low-frequency, mid-frequency, and high-frequency bands are used as key anchor points. A cubic spline curve fitting algorithm is used to perform smooth interpolation in the transition frequency region between them, thereby generating a window length-frequency curve that continuously and smoothly changes from the lowest analysis frequency to the highest analysis frequency. This curve is the window length parameter that ultimately controls the windowing process.

[0077] 206. Determine a windowing strategy based on window control parameters that allows the window length to vary with frequency;

[0078] 207. Windowing strategy is used to process the room impulse response to extract the effective frequency response curve for acoustic calibration;

[0079] 208. Calculate the correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve;

[0080] 209. Calibrate the audio signal of the audio playback system based on the correction filter coefficients.

[0081] In this embodiment of the invention, by mapping user listening preference parameters to the initial window period number of different frequency bands and dynamically correcting them in combination with actual room environment indicators, the windowing strategy achieves dual adaptive optimization in the frequency dimension for both user subjective preferences and objective acoustic characteristics. This method enables the impulse response analysis window length to be intelligently adjusted according to the importance of frequency bands, listening needs, and specific room acoustic conditions, thereby more accurately balancing transient and steady-state sound field information when extracting effective frequency response curves. Ultimately, it generates calibration results that are more in line with personalized listening preferences and more in line with actual room acoustic characteristics, significantly improving the naturalness of sound reproduction and the satisfaction of the listening experience.

[0082] Please see Figure 3 Another embodiment of the room acoustic calibration method based on auditory tendency control in this invention includes:

[0083] 301. Obtain the listening preference parameters selected by the user through the interactive interface and the room impulse response of the current room;

[0084] 302. Based on the listening preference parameters and room impulse response, determine a set of frequency-related window control parameters;

[0085] 303. Determine a windowing strategy based on window control parameters that allows the window length to vary with frequency;

[0086] Based on the window length parameter in the window control parameters, a functional relationship between the window length and frequency is determined. Based on the functional relationship and the preset window function type, an executable windowing rule is determined as the windowing strategy. The windowing rule defines the window function duration used when trunculating different frequency signal components in the time domain, and the window length value corresponding to high frequency is less than the window length value corresponding to low frequency.

[0087] The system reads the window length-frequency relationship stored in the window control parameters. Based on this relationship, it uses piecewise linear or spline interpolation algorithms to construct a mathematical function relationship in which the window length continuously changes with frequency. It then calls a preset window function type, such as a Hanning window or a Blackman window, as the base window shape. Next, it combines the continuous window length-frequency function relationship with the base window shape to generate a set of explicit, executable windowing rules. These rules specify that for any frequency value to be analyzed, a specific time length must be dynamically calculated based on the function relationship as the duration of the window function, ensuring that the calculated window duration strictly follows the principle of smaller high-frequency values ​​and larger low-frequency values. Finally, this complete set of rules binds dynamic window length calculation, fixed window shape, and frequency selection logic together.

[0088] 304. Identify the start time point of the direct sound component from the room impulse response;

[0089] In the time-domain waveform of the room impulse response, locate the position where the energy first shows a significant surge; combine the phase characteristics or group delay characteristics of the impulse response to verify and correct the position of the first energy surge, thereby determining the starting time point of the direct sound; if the position of the first energy surge is unclear, make a comprehensive judgment based on the acoustic characteristics at multiple candidate time points to determine the starting time point of the direct sound.

[0090] The short-time energy or envelope of the room impulse response is calculated using time-domain waveform analysis. By detecting the rising edge inflection point where this energy curve first sustains and significantly exceeds the background noise baseline threshold, candidate locations for energy spikes are initially identified. Subsequently, the instantaneous phase curve of the impulse response near these candidate locations is extracted, or its group delay is calculated. The presence of regular linear phase changes or local minima in the group delay is observed, and these phase characteristics are used to verify and fine-tune the candidate locations. If multiple energy spikes in the initial detection result in unclear locations, the characteristics of each candidate point within the preceding and following time intervals must be comprehensively evaluated. This includes comparing energy accumulation rates, analyzing the regularity of early reflected sound intervals, and checking for abrupt changes in the spectrum. By assigning different weights to these acoustic features, a score is calculated, and the candidate point with the highest overall score is ultimately selected as the starting time point of the direct sound component.

