Sound field simulation method and device and storage medium

Abstract

The invention relates to the technical field of audio simulation, in particular to a sound field simulation method and device and a storage medium. Comprising the steps of obtaining audio input data, user parameters corresponding to a preset space and system parameters corresponding to the preset space in response to a target operation of a user on an interactive interface; performing integration processing on the user parameters and the system parameters by using a pulse generation algorithm to generate an initial pulse response; cutting the initial pulse response according to system parameters to obtain early reflection and late reflection; performing convolution processing on the audio input data and the early reflection to obtain a convolution result; inputting the audio input data into a target feedback delay network after a preset delay time to obtain network output; and taking the sum of the network output and the convolution result as audio output data, and playing the audio output data. The embodiment of the invention is used for solving the problem of low precision of sound field simulation.

Description

Technical Field

[0001] The present application relates to the field of audio simulation technology, and in particular to a sound field simulation method, device and storage medium. Background Art

[0002] Sound field simulation can help audio producers adjust the sound effects more accurately during recording and mixing. By simulating different closed space characteristics such as size, shape, reflection and sound absorption, the reverberation, echo and spatial sense of the sound can be changed, making the audio content more realistic and immersive.

[0003] At present, the method of simulating sound fields is usually based on Schroeder reverberator. In Schroeder reverberator, a one-dimensional serial feedback structure is usually used. It uses the delay and mixing of reflected signals to simulate multiple reflections of sound, thereby producing a reverberation effect. Among them, the delay time and amplitude attenuation coefficient of each reflection are usually fixed and remain unchanged throughout the reverberation process. Therefore, due to the limitations of the one-dimensional structure, this method of simulating sound fields is usually limited in accuracy and authenticity, resulting in a certain gap between the simulation results and the real space sound, and a poor user experience. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a sound field simulation method, device and storage medium, which can improve the accuracy of sound field simulation.

[0005] In the first aspect, the present application provides a sound field simulation method, including: in response to a user's target operation on an interactive interface, obtaining audio input data, user parameters corresponding to a preset space, and system parameters corresponding to the preset space; the interactive interface is used to realize interaction with the user; using an impulse generation algorithm to integrate and process the user parameters and system parameters to generate an initial impulse response; cutting the initial impulse response according to the system parameters to obtain early reflections and late reflections; convolving the audio input data with the early reflections to obtain a convolution result; after the audio input data has been delayed for a preset time, inputting the data into a target feedback delay network to obtain a network output; the target feedback delay network is generated by analyzing and processing the late reflections; taking the sum of the network output and the convolution result as audio output data, and playing the audio output data; the audio output data is the simulated sound field corresponding to the preset space.

[0006] In the second aspect, the present application provides a sound field simulation device, including: an acquisition module, which is used to respond to the user's target operation on the interactive interface, to obtain audio input data, user parameters corresponding to the preset space, and system parameters corresponding to the preset space; a generation module, which is used to use an impulse generation algorithm to integrate the user parameters and the system parameters to generate an initial impulse response; a processing module, which is used to cut the initial impulse response according to the system parameters to obtain early reflections and late reflections; a convolution module, which is used to convolve the audio input data with the early reflections to obtain a convolution result; the processing module is also used to input the audio input data after a preset delay time into a target feedback delay network to obtain a network output; the target feedback delay network is generated by analyzing and processing the late reflections; the processing module is also used to take the sum of the network output and the convolution result as audio output data, and play the audio output data; the audio output data is the simulated sound field corresponding to the preset space.

[0007] In a third aspect, the present application provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the sound field simulation method of the first aspect is implemented.

[0008] In a fourth aspect, the present application provides a computer-readable storage medium, comprising: a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the sound field simulation method of the first aspect is implemented.

[0009] In a fifth aspect, the present application provides a computer program product, comprising: when the computer program product is run on a computer, the computer implements the sound field simulation method as in the first aspect.

[0010] The technical solution provided by the present application has the following advantages compared with the prior art: first, in response to the user's target operation on the interactive interface, the audio input data, the user parameters corresponding to the preset space, and the system parameters corresponding to the preset space are obtained, and the user parameters and the system parameters are integrated and processed using the pulse generation algorithm to generate an initial impulse response. After that, the initial impulse response is cut according to the system parameters to obtain early reflections and late reflections, and the audio input data and the early reflections are convolved to obtain the convolution result. After that, the audio input data is input into the target feedback delay network after a preset delay time to obtain the network output. Finally, the sum of the network output and the convolution result is used as the audio output data, and the audio output data is played. In this way, first, the user parameters corresponding to the preset space defined by the user can be obtained according to the target operation performed by the user, and the audio output data can be generated according to the user parameters, system parameters, and audio input data corresponding to the preset space, that is, from the user's perspective, that is, the user can define the physical conditions corresponding to the preset space by himself, thereby simulating the audio output data desired by the user, and improving the user experience. Secondly, in this application, the audio input data is convolved with the early reflections in the initial impulse response, rather than convolving the audio input data with the entire initial impulse response, saving a lot of computing resources. Finally, after the audio input data has been delayed for a preset time, it is input into the target feedback delay network to obtain the network output, and the sum of the network output and the convolution result is used as the audio output data, avoiding the problem that there is a certain gap between the sound field simulated by the Schroeder reverberator and the real sound, improving the accuracy of the sound field simulation, and further improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0012] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0013] Figure 1 One of the flow charts of the sound field simulation method provided in the embodiment of the present application;

[0014] Figure 2 One of the interactive interface schematic diagrams provided in the embodiment of the present application;

[0015] Figure 3 One of the flow charts of the sound field simulation method provided in the embodiment of the present application;

[0016] Figure 4 The second interactive interface diagram provided in the embodiment of the present application;

[0017] Figure 5 The third interactive interface diagram provided in the embodiment of the present application;

[0018] Figure 6 A pulse response schematic diagram provided in an embodiment of the present application;

[0019] Figure 7 A third flow chart of the sound field simulation method provided in an embodiment of the present application;

[0020] Figure 8 A fourth flowchart of the sound field simulation method provided in an embodiment of the present application;

[0021] Fig. 9 A fifth flow chart of the sound field simulation method provided in an embodiment of the present application;

[0022] Fig.10 Flow chart six of the sound field simulation method provided in the embodiment of the present application;

[0023] Fig.11 Schematic diagram of the seventh process of the sound field simulation method provided in the embodiment of the present application;

[0024] Fig.12 One of the network structure diagrams of the feedback delay network provided in the embodiment of the present application;

[0025] Fig.13 A second schematic diagram of the network structure of the feedback delay network provided in an embodiment of the present application;

[0026] Fig.14 A schematic diagram of the structure of a sound field simulation device provided in an embodiment of the present application;

[0027] Fig.15 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to more clearly understand the above-mentioned purposes, features and advantages of the present application, the scheme of the present application will be further described below. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0029] In the following description, many specific details are set forth to facilitate a full understanding of the present application, but the present application may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only part of the embodiments of the present application, rather than all of the embodiments.