[0091] 305. Using the starting time point as a reference, apply a windowing strategy to truncate the impulse response in the time domain;

[0092] For different frequency components contained in the room impulse response, the corresponding time-domain truncation window length is determined according to the windowing strategy; taking the starting time point as the starting position of the window, for each frequency component, the room impulse response is truncated according to its corresponding time-domain truncation window length to obtain a set of frequency-related time-domain signal segments.

[0093] Based on the window length function defined in the windowing strategy, a specific time-domain truncation window length is calculated for each specific frequency or frequency band to be analyzed. Next, the previously identified direct sound start time is used as the starting point for aligning all window functions. Then, on the complete time-domain waveform of the room impulse response, signal segments of corresponding time lengths are extracted, starting from this point and using the independently calculated window length value for each frequency component. Ultimately, this series of operations will produce a set of time-domain signal segments, each with a different time length and corresponding to a specific frequency.

[0094] 306. Perform frequency domain analysis on the extracted time-domain signal segment to obtain the effective frequency response curve;

[0095] For each time-domain signal segment, a frequency domain transformation is performed to obtain the corresponding frequency domain representation. From the frequency domain representation of each time-domain signal segment, the amplitude spectrum information of the corresponding frequency or frequency band is extracted. The amplitude spectrum information of all frequencies or frequency bands is spliced ​​and smoothly fused in frequency order to form a continuous frequency response curve covering the target frequency band, which serves as the effective frequency response curve.

[0096] For each captured time-domain signal segment, a specific window function matching the segment's window length is first applied to reduce spectral leakage. Then, a Fast Fourier Transform (FFT) is performed on the windowed segment to obtain a spectrum containing complex amplitude and phase information, serving as its frequency domain representation. Next, the average amplitude spectrum value within a narrow band centered on the current analysis frequency is extracted from this spectrum, serving as the representative amplitude response value for that frequency point or band. Finally, the amplitude response values ​​acquired from all frequency points or bands are arranged sequentially from low to high frequency, and adjacent values ​​are smoothly connected using linear or spline interpolation, forming a continuous and uninterrupted effective frequency response curve across the entire target frequency band.

[0097] 307. The correction filter coefficients are calculated based on the difference between the effective frequency response curve and the target frequency response curve;

[0098] Calculate the amplitude deviation of the effective frequency response curve relative to the target frequency response curve in each frequency band; based on the amplitude deviation, determine the frequency response characteristics that the filter needs to correct, and select the appropriate filter type and structure; combined with the style constraints corresponding to the listening preference parameters, limit the correction amplitude and range of the filter, thereby generating the final correction filter coefficients.

[0099] The effective frequency response curve and the target frequency response curve are compared across multiple standard frequency bands to calculate the average amplitude deviation for each band. Then, based on the sign and magnitude of these deviations, the frequency response characteristics requiring compensation are determined, and a finite impulse response (FIR) filter is selected as the implementation structure. Next, the listening preference parameters are translated into specific constraints on the filter design; for example, limiting the high-frequency boost for users who prefer a warmer sound, or widening the low-frequency attenuation range for users who prefer a brighter sound. Finally, while satisfying these style constraints, frequency sampling or least squares optimization algorithms are used to directly calculate the filter tap coefficients that achieve the target correction, thus generating the final correction filter coefficients.

[0100] The formula for calculating the expected correction amount at each frequency point is:

[0101]

[0102] in, Index of frequency sampling points; This represents the total number of frequency sampling points. is the amplitude value (dB) of the target frequency response curve at the k-th frequency point; This represents the effective frequency response amplitude (dB) at the k-th frequency point.

[0103] The formula for calculating the amplitude limit constrained by auditory perception bias is:

[0104]

[0105] ,

[0106] Where p is the listening preference parameter normalized to [0,1] (0→warm, 1→bright); This is the upper limit of correction (upper limit of improvement, dB) for the k-th frequency point under parameter p. This is the lower limit of correction (upper limit of attenuation, dB) for the k-th frequency point under parameter p. This is the maximum allowable correction amount for the system (recommended value: 12 dB). and This is a frequency partitioning weighting function based on auditory preferences.

[0107] Solving for a weighted least squares FIR filter:

[0108] Optimal objective (weighted least squares):

[0109]

[0110] Filter frequency response definition:

[0111]

[0112] Closed solution:

[0113]

[0114] in, Let be the coefficient vector of the Nth-order FIR filter to be determined; N is the filter order; A is a K×N DFT matrix, A_{k,n} = exp( j2πkn / K); For a K×K diagonal weight matrix, the diagonal elements are... ; The perception weight for the k-th frequency point is generated by combining the equal loudness curve and parameter p (high-frequency weights are increased when there is a preference for brightness). The target linear magnitude vector, .

[0115] By transforming the qualitative description of listening preference parameters into quantitative constraints within the filter design domain, and employing a frequency-partitioned weighting function to achieve differentiated correction space control across different frequency bands, this approach prevents over-equalization from disrupting the listening balance. Furthermore, by using weighted least squares to prioritize the fitting of perceptually sensitive frequency bands, it maximizes subjective listening benefits. Compared to unconstrained equalization, the resulting filter coefficients mathematically best approximate the user's actual listening expectations, significantly reducing the probability of over-correction or style drift after calibration. Ultimately, this achieves a synergistic improvement in both objective calibration accuracy and subjective listening satisfaction.

[0116] 308. Calibrate the audio signal of the audio playback system based on the correction filter coefficients.

[0117] In this embodiment of the invention, frequency-related window control parameters are generated by combining user listening preference parameters with room impulse response analysis. Based on these parameters, intelligent time-domain truncation is performed using the direct sound start point as the time reference. This ensures that the windowing strategy can not only dynamically adjust the window length according to the frequency band, but also accurately focus on the concentrated sound energy period containing the direct sound and key early reflections. This allows the extracted effective frequency response curve to more accurately reflect the core acoustic features affecting subjective listening, thereby achieving targeted equalization and optimization of the direct sound field and early reflection sound field in subsequent calibration, ultimately obtaining a clearer, more accurate, and more user-pleasing sound quality improvement effect.

[0118] The above describes the room acoustic calibration method based on auditory tendency control in the embodiments of the present invention. The following describes the room acoustic calibration device based on auditory tendency control in the embodiments of the present invention. Please refer to [link / reference]. Figure 4 One embodiment of the room acoustic calibration device based on auditory tendency control in this invention includes:

[0119] The acquisition module 401 is used to acquire the listening preference parameters selected by the user through the interactive interface and the room impulse response of the current room;

[0120] The first determining module 402 is used to determine a set of frequency-related window control parameters based on the listening tendency parameters and the room impulse response;

[0121] The second determining module 403 is used to determine a windowing strategy whose window length varies with frequency based on window control parameters;

[0122] Processing module 404 is used to perform windowing processing on the room impulse response using a windowing strategy to extract the effective frequency response curve for acoustic calibration;

[0123] The calculation module 405 is used to calculate the correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve.

[0124] The calibration module 406 is used to calibrate the audio signal of the audio playback system based on the correction filter coefficients.

[0125] In this embodiment of the invention, by introducing user listening preference parameters and generating frequency-related window control parameters accordingly, the window length of the room impulse response is dynamically adjusted with frequency. This allows for adaptive balancing of time and frequency resolution when extracting the effective frequency response curve, taking into account the acoustic characteristics and listening needs of different frequency bands. This method closely integrates subjective listening preferences with objective acoustic analysis, which not only improves the accuracy of calibration but also achieves a high degree of matching between the calibration results and the user's personalized listening needs, ultimately outputting a more natural and optimized sound effect that better suits listening habits.