[0030] Existing sound field simulation technologies can be mainly divided into simulation methods based on physical models and simulation methods based on digital signal processing. Simulation methods based on physical models usually use methods such as wave equations, sound rays, and statistical models to establish a preset space model to solve the sound field distribution of the preset space. However, these simulation methods based on physical models require high computational complexity and high storage capacity, and are difficult to calculate in real time, so they are rarely used in practical applications. Simulation methods based on digital signal processing are usually based on reverberation theory, using the time delay and reflection coefficient between reflections to simulate the preset space audio. However, due to the limitations of the one-dimensional structure, simulation methods based on digital signal processing are usually limited in accuracy and authenticity, resulting in a certain gap between the simulation results and the real space sound, and a poor user experience.

[0031] In view of the above problems, the embodiment of the present application provides a sound field simulation method, first responding to the user's target operation on the interactive interface, obtaining audio input data, user parameters corresponding to the preset space, and system parameters corresponding to the preset space, and using the pulse generation algorithm to integrate the user parameters and system parameters, and generate an initial impulse response. Afterwards, the initial impulse response is cut according to the system parameters to obtain early reflections and late reflections, and the audio input data is convolved with the early reflections to obtain a convolution result. Afterwards, the audio input data is input into the target feedback delay network after a preset delay time to obtain a network output. Finally, the sum of the network output and the convolution result is used as audio output data, and the audio output data is played. The audio input data can be convolved with the early reflections in the initial impulse response, rather than the audio input data being convolved with the entire initial impulse response, saving a large amount of computing power resources, avoiding the problem that the sound field simulated using the Schroeder reverberator has a certain gap with the real sound, improving the accuracy of the sound field simulation, and further improving the user experience.

[0032] The sound field simulation method provided in the embodiment of the present application can be implemented by a sound field simulation device, and the sound field simulation device provided in the embodiment of the present application can be hardware or software. When the sound field simulation device is hardware, it can be various electronic devices with the function of running sound field simulation, including but not limited to vehicle-mounted equipment, smart vehicles, mobile phones, computers, etc. When the sound field simulation device is software, it can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules, or it can be implemented as a single software or software module, which is not specifically limited here.

[0033] Figure 1 A schematic diagram of the flow of the sound field simulation method provided in the embodiment of the present application, such as Figure 1 As shown, the sound field simulation method may include the following steps.

[0034] S11. In response to a target operation of the user on the interactive interface, audio input data, user parameters corresponding to the preset space, and system parameters corresponding to the preset space are acquired.

[0035] The interactive interface is used to implement interaction with the user, and the interactive interface includes at least one of a space model corresponding to the preset space and a writing control. Figure 2 The interactive interface shown includes a space model 21. The user can change the user parameters corresponding to the preset space by dragging or rotating the space model 21. Figure 4 The interactive interface shown includes a space model 21 and a write control 22. The user can change the user parameters corresponding to the preset space by dragging or rotating the space model 21, and can also input the user parameters in the corresponding target window by triggering the write control 22.

[0036] The preset space is equipment, facilities, or other objects with a closed space. For example, the preset space can be a vehicle with a closed compartment, or a room, etc. This application does not limit this.

[0037] The user parameter may include at least one of the size, position, material, humidity, and temperature of the preset space. The size may include parameters such as the length, width, and height of the preset space, and the position may include a sound receiving position and a sound source position; the sound receiving position may be a position where the user wants the sound to reach, or a position selected by the user.

[0038] System parameters may include at least one of the following: sampling rate, reflection order, impulse length, window size, filter bank center frequency, and feedback delay line length. Sampling rate refers to the number of times a signal is sampled per second in digital signal processing. The sampling rate in this application refers to the sampling rate of the feedback delay network for audio input data. Reflection order refers to the number of reflections (each reflection causes the path of the sound wave to change and the energy to decay) experienced by the sound wave in the feedback delay network. Pulse length refers to the length of the initial pulse signal used in the feedback delay network. The pulse length determines the time domain characteristics of the reflected signal. A shorter pulse length can produce a clear reflection effect, while a longer pulse length can produce a lasting reverberation effect. The window function length refers to the length of the window function for processing the pulse signal. For example, in step S13, the window function can be used to cut the initial pulse response according to the pre-delay time and the mixing time to obtain the early reflection and the late reflection. Exemplarily, the window function can be a Hanning window, a rectangular window, a Hamming window, etc. The center frequency of the filter group refers to the center frequency of each filter in a group of filters used for frequency segmentation and signal processing. In the feedback delay network, a filter group is usually used to perform frequency domain analysis and processing on the input signal. The center frequency of each filter determines its position in the spectrum and also determines the response of the filter to the signal within a specific frequency range. The length of the delay line of the feedback delay network refers to the number of sampling points of each delay line. The length of the delay line determines the delay time of the reflected signal. A longer delay line can produce a longer delay time and reverberation effect.

[0039] First, in response to the user's target operation on the interactive interface, audio input data is obtained. In some embodiments, the audio input data can be real-time audio from any audio source, or pre-recorded audio, such as music, voice, ambient sound, etc.

[0040] In some embodiments, the target operation may include one of a transmission operation and a download operation. In response to the user's target operation on the interactive interface, the method of obtaining the audio input data may be: in response to the user's transmission operation, establishing a connection with the user device and receiving the audio input data sent by the user device; or, when it is determined that a network connection is established, downloading the audio input data in response to the user's download operation on the network resource.

[0041] Afterwards, in response to the user's target operation on the interactive interface, the user parameters corresponding to the preset space are obtained. In some embodiments, the user parameters are parameters input by the user according to the needs.