[0126] Please see Figure 5 Another embodiment of the room acoustic calibration device based on auditory tendency control in this invention includes:

[0127] The acquisition module 401 is used to acquire the listening preference parameters selected by the user through the interactive interface and the room impulse response of the current room;

[0128] The first determining module 402 is used to determine a set of frequency-related window control parameters based on the listening tendency parameters and the room impulse response;

[0129] The second determining module 403 is used to determine a windowing strategy whose window length varies with frequency based on window control parameters;

[0130] Processing module 404 is used to perform windowing processing on the room impulse response using a windowing strategy to extract the effective frequency response curve for acoustic calibration;

[0131] The calculation module 405 is used to calculate the correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve.

[0132] The calibration module 406 is used to calibrate the audio signal of the audio playback system based on the correction filter coefficients.

[0133] Optionally, the first determining module 402 can be specifically used for:

[0134] The mapping unit 4021 is used to map the listening preference parameter to the initial window period number of three independent frequency bands based on a preset mapping relationship. The three independent frequency bands include the low frequency band, the mid frequency band, and the high frequency band.

[0135] The first analysis unit 4022 is used to analyze the room impulse response to obtain room environmental indicators;

[0136] The correction unit 4023 is used to correct the initial window cycle number based on room environment indicators to obtain the target window cycle number;

[0137] The calculation unit 4024 is used to calculate the window length parameter that varies with frequency based on the target window period number, and uses the window length parameter as the window control parameter.

[0138] Optionally, the mapping unit 4021 is specifically used for:

[0139] Provide at least two predefined window cycle number templates, each template containing a set of reference window cycle numbers for low frequency, mid frequency and high frequency bands, and each template corresponds to a different listening preference; perform interpolation calculation between the reference window cycle numbers of at least two templates based on the value or level of the listening preference parameter; determine the initial window cycle number for low frequency, mid frequency and high frequency bands based on the interpolation calculation results.

[0140] Optionally, the first analysis unit 4022 can be specifically used for:

[0141] Time-domain or frequency-domain analysis of the room impulse response is performed to obtain at least one reverberation time parameter, which characterizes the attenuation rate of sound energy in the room. A background noise interval is selected from the tail end of the room impulse response, and the root mean square value or equivalent sound pressure level of the signal in the background noise interval is calculated as an indicator of the background noise level. In the room impulse response, the early time window after the arrival of the direct sound is identified, and the ratio of the signal energy to the direct sound energy in the early time window is calculated as an indicator of the early reflection intensity.

[0142] Optionally, the correction unit 4023 can be specifically used for:

[0143] Based on the reverberation time parameter, the corresponding reverberation time correction factor is calculated for each frequency band; combined with the background noise level index and the early reflection intensity index, the environmental interference factor is calculated; the initial window period number of each frequency band is multiplied by the reverberation time correction factor and the environmental interference factor of the corresponding frequency band to obtain the target window period number.

[0144] Optionally, the computing unit 4024 can be specifically used for:

[0145] For the target window period number corresponding to the low-frequency, mid-frequency, and high-frequency bands, the period length corresponding to the center frequency of each frequency band is calculated respectively; the target window period number of each frequency band is multiplied by the corresponding period length to obtain the reference window length corresponding to the low-frequency, mid-frequency, and high-frequency bands respectively; smooth interpolation is performed on the transition frequency region between the low-frequency, mid-frequency, and high-frequency bands to generate a window length parameter that changes continuously over the entire frequency band as a window control parameter.

[0146] Optionally, the second determining module 403 can be specifically used for:

[0147] Based on the window length parameter in the window control parameters, a functional relationship between the window length and frequency is determined. Based on the functional relationship and the preset window function type, an executable windowing rule is determined as the windowing strategy. The windowing rule defines the window function duration used when trunculating different frequency signal components in the time domain, and the window length value corresponding to high frequency is less than the window length value corresponding to low frequency.

[0148] Optionally, processing module 404 can be specifically used for:

[0149] The identification unit 4041 is used to identify the start time point of the direct sound component from the room impulse response;

[0150] The truncation unit 4042 is used to truncate the impulse response in the time domain using a windowing strategy based on the starting time point;

[0151] The second analysis unit 4043 is used to perform frequency domain analysis on the truncated time-domain signal segment to obtain the effective frequency response curve.

[0152] Optionally, the identification unit 4041 can be specifically used for:

[0153] In the time-domain waveform of the room impulse response, locate the position where the energy first shows a significant surge; combine the phase characteristics or group delay characteristics of the impulse response to verify and correct the position of the first energy surge, thereby determining the starting time point of the direct sound; if the position of the first energy surge is unclear, make a comprehensive judgment based on the acoustic characteristics at multiple candidate time points to determine the starting time point of the direct sound.

[0154] Optionally, the truncation unit 4042 can be specifically used for:

[0155] For different frequency components contained in the room impulse response, the corresponding time-domain truncation window length is determined according to the windowing strategy; taking the starting time point as the starting position of the window, for each frequency component, the room impulse response is truncated according to its corresponding time-domain truncation window length to obtain a set of frequency-related time-domain signal segments.

[0156] Optionally, the second analysis unit 4043 can be specifically used for:

[0157] For each time-domain signal segment, a frequency domain transformation is performed to obtain the corresponding frequency domain representation. From the frequency domain representation of each time-domain signal segment, the amplitude spectrum information of the corresponding frequency or frequency band is extracted. The amplitude spectrum information of all frequencies or frequency bands is spliced ​​and smoothly fused in frequency order to form a continuous frequency response curve covering the target frequency band, which serves as the effective frequency response curve.

[0158] Optionally, the identification unit 4041 can be specifically used for:

[0159] Calculate the amplitude deviation of the effective frequency response curve relative to the target frequency response curve in each frequency band; based on the amplitude deviation, determine the frequency response characteristics that the filter needs to correct, and select the appropriate filter type and structure; combined with the style constraints corresponding to the listening preference parameters, limit the correction amplitude and range of the filter, thereby generating the final correction filter coefficients.

[0160] In this embodiment of the invention, by mapping user listening preference parameters to the initial window period number of different frequency bands and dynamically correcting them in combination with actual room environment indicators, the windowing strategy achieves dual adaptive optimization in the frequency dimension for both user subjective preferences and objective acoustic characteristics. This method enables the impulse response analysis window length to be intelligently adjusted according to the importance of frequency bands, listening needs, and specific room acoustic conditions, thereby more accurately balancing transient and steady-state sound field information when extracting effective frequency response curves. Ultimately, it generates calibration results that are more in line with personalized listening preferences and more in line with actual room acoustic characteristics, significantly improving the naturalness of sound reproduction and the satisfaction of the listening experience.

[0161] above Figure 4 and Figure 5 The room acoustic calibration device based on auditory tendency control in the embodiments of the present invention will be described in detail from the perspective of modular functional entities. The electronic devices in the embodiments of the present invention will be described in detail from the perspective of hardware processing.

[0162] See Figure 6 As shown, the electronic device includes a processor 600 and a memory 601. The memory 601 stores machine-executable instructions that can be executed by the processor 600. The processor 600 executes the machine-executable instructions to implement the above-described room acoustic calibration method based on auditory tendency control.

[0163] Furthermore, Figure 6 The electronic device shown also includes a bus 602 and a communication interface 603. The processor 600, the communication interface 603 and the memory 601 are connected via the bus 602.

[0164] The memory 601 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 603 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 602 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0165] The processor 600 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 600 or by instructions in software form. The processor 600 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this disclosure can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 601. Processor 600 reads the information in memory 601 and, in conjunction with its hardware, completes the method steps of the aforementioned embodiment.

[0166] The present invention also provides an electronic device, the computer device including a memory and a processor, the memory storing computer-readable instructions, which, when executed by the processor, cause the processor to perform the steps of the room acoustic calibration method based on auditory tendency control in the above embodiments.

[0167] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of the room acoustic calibration method based on auditory tendency control.