[0042] In some embodiments, the interactive interface includes a spatial model corresponding to the preset space, and the target operation includes at least one of a touch operation, a voice operation, a gesture operation, and a sight operation. In response to the user's target operation on the interactive interface, the method of obtaining the user parameter corresponding to the preset space may be: in response to the user's target operation on the interactive interface, determining the target position and target attributes of the spatial model in the interactive interface, and determining the sum of the target position and the target attributes as the user parameter corresponding to the preset space.

[0043] First, if Figure 3 As shown, in response to the user's target operation on the interactive interface, the method of determining the target position of the spatial model in the interactive interface may include the following steps:

[0044] S111. When a target operation is detected, determine a target movement parameter according to the target operation.

[0045] The target movement parameter includes at least one of a target direction, a target distance, and a target angle.

[0046] In some embodiments, when the target operation is a touch operation, the target operation is detected and the target movement parameters are determined based on the target operation. The method can be: when a touch event is detected, it is determined that a touch operation is detected, and then, the target movement parameters are determined based on a predefined relationship between the touch event and the movement parameters.

[0047] In some embodiments, when the target operation is a voice operation, the target operation is detected, and the target movement parameters are determined according to the target operation in the following manner: first, the user's voice is recognized through a voice recognition service, and whether the voice operation is detected is determined according to the voice recognition result. When the voice recognition result includes a pre-stored voice instruction, it is determined that the voice operation is detected, and when the voice recognition result does not include a pre-stored voice instruction, it is determined that the voice operation is not detected. Thereafter, the target movement parameters are determined according to the pre-defined relationship between the voice instruction and the movement parameters.

[0048] In some embodiments, when the target operation is a gesture operation, the target operation is detected, and the target movement parameters are determined according to the target operation by: recognizing the user gesture through a gesture recognizer, and determining whether the gesture operation is detected according to the gesture recognition result. When the gesture recognition result includes a pre-stored gesture instruction, it is determined that the gesture operation is detected, and when the gesture recognition result does not include a pre-stored gesture instruction, it is determined that the gesture operation is not detected. Thereafter, the target movement parameters are determined according to the relationship between the pre-defined gesture instruction and the movement parameters.

[0049] In some embodiments, when the target operation is a line-of-sight operation, the target operation may be detected by capturing and analyzing the user's eye movement data through an eye tracking system, and determining whether the line-of-sight operation is detected based on the eye movement data. Then, the target movement parameter is determined based on the predefined relationship between the eye movement data and the movement parameter.

[0050] S112. Changing the position of the spatial model in the interactive interface according to the target movement parameter.

[0051] In some embodiments, changing the position of the spatial model in the interactive interface according to the target movement parameters may include scaling the size of the spatial model, changing the shape of the spatial model, moving the position of the spatial model, rotating the perspective of the spatial model, etc. according to the target movement parameters.

[0052] For example, in Figure 2 The interactive interface shown includes a space model 21, and the eight corners of the space model 21 are the first corner A, the second corner B, the third corner C, the fourth corner D, the fifth corner a, the sixth corner b, the seventh corner c, and the eighth corner d. The corners of the space model 21 refer to the intersections of the three faces. When the target direction in the target movement parameter is the bd direction, the target distance is bb', and the target angle is 45° in the ba direction, then after the position of the space model in the interactive interface is changed according to the target movement parameter, the position of the space model in the interactive interface is as follows: Figure 4 As shown, the eight angles are the first angle A, the second angle B, the third angle C, the fourth angle D, the fifth angle a, the sixth angle b', the seventh angle c, and the eighth angle d.

[0053] S113: Determine the position of the changed space model in the interactive interface as the target position, and determine the position parameters corresponding to the target position as the target position parameters.

[0054] Afterwards, in response to the user's target operation on the interactive interface, target attribute parameters of the space model in the interactive interface are determined.

[0055] In some embodiments, in response to a user's target operation on the interaction interface, a method for determining target attribute parameters of the spatial model in the interaction interface may be to obtain the target attribute parameters of the spatial model in the interaction interface from a corresponding relationship according to the target operation.

[0056] The target operation is one of the user operations, and the user operation includes at least one of touch operation, voice operation, gesture operation, and sight operation. The attribute parameter includes at least one of material, humidity, and temperature. The corresponding relationship is the corresponding relationship between the user operation and the attribute parameter of the space model, and the corresponding relationship is pre-stored.

[0057] Finally, the sum of the target position parameter and the target attribute parameter is determined as the user parameter corresponding to the preset space.

[0058] In some embodiments, the interactive interface includes a write control, and the target operation includes a write operation. Then, in response to the user's target operation on the interactive interface, the method of obtaining the user parameters corresponding to the preset space may also be: in response to the user's triggering operation on the write control in the interactive interface, the target window is displayed, and in response to the user's write operation, the user parameters written by the user are obtained. The target window is used to write the user parameters, and the user parameters include at least one of the size, position, material, humidity, and temperature of the preset space, or the user parameters include at least one of the size, position, sound absorption coefficient, humidity, and temperature of the preset space.

[0059] For example, in Figure 5 The interactive interface shown includes a space model 21 and a write control 22. The user can call out a target window and input user parameters in the corresponding target window by triggering the write control 22. The size, shape, position and other parameters of the write control 22 are not limited in this application.

[0060] In the above scheme, the user parameters corresponding to the preset space defined by the user can be obtained according to the target operation performed by the user, that is, the user can define the physical conditions corresponding to the preset space by himself, and can even generate a material that does not exist in the physical world by defining the sound absorption coefficient, thereby enhancing the user's sense of participation and improving the user experience.

[0061] Finally, in response to the user's target operation on the interactive interface, the system parameters corresponding to the preset space are obtained. In some embodiments, the system parameters are parameters related to the feedback delay network (FDN), and the system parameters are preset, for example, they can be default parameter values, or they can be parameter values ​​set by relevant personnel according to actual conditions.

[0062] S12. Use a pulse generation algorithm to integrate the user parameters and the system parameters to generate an initial pulse response.

[0063] Among them, the impulse response (RIR) is usually used to describe the corresponding relationship between the reverberation time and reverberation intensity of the sound propagating in a preset space and reaching the receiving point after various reflections, attenuation and interference. Figure 6 is an impulse response, such as Figure 6 As shown in the figure, the horizontal axis is used to represent the reverberation time in seconds (s), and the vertical axis is used to represent the reverberation intensity. Figure 6 In the impulse response shown, the reverberation intensity gradually decreases as the reverberation time increases.

[0064] In some embodiments, Figure 7 As shown, the method of integrating the user parameters and the system parameters using the pulse generation algorithm to generate the initial pulse response may include the following steps:

[0065] S121. Generate a primary impulse response according to user parameters and system parameters using an image source algorithm.

[0066] In some embodiments, the user parameters include the sound receiving position and the sound source position, and the system parameters include the pulse length and the sampling rate. Thus, the method of using the image source algorithm to generate the primary impulse response according to the user parameters and the system parameters can be to use the image source model (ISM) to generate the primary impulse response according to the following formula.

[0067]

[0068] Among them, r is used to represent the sound receiving position, r s Used to indicate the location of the sound source, h(r,r s ,n) is used to represent the primary impulse response at (r,r s ) at the position. q, j, k are the set in p, and q is used to represent the mirror image on the x-axis, j is used to represent the mirror image on the y-axis, and k is used to represent the mirror image on the z-axis. x , m y , m z is a set in m, and m x Used to indicate the number of reflections on the x-axis, m y Used to indicate the number of reflections on the y-axis, m z is used to represent the number of reflections on the z-axis. δ is the Dirac function, τ is used to represent the time of sound propagation, and τ is the continuous time, f s It is used to indicate the sampling rate, and d is used to indicate the distance the sound travels. and Used to represent the sound absorption coefficient of two surfaces on the x-axis; and Used to represent the sound absorption coefficient of two surfaces on the y-axis; and It is used to indicate the sound absorption coefficient of two surfaces on the z-axis. LPF is a low-pass filter (LPF).

[0069] The sound propagation time τ can be the pulse length in the system parameters, and the sound propagation distance d can be the distance between the sound receiving position r and the sound source position r in the user parameters. s The Euclidean distance between the sound receiving position r and the sound source position r s The Euclidean distance between r and r s For example, when the coordinates of r are (x r ,y r , z r ), r s The coordinates of (x s ,y s , z s ), then r and r s The Euclidean distance between

[0070] S122: Generate initial reverberation time and event occurrence rate according to user parameters and system parameters using a reverberation time algorithm.

[0071] Among them, the event rate is the probability of the primary impulse response event occurring.

[0072] In some embodiments, the user parameters include the size of the preset space, and the system parameters include the pulse length and the sampling rate.

[0073] First, the reverberation time algorithm can be used to calculate the event rate of the primary impulse response based on the size of the preset space, the pulse length, the sampling rate, and the following formula.

[0074]

[0075] Among them, μ is used to represent the event rate, V is used to represent the volume of the preset space, c is used to represent the speed of sound, t is used to represent the time of sound propagation, and t is a discrete time. V can be calculated according to the size of the preset space. For example, when the shape of the preset space is a rectangular parallelepiped, V = U × O × P, U is the length of the preset space, O is the width of the preset space, and P is the height of the preset space; t can be obtained by sampling the pulse length according to the sampling rate in the system parameters.

[0076] After that, the initial reverberation time is calculated according to the following formula.

[0077]

[0078] Among them, Δt A (z) is used to represent the initial reverberation time, μ is used to represent the event occurrence rate, and z is a random number between 0 and 1.

[0079] S123, performing integration processing based on the primary impulse response, the initial reverberation time, and the event occurrence rate to obtain an initial impulse response.

[0080] In some embodiments, Figure 8 As shown, the method of obtaining the initial impulse response by integrating the primary impulse response, the initial reverberation time, and the event occurrence rate may include the following steps:

[0081] S1231. Generate a target sequence based on the event occurrence rate and the initial reverberation time using the Poisson process.

[0082] In some embodiments, according to the event occurrence rate of the primary impulse response events, the primary impulse response events are distributed at time points corresponding to the initial reverberation time to obtain a target sequence.

[0083] S1232. Perform discrete transformation on the target sequence to obtain at least one subsequence.

[0084] In some embodiments, the target sequence may be discretely transformed to obtain at least one subsequence by applying a filter group (the center frequency of the filter group is the center frequency of the filter group defined in the system parameters) to the target sequence to divide the target sequence into at least one subsequence; or the target sequence may be discretely transformed (DFT) to divide the target sequence into at least one subsequence.

[0085] Exemplarily, the filter bank may be a quadrature mirror filter (QMF) filter bank, a finite impulse response (FIR) filter bank, an infinite impulse response (IIR) filter bank, or the like.

[0086] For example, when the target sequence is h d (n), for h d (n) Applying a filter bank (such as QMF, FIR, IIR, etc.) or performing DFT transformation to obtain at least one subsequence.

[0087] S1233. Use the primary impulse response to perform weighted summation on at least one subsequence to obtain an initial impulse response.

[0088] The primary impulse response is used to perform weighted summation on at least one subsequence to obtain an initial impulse response, that is, weighted summation is performed on at least one subsequence, the weight being the energy envelope corresponding to the primary impulse response, to obtain the initial impulse response.

[0089] In the above scheme, the image source algorithm is first used to generate a primary impulse response according to the user parameters and system parameters, and the reverberation time algorithm is used to generate the initial reverberation time and event rate according to the user parameters and system parameters. Then, the primary impulse response, the initial reverberation time, and the event rate are integrated and processed to obtain the initial impulse response. The initial impulse response can be generated according to the user parameters and the system parameters, that is, from the user's perspective, the user can define the physical conditions corresponding to the preset space through the interface, thereby simulating the audio data output data that the user wants, thereby improving the user experience.

[0090] In addition, the Poisson process is used to generate a target sequence based on the event rate and the initial reverberation time, and the target sequence is discretely transformed to obtain at least one subsequence. Finally, the primary impulse response is used to perform weighted summation on at least one subsequence to obtain the initial impulse response. The Poisson process can be used to generate the target sequence and finally obtain the initial impulse response, which avoids the influence of ray tracing on the sound field simulation and improves the accuracy of the sound field simulation.

[0091] In addition, the number of generated subsequences can be adjusted by controlling the number of filters in the filter group, thereby achieving a balance between computing power and realism. When computing power permits, the accuracy of the sound field simulation can be further improved by increasing the number of subsequences.

[0092] S13. Cut the initial pulse response according to the system parameters to obtain early reflection and late reflection.

[0093] Among them, early reflection is the set of sounds that arrive at the listener for the first time after the sound is emitted from the sound source; late reflection is the set of sounds that reach the listener after experiencing at least one reverberation during the propagation process. Reverberation includes at least one of the reflection, attenuation and superposition of sound; mixing time is the time it takes for the sound to be evenly distributed in the preset space after being emitted from the sound source and reflected and scattered.