[0168] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0169] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0170] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A room acoustic calibration method based on auditory tendency control, characterized in that, The room acoustic calibration method based on auditory tendency control includes: Acquire the listening preference parameters selected by the user through the interactive interface and the room impulse response of the current room; Based on the hearing tendency parameters and the room impulse response, a set of frequency-related window control parameters are determined; Based on the window control parameters, a windowing strategy in which the window length varies with frequency is determined; The windowing strategy is used to window the room impulse response in order to extract the effective frequency response curve for acoustic calibration; The correction filter coefficients are calculated based on the difference between the effective frequency response curve and the target frequency response curve. The audio signal of the audio playback system is calibrated based on the correction filter coefficients. The step of determining a set of frequency-related window control parameters based on the listening preference parameter and the room impulse response includes: mapping the listening preference parameter to an initial window period number for three independent frequency bands based on a preset mapping relationship, wherein the three independent frequency bands include a low-frequency band, a mid-frequency band, and a high-frequency band; analyzing the room impulse response to obtain room environment indicators; correcting the initial window period number based on the room environment indicators to obtain a target window period number; calculating a window length parameter that varies with frequency based on the target window period number, and using the window length parameter as the window control parameter.

2. The room acoustic calibration method based on auditory tendency control according to claim 1, characterized in that, The method of mapping the listening preference parameter to the initial window period number of three independent frequency bands based on a preset mapping relationship includes: Provide at least two predefined window cycle number templates, each template containing a set of reference window cycle numbers for the low frequency band, mid frequency band and high frequency band, and each template corresponds to a different listening preference; Based on the value or level of the hearing tendency parameter, interpolation calculations are performed between the reference window period numbers of the at least two templates; The initial window period number for the low-frequency, mid-frequency, and high-frequency bands is determined based on the interpolation results.

3. The room acoustic calibration method based on auditory tendency control according to claim 1, characterized in that, The analysis of the room impulse response to obtain room environmental indicators includes: The room impulse response is analyzed in the time domain or frequency domain to obtain at least one reverberation time parameter, which characterizes the attenuation rate of sound energy in the room. A background noise range is selected from the tail end of the room impulse response, and the root mean square value or equivalent sound pressure level of the signal within the background noise range is calculated as an indicator of the background noise level. In the room impulse response, an early time window after the arrival of the direct sound is identified, and the ratio of signal energy to direct sound energy within the early time window is calculated as an early reflection intensity index.

4. The room acoustic calibration method based on auditory tendency control according to claim 3, characterized in that, The step of correcting the initial window cycle number based on the room environment indicators to obtain the target window cycle number includes: Based on the reverberation time parameters, calculate the corresponding reverberation time correction factor for each frequency band; The environmental interference factor is calculated by combining the background noise level index and the early reflection intensity index. The target window period number is obtained by multiplying the initial window period number of each frequency band by the reverberation time correction factor and environmental interference factor of the corresponding frequency band.

5. The room acoustic calibration method based on auditory tendency control according to claim 1, characterized in that, The step of calculating the window length parameter as a function of frequency based on the target window period number, and using the window length parameter as a window control parameter, includes: For the target window period number corresponding to the low frequency band, the mid frequency band, and the high frequency band, calculate the period length corresponding to the center frequency of each frequency band respectively; Multiply the number of target window periods for each frequency band by the corresponding period length to obtain the reference window lengths for the low-frequency band, the mid-frequency band, and the high-frequency band, respectively. Smooth interpolation is performed on the transition frequency region between the low-frequency band, the mid-frequency band, and the high-frequency band to generate a window length parameter that varies continuously across the entire frequency band as a window control parameter.

6. The room acoustic calibration method based on auditory tendency control according to claim 1, characterized in that, The step of determining a windowing strategy based on the window control parameters, where the window length varies with frequency, includes: Based on the window length parameter in the window control parameters, a functional relationship between the window length and the frequency is determined; Based on the functional relationship and the preset window function type, an executable windowing rule is determined as the windowing strategy. The windowing rule defines the window function duration used when trunculating different frequency signal components in the time domain, and the window length value corresponding to high frequency is less than the window length value corresponding to low frequency.