[0094] In some embodiments, before the initial impulse response is cut according to the system parameters to obtain the early reflection and the late reflection, the method further includes: estimating the initial impulse response using a time estimation algorithm to obtain the pre-delay time and the mixing time.

[0095] In some embodiments, a pre-delay time estimation algorithm and a mixing time estimation algorithm may be used to estimate the initial impulse response to obtain a pre-delay time and a mixing time.

[0096] In some embodiments, the initial impulse response includes an initial reverberation time and an initial reverberation response. Fig. 9 As shown, the initial impulse response is cut according to the system parameters to obtain the early reflection and the late reflection, which may include the following steps:

[0097] S131. Determine an initial reverberation intensity set in a first time period in a preset impulse response as an early reflection.

[0098] The preset impulse response is the impulse response corresponding to the reflection level in the initial impulse response; the first time period is the time period between the initial reverberation time and the first initial reverberation time in the preset impulse response, and the length of the first time period is the same as the length of the pre-delay time. In this way, with the help of the pre-delay time and the reflection level, unnecessary delay time in the initial impulse response can be cut off. These unnecessary delay times only have a delay effect, but do not have any acoustic characteristics associated with the preset space. After cutting them off, the accuracy of the sound field simulation can be improved.

[0099] S132: Determine an initial reverberation intensity set within a second time period in the preset impulse response as a late reflection.

[0100] The second time period is the time period between the first initial reverberation time and the second initial reverberation time in the preset impulse response, and the duration of the second time period is the same as the duration of the mixing time. In this way, with the help of the mixing time and the reflection series, it is possible to avoid directly cutting the initial impulse response, but to use a complete window function to divide the preset impulse response, which can improve the accuracy of the sound field simulation.

[0101] In the above scheme, the initial reverberation intensity set in the first time period of the preset impulse response is determined as the early reflection, and the initial reverberation intensity set in the second time period of the preset impulse response is determined as the late reflection. The reflection order based on the image source algorithm is adopted instead of the traditional direct truncation, which can better retain the characteristics of the signal and thus improve the accuracy of the simulated sound field.

[0102] S14, performing convolution processing on the audio input data and the early reflection to obtain a convolution result.

[0103] First, before convolving the audio input data with the early reflection, it is necessary to unify the length of the audio input data and the length of the early reflection. In some embodiments, the audio input data or the early reflection may be zero-padded so that the length of the audio input data is the same as the length of the early reflection. For example, a zero-valued sample is added to the end of the audio signal so that its length is the same as the length of the early reflection.

[0104] Afterwards, the audio input data with unified length is convolved with the early reflection to obtain the convolution result.

[0105] In some embodiments, the convolution operation can be implemented by time domain convolution or by frequency domain convolution. When implemented by frequency domain convolution, it is also necessary to convert the audio input data and early reflections from time domain signals to frequency domain signals, and then perform frequency domain convolution calculations. After obtaining the frequency domain convolution results, the frequency domain convolution results are converted from frequency domain signals to time domain signals to obtain convolution results. Among them, the time domain-frequency domain signal conversion method can be to use Fourier transform (Fourier transform, FT) algorithm or fast Fourier transform (fast Fourier transform, FFT) algorithm to convert the audio input data and early reflections from time domain signals to frequency domain signals. The frequency domain-time domain signal conversion method can be to use inverse Fourier transform (inverse Fourier transform, IFT) algorithm to convert the frequency domain convolution results from frequency domain signals to time domain signals to obtain convolution results.

[0106] S15, after the audio input data has been delayed for a preset time, it is input into a target feedback delay network to obtain a network output.

[0107] Among them, the target feedback delay network is generated by analyzing and processing the late reflections.

[0108] In some embodiments, Fig.10 As shown, before the audio input data is input into the target feedback delay network to obtain the network output, the sound field simulation method further includes the following steps:

[0109] S81. Analyze and process the late reflection to obtain a first coefficient and a second coefficient.

[0110] In some embodiments, Fig.11 As shown, the method of analyzing and processing the late reflection to obtain the first coefficient and the second coefficient may include the following steps:

[0111] S811. Use a data processing algorithm to perform energy decay analysis on late reflections to determine secondary reverberation time and secondary reverberation intensity.

[0112] In some embodiments, the sound field simulation method also includes using a data processing algorithm to perform energy attenuation analysis on late reflections to determine the noise floor, which can be used to guide the selection of appropriate sound-absorbing materials, sound insulation measures, etc. to ensure that the desired acoustic environment is obtained within a preset space; it can also be used to guide the layout of speakers, microphones and other audio equipment to ensure that the impact of noise on sound signals is minimized and the sound quality is improved.

[0113] In some embodiments, the data processing algorithm is an algorithm that can perform energy decay function (EDF) analysis on late reflections. For example, the data processing algorithm can be a Karjalainen algorithm or a Bayesian algorithm.

[0114] The energy decay function satisfies the following formula:

[0115]

[0116] Among them, d K (t,θ) is used to represent the energy attenuation, N0 is used to represent the noise floor, Ti is used to represent the i-th moment in the secondary reverberation time, A i It is used to indicate the i-th reverberation intensity in the secondary reverberation intensity, L is used to indicate the late reflection length, t is used to indicate the time of sound propagation, and t is a discrete time, f s Used to indicate the sampling rate.

[0117] S812: Use an initial level analysis algorithm to perform level analysis on the secondary reverberation time, the secondary reverberation intensity, and the system parameters to obtain a first coefficient.

[0118] In some embodiments, the first coefficient may be calculated according to the following formula: Where l(ω) is used to represent the first coefficient, L is used to represent the late reflection length, b(ω) is used to represent the center frequency of the filter bank, and A(ω) is used to represent the secondary reverberation intensity; f s Used to indicate the sampling rate, T 60 (ω) is used to represent the secondary reverberation time.

[0119] T 60 (ω) is RT 60 2. Parameters in the Absorption function, RT60 (Reverberation Time 60) is a parameter that measures the reverberation time in an audio environment. It refers to the time interval from the beginning of the sound to the decay to a certain intensity. The Absorption function describes the material's ability to absorb sound. It usually takes frequency as the independent variable and returns the sound absorption coefficient as the function value.

[0120] S813: Use a preset function to perform attenuation analysis on the secondary reverberation time and system parameters to obtain a second coefficient.

[0121] In some embodiments, the preset function may be RT 60 2Absorption function, the second coefficient can be calculated according to the following formula: A(ω) = Lγ dB (ω), where A(ω) is used to represent the second coefficient, L is used to represent the late reflection length, f s Used to indicate sampling rate, T 60 (ω) is used to represent the secondary reverberation time.

[0122] S82: Using the first coefficient as a level coefficient of a preset feedback delay network and the second coefficient as an attenuation coefficient of the preset feedback delay network to obtain a target feedback delay network.

[0123] Among them, the level coefficient is used to control the level of the delay line output data, and the attenuation coefficient is used to control the attenuation speed of the sound on the delay line. The delay line is a component of the feedback delay network.

[0124] The feedback delay network is usually composed of at least one delay line, a feedback matrix, at least one mixer, and a filter group. Among them, the delay line is a linear buffer with a fixed delay time, which is usually used to store samples of audio input data and mix it with copies with different delay times. The feedback matrix is ​​used to feed the output of the delay line to the input end of the delay line again. By adjusting the corresponding attenuation coefficient of the feedback matrix, the strength of the feedback signal and the complexity of the delay path can be controlled. The mixer is used to multiply the output signal of the delay line by the level coefficient to obtain the network output of the feedback delay network. The filter group is used to further process the output signal of the delay line. Exemplarily, the filter group can be used to adjust the frequency response and reverberation characteristics.

[0125] For example, Fig.12 is a network structure of a feedback delay network, such as Fig.12 As shown, the feedback delay network includes a delay line, a filter bank, a feedback matrix, a first mixer Sum1, and a second mixer Sum2. In this way, after the audio input data x(n) is input into the feedback delay network, it first passes through the delay line and the filter bank to obtain a first result; the first mixer Sum1 adds a level coefficient to the first result to obtain a network output y(n) of the feedback delay network; the second mixer Sum2 adds an attenuation coefficient to the first result, inputs the feedback matrix, obtains a second result, and uses the sum of the second result and the audio input data x(n) as the input of the next delay line.

[0126] For example, Fig.13The network structure is a feedback delay network, which includes four delay lines and eight mixers. Fig.13 As shown, the feedback delay network includes delay line Z1, delay line Z2, delay line Z3, delay line Z4, filter FB1, filter FB2, filter FB3, filter FB4, feedback matrix, mixer Sum11, mixer Sum12, mixer Sum13, mixer Sum14, mixer Sum21, mixer Sum22, mixer Sum23, and mixer Sum24. In this way, after the audio input data x(n) enters the feedback delay network, it is first distributed to the delay lines Z1-Z4 (for the sake of convenience of distinction, the x(n) distributed to Z1-Z4 is called x1(n)-x4(n)), and then passes through the filter group FB1-FB4 to obtain the first result (including 4 first results, one filter corresponds to one first result), and then the level coefficient is added to the first result through the mixer Sum11-Sum14 to obtain the network output y1(n)-y4(n) of the feedback delay network; in addition, the mixer Sum21-Sum24 adds the attenuation coefficient to the first result, inputs the feedback matrix, and obtains the second result (including 4 second results, each mixer in the mixer Sum21-Sum24 corresponds to a second result), and the sum of the second result and the audio input data x1(n)-x4(n) is used as the input of the next delay line.

[0127] In the above scheme, the late reflection is analyzed and processed to obtain the first coefficient and the second coefficient, and the first coefficient is used as the level coefficient of the preset feedback delay network, and the second coefficient is used as the attenuation coefficient of the preset feedback delay network to obtain the target feedback delay network. The target feedback delay network can be generated according to the late reflection, so that the audio input data can be input into the target feedback delay network after the preset delay time to obtain the network output, avoiding the convolution of the audio input data with the entire initial impulse response, saving a lot of computing resources.

[0128] In addition, a data processing algorithm is used to perform energy decay analysis on late reflections to determine the secondary reverberation time and secondary reverberation intensity. Then, an initial level analysis algorithm is used to perform level analysis on the secondary reverberation time, secondary reverberation intensity, and system parameters to obtain the first coefficient, and a preset function is used to perform decay analysis on the secondary reverberation time and system parameters to obtain the second coefficient. In this way, the use of energy decay analysis can more accurately simulate the reverberation characteristics.

[0129] In some embodiments, the audio input data is input into a target feedback delay network after a mixing time to obtain a network output, that is, the preset delay time is the mixing time.

[0130] In the above scheme, the audio input data is input into the target feedback delay network after the mixing time to obtain the network output, which can simulate the reverberation characteristics more accurately.

[0131] S16. Use the sum of the network output and the convolution result as audio output data, and play the audio output data.

[0132] The audio output data is the simulated sound field corresponding to the preset space.

[0133] In the above scheme, first, in response to the user's target operation on the interactive interface, the audio input data, the user parameters corresponding to the preset space, and the system parameters corresponding to the preset space are obtained, and the user parameters and the system parameters are integrated and processed using the pulse generation algorithm to generate an initial impulse response. After that, the initial impulse response is cut according to the system parameters to obtain early reflections and late reflections, and the audio input data and the early reflections are convolved to obtain the convolution result. After that, the audio input data is input into the target feedback delay network after a preset delay time to obtain the network output. Finally, the sum of the network output and the convolution result is used as the audio output data, and the audio output data is played. In this way, first, according to the target operation performed by the user, the user parameters corresponding to the preset space defined by the user can be obtained, and the audio output data can be generated according to the user parameters, system parameters, and audio input data corresponding to the preset space, that is, from the user's perspective, that is, the user can define the physical conditions corresponding to the preset space by himself, thereby simulating the audio output data desired by the user, and improving the user experience. Secondly, in this application, the audio input data is convolved with the early reflections in the initial impulse response, rather than convolving the audio input data with the entire initial impulse response, saving a lot of computing resources. Finally, after the audio input data has been delayed for a preset time, it is input into the target feedback delay network to obtain the network output, and the sum of the network output and the convolution result is used as the audio output data, avoiding the problem that there is a certain gap between the sound field simulated by the Schroeder reverberator and the real sound, improving the accuracy of the sound field simulation, and further improving the user experience.