7. The room acoustic calibration method based on auditory tendency control according to claim 1, characterized in that, The step of using the windowing strategy to window the room impulse response to extract an effective frequency response curve for acoustic calibration includes: Identify the start time point of the direct sound component from the room impulse response; Using the starting time point as a reference, the windowing strategy is applied to truncate the impulse response in the time domain; Frequency domain analysis was performed on the extracted time-domain signal segment to obtain the effective frequency response curve.

8. The room acoustic calibration method based on auditory tendency control according to claim 7, characterized in that, The starting time point for identifying the direct sound component from the room impulse response includes: In the time-domain waveform of the room impulse response, locate the position where the energy first suddenly increases; By combining the phase characteristics or group delay characteristics of the impulse response, the location of the first energy surge is verified and corrected, thereby determining the starting time point of the direct sound; If the location of the first energy surge is unclear, a comprehensive judgment is made based on the acoustic characteristics at multiple candidate time points to determine the starting time point of the direct sound.

9. The room acoustic calibration method based on auditory tendency control according to claim 7, characterized in that, The step of applying the windowing strategy to truncate the impulse response in the time domain, based on the starting time point, includes: For different frequency components contained in the room impulse response, the corresponding time-domain truncation window length is determined according to the windowing strategy; Using the starting time point as the starting position of the window, for each frequency component, the corresponding time-domain truncation window length is used to truncate the room impulse response to obtain a set of frequency-related time-domain signal segments.

10. The room acoustic calibration method based on auditory tendency control according to claim 7, characterized in that, The step of performing frequency domain analysis on the truncated time-domain signal segment to obtain the effective frequency response curve includes: For each time-domain signal segment, a frequency-domain transformation is performed to obtain the corresponding frequency-domain representation; From the frequency domain representation of each time-domain signal segment, extract the amplitude spectrum information of its corresponding frequency or frequency band; The amplitude spectrum information of all frequencies or frequency bands is spliced ​​and smoothly fused in frequency order to form a continuous frequency response curve covering the target frequency band, which serves as the effective frequency response curve.

11. The room acoustic calibration method based on auditory tendency control according to claim 1, characterized in that, The calculation of the correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve includes: Calculate the amplitude deviation of the effective frequency response curve relative to the target frequency response curve in each frequency band; Based on the amplitude deviation, determine the frequency response characteristics that the filter needs to correct, and select the appropriate filter type and structure; By combining the style constraints corresponding to the aforementioned listening preference parameters, the correction amplitude and range of the filter are limited, thereby generating the final correction filter coefficients.

12. A room acoustic calibration device based on auditory tendency control, characterized in that, The room acoustic calibration device based on auditory tendency control includes: The acquisition module is used to acquire the listening preference parameters selected by the user through the interactive interface and the room impulse response of the current room; The first determining module is used to determine a set of frequency-related window control parameters based on the hearing tendency parameters and the room impulse response; The second determining module is used to determine a windowing strategy in which the window length varies with frequency based on the window control parameters; The processing module is used to perform windowing processing on the room impulse response using the windowing strategy to extract the effective frequency response curve for acoustic calibration; The calculation module is used to calculate the correction filter coefficients based on the difference between the effective frequency response curve and the target frequency response curve. A calibration module is used to calibrate the audio signal of the audio playback system based on the coefficients of the correction filter. The first determining module includes: a mapping unit, used to map the listening tendency parameter to an initial window period number of three independent frequency bands based on a preset mapping relationship, the three independent frequency bands including a low-frequency band, a mid-frequency band, and a high-frequency band; a first analysis unit, used to analyze the room impulse response to obtain room environment indicators; a correction unit, used to correct the initial window period number based on the room environment indicators to obtain a target window period number; and a calculation unit, used to calculate a window length parameter that varies with frequency based on the target window period number, and use the window length parameter as a window control parameter.

13. An electronic device, characterized in that, The electronic device includes: a memory and at least one processor, wherein the memory stores instructions; The at least one processor invokes the instructions in the memory to cause the electronic device to perform the room acoustic calibration method based on auditory tendency control as described in any one of claims 1-11.

14. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the room acoustic calibration method based on auditory tendency control as described in any one of claims 1-11.

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