[0134] The embodiment of the present application can divide the functional modules of the sound field simulation device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0135] like Fig.14As shown, an embodiment of the present application provides a structural schematic diagram of a sound field simulation device 200 , which includes an acquisition module 201 , a generation module 202 , a processing module 203 , and a convolution module 204 .

[0136] The acquisition module 201 is used to respond to the user's target operation on the interactive interface, obtain audio input data, user parameters corresponding to the preset space, and system parameters corresponding to the preset space; the interactive interface is used to realize interaction with the user; the generation module 202 is used to use the pulse generation algorithm to integrate the user parameters and the system parameters to generate an initial pulse response; the processing module 203 is used to cut the initial pulse response according to the system parameters to obtain early reflections and late reflections; the convolution module 204 is used to convolve the audio input data with the early reflection to obtain the convolution result; the processing module 203 is also used to input the audio input data after a preset delay time into the target feedback delay network to obtain the network output; the target feedback delay network is generated by the late reflection after analysis and processing; the processing module 203 is also used to use the sum of the network output and the convolution result as the audio output data, and play the audio output data; the audio output data is the simulated sound field corresponding to the preset space.

[0137] In some embodiments, the interactive interface includes a spatial model corresponding to the preset space. The acquisition module 201 is specifically configured to determine a target position parameter and a target attribute parameter of the spatial model in the interactive interface in response to a target operation of the user on the interactive interface, and determine the sum of the target position parameter and the target attribute parameter as the user parameter corresponding to the preset space.

[0138] In some embodiments, the acquisition module 201 is specifically used to determine the target movement parameters according to the target operation when a target operation is detected; the target movement parameters include at least one of the target direction, target distance, and target angle; the position of the spatial model in the interactive interface is changed according to the target movement parameters; the position of the changed spatial model in the interactive interface is determined as the target position, and the position parameters corresponding to the target position are determined as the target position parameters.

[0139] In some embodiments, the acquisition module 201 is specifically used to obtain the target attribute parameters of the spatial model in the interactive interface from the corresponding relationship according to the target operation; the corresponding relationship is the corresponding relationship between the user operation and the spatial model attribute parameters; the user operation includes the target operation.

[0140] In some embodiments, the interactive interface includes a write control, and the target operation includes a write operation. The acquisition module 201 is specifically used to display a target window in response to a user triggering operation on the write control in the interactive interface; the target window is used to write user parameters; and in response to the user's write operation, acquire the user parameters written by the user.

[0141] In some embodiments, the generation module 202 is specifically used to generate a primary impulse response according to user parameters and system parameters using an image source algorithm; generate an initial reverberation time and an event occurrence rate according to user parameters and system parameters using a reverberation time algorithm; wherein the event occurrence rate is the probability of occurrence of a primary impulse response event; and perform integration processing based on the primary impulse response, the initial reverberation time, and the event occurrence rate to obtain an initial impulse response.

[0142] In some embodiments, the generation module 202 is specifically used to generate a target sequence based on an event occurrence rate and an initial reverberation time using a Poisson process; perform a discrete transformation on the target sequence to obtain at least one subsequence; and perform a weighted summation of at least one subsequence using a primary impulse response to obtain an initial impulse response.

[0143] In some embodiments, the processing module 203 is further configured to use a time estimation algorithm to estimate the initial impulse response to obtain a pre-delay time and a mixing time.

[0144] In some embodiments, the system parameters include the reflection order, and the initial impulse response includes the initial reverberation time and the initial reverberation response; the processing module 203 is specifically used to determine the initial reverberation intensity set in the first time period in the preset impulse response as the early reflection; the preset impulse response is the impulse response corresponding to the reflection order in the initial impulse response; the first time period is the time period between the starting initial reverberation time and the first initial reverberation time in the preset impulse response, and the length of the first time period is the same as the length of the pre-delay time; the initial reverberation intensity set in the second time period in the preset impulse response is determined as the late reflection; the second time period is the time period between the first initial reverberation time and the second initial reverberation time in the preset impulse response, and the length of the second time period is the same as the length of the mixing time.

[0145] In some embodiments, the processing module 203 is specifically configured to input the audio input data into a target feedback delay network after a mixing time to obtain a network output.

[0146] In some embodiments, the processing module 203 is also used to analyze and process the late reflection to obtain a first coefficient and a second coefficient; the first coefficient is used as the level coefficient of the preset feedback delay network, and the second coefficient is used as the attenuation coefficient of the preset feedback delay network to obtain a target feedback delay network.

[0147] In some embodiments, the processing module 203 specifically uses a data processing algorithm to perform energy attenuation analysis on late reflections to determine the secondary reverberation time and the secondary reverberation intensity; uses an initial level analysis algorithm to perform level analysis on the secondary reverberation time, the secondary reverberation intensity, and the system parameters to obtain a first coefficient; and uses a preset function to perform attenuation analysis on the secondary reverberation time and the system parameters to obtain a second coefficient.

[0148] The sound field simulation device provided in this embodiment can execute the sound field simulation method provided in the above method embodiment. Its implementation principle and technical effect are similar to those of the above method and will not be described in detail here.

[0149] Fig.15 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0150] like Fig.15 As shown, an embodiment of the present application provides an electronic device, which includes: a processor 1201, a memory 1202, and a computer program stored in the memory 1202 and executable on the processor 1201, and when the computer program is executed by the processor 1201, each process of the sound field simulation method in the above method embodiment is implemented. And the same technical effect can be achieved, and it will not be repeated here to avoid repetition.

[0151] An embodiment of the present application provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, each process of the sound field simulation method in the above method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0152] The computer readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0153] An embodiment of the present application provides a computer program product, which stores a computer program. When the computer program is executed by a processor, each process of the sound field simulation method in the above method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0154] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media that include computer-usable program code.

[0155] In the present application, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0156] In this application, memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0157] In this application, computer-readable media includes permanent and non-permanent, removable and non-removable storage media. Storage media can be implemented by any method or technology to store information, and the information can be computer-readable instructions, data structures, modules of programs or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. According to the definition in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data and carrier waves.

[0158] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0159] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A sound field simulation method, characterized in that: include: In response to a target operation of the user on the interactive interface, obtaining audio input data, user parameters corresponding to the preset space, and system parameters corresponding to the preset space; The interactive interface is used to implement interaction with the user; Using an impulse generation algorithm to integrate the user parameters and system parameters to generate an initial impulse response; Cutting the initial impulse response according to the system parameters to obtain early reflections and late reflections; Convolution processing is performed on the audio input data and the early reflection to obtain a convolution result; After the audio input data has been delayed for a preset time, it is input into a target feedback delay network to obtain a network output; The target feedback delay network is generated by analyzing and processing the late reflection; The sum of the network output and the convolution result is used as audio output data, and the audio output data is played; the audio output data is a simulated sound field corresponding to the preset space.

2. The sound field simulation method according to claim 1, characterized in that: The interactive interface includes a space model corresponding to the preset space; in response to a target operation of the user on the interactive interface, obtaining user parameters corresponding to the preset space includes: In response to a target operation of the user on the interactive interface, determining a target position parameter and a target attribute parameter of the spatial model in the interactive interface; The sum of the target position parameter and the target attribute parameter is determined as the user parameter corresponding to the preset space.

3. The sound field simulation method according to claim 2, characterized in that: The step of determining target position parameters of the spatial model in the interactive interface in response to a target operation of the user on the interactive interface includes: When a target operation is detected, a target movement parameter is determined according to the target operation; the target movement parameter includes at least one of a target direction, a target distance, and a target angle; changing the position of the spatial model in the interactive interface according to the target movement parameter; The position of the changed spatial model in the interactive interface is determined as the target position, and the position parameters corresponding to the target position are determined as the target position parameters.

4. The sound field simulation method according to claim 2, characterized in that: The step of determining target attribute parameters of the spatial model in the interactive interface in response to a target operation of the user on the interactive interface includes: According to the target operation, the target attribute parameters of the space model in the interactive interface are obtained from the corresponding relationship; the corresponding relationship is the corresponding relationship between the user operation and the space model attribute parameters; the user operation includes the target operation.

5. The sound field simulation method according to any one of claims 1 to 4, characterized in that: The interactive interface includes a write control; the target operation includes a write operation; and in response to the user's target operation on the interactive interface, obtaining user parameters corresponding to the preset space includes: In response to a user triggering operation on the write control in the interactive interface, a target window is displayed; the target window is used to write user parameters; In response to a write operation by a user, a user parameter written by the user is acquired.

6. The sound field simulation method according to any one of claims 1 to 4, characterized in that: The user parameters and the system parameters are integrated and processed using an impulse generation algorithm to generate an initial impulse response, including: generating a primary impulse response based on the user parameters and the system parameters using an image source algorithm; Generate an initial reverberation time and an event occurrence rate according to the user parameters and the system parameters using a reverberation time algorithm; wherein the event occurrence rate and the probability of occurrence of a primary impulse response event; An initial impulse response is obtained by performing integration processing based on the primary impulse response, the initial reverberation time, and the event occurrence rate.

7. The sound field simulation method according to claim 6, characterized in that: The integrating process based on the primary impulse response, the initial reverberation time, and the average number of occurrences of the event to obtain the initial impulse response includes: Using a Poisson process, a target sequence is generated according to the event occurrence rate and the initial reverberation time; Performing a discrete transformation on the target sequence to obtain at least one subsequence; The at least one subsequence is weightedly summed using the primary impulse response to obtain an initial impulse response.

8. The sound field simulation method according to any one of claims 1 to 4, characterized in that: Before the initial impulse response is cut according to the system parameters to obtain early reflections and late reflections, the method further includes: The initial impulse response is estimated using a time estimation algorithm to obtain the pre-delay time and the mixing time.

9. The sound field simulation method according to claim 8, characterized in that: The system parameters include reflection levels, and the initial impulse response includes initial reverberation time and initial reverberation response; The cutting process of the initial impulse response according to the system parameter to obtain the early reflection and the late reflection includes: Determine an initial reverberation intensity set within a first time period in a preset impulse response as an early reflection; the preset impulse response is an impulse response corresponding to the reflection level in the initial impulse response; the first time period is a time period between a starting initial reverberation time and a first initial reverberation time in the preset impulse response, and the duration of the first time period is the same as the duration of the pre-delay time; An initial reverberation intensity set within a second time period in the preset impulse response is determined as a late reflection; the second time period is a time period between a first initial reverberation time and a second initial reverberation time in the preset impulse response, and the duration of the second time period is the same as the duration of the mixing time.

10. The sound field simulation method according to claim 8, characterized in that: The step of inputting the audio input data into a target feedback delay network after a preset delay time to obtain a network output includes: After the audio input data has passed the mixing time, it is input into a target feedback delay network to obtain a network output.

11. The sound field simulation method according to any one of claims 1 to 4, characterized in that: Before inputting the audio input data into a target feedback delay network to obtain a network output, the method further includes: Analyzing and processing the late reflection to obtain a first coefficient and a second coefficient; The first coefficient is used as a level coefficient of a preset feedback delay network, and the second coefficient is used as an attenuation coefficient of the preset feedback delay network to obtain a target feedback delay network.

12. The sound field simulation method according to claim 11, characterized in that: The analyzing and processing the late reflection to obtain the first coefficient and the second coefficient includes: performing an energy decay analysis on the late reflections using a data processing algorithm to determine a secondary reverberation time and a secondary reverberation intensity; Using an initial level analysis algorithm, performing level analysis on the secondary reverberation time, the secondary reverberation intensity, and the system parameters to obtain a first coefficient; A preset function is used to perform attenuation analysis on the secondary reverberation time and the system parameter to obtain a second coefficient.

13. A sound field simulation device, characterized in that: include: an acquisition module, for acquiring audio input data, user parameters corresponding to a preset space, and system parameters corresponding to the preset space in response to a target operation of the user on the interactive interface; the interactive interface is used to implement interaction with the user; A generating module, used for integrating the user parameters and the system parameters using an impulse generating algorithm to generate an initial impulse response; A processing module, used for cutting the initial impulse response according to the system parameters to obtain early reflections and late reflections; A convolution module, used for performing convolution processing on the audio input data and the early reflection to obtain a convolution result; The processing module is further used to input the audio input data into a target feedback delay network after a preset delay time to obtain a network output; the target feedback delay network is generated by analyzing and processing the late reflection; The processing module is also used to use the sum of the network output and the convolution result as audio output data, and play the audio output data; the audio output data is the simulated sound field corresponding to the preset space.

14. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the sound field simulation method according to any one of claims 1 to 12 when executed by the processor.

15. A computer-readable storage medium, characterized in that: include: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the sound field simulation method according to any one of claims 1 to 12 is implemented.

Images