Pulse feedback determination method and apparatus, device, storage medium, and program product

Abstract

Embodiments of the application disclose a pulse feedback determination method and device, equipment, a storage medium and a program product, and belong to the technical field of acoustics. The method comprises the following steps: determining path filtering features of sound wave paths in a virtual room, wherein the path filtering features are used to represent sound absorption of sound waves propagating on the sound wave paths, and the sound wave paths are paths generated after sound reflection on sound reflection surfaces in the virtual room; performing feature fusion on the path filtering features based on energy of sound waves reaching a sound pickup device on each of the sound wave paths, to obtain a total filtering feature of the virtual room, wherein the total filtering feature is used to represent sound absorption of the virtual room to sound waves; and filtering total pulse feedback of the virtual room based on the total filtering feature, to obtain target pulse feedback, wherein the total pulse feedback is obtained through sound wave tracking.

Description

Technical Field

[0001] This application relates to the field of acoustic technology, and in particular to a method, apparatus, device, storage medium, and program product for determining pulse feedback. Background Technology

[0002] Normally, after sound is emitted from the sound source, it undergoes a series of reflections in the virtual room before finally reaching the microphone. During this process, the pulse feedback of the room can be determined, which is beneficial for debugging and optimizing the audio system.

[0003] In related technologies, by tracing the path of sound waves, the pulse feedback coefficient corresponding to the path of sound waves from the sound source to the microphone in the virtual room is determined, and then the different pulse feedback coefficients are linearly added together to obtain the pulse feedback of the entire virtual room.

[0004] However, to enhance the realism of reverberation in a virtual room, the reflective surfaces are typically made of materials commonly found in reality, whose sound absorption coefficient is related to the frequency of the sound. Therefore, in this case, the filtering characteristics corresponding to each sound wave path are different, and directly using linear addition will result in low accuracy of the final impulse feedback in the virtual room. Summary of the Invention

[0005] This application provides a method, apparatus, device, storage medium, and program product for determining pulse feedback. The technical solution is as follows:

[0006] On one hand, embodiments of this application provide a method for determining impulse feedback, the method comprising:

[0007] The path filtering characteristics of each sound wave path in the virtual room are determined. The path filtering characteristics are used to characterize the sound absorption of the sound wave when it propagates along the sound wave path. The sound wave path is the path generated after the sound wave is reflected by the sound reflecting surface in the virtual room.

[0008] Based on the energy of the sound wave when it reaches the microphone in each of the sound wave paths, the path filtering features are fused to obtain the total filtering features of the virtual room. The total filtering features are used to characterize the sound absorption of the virtual room.

[0009] Based on the total filtering characteristics, the total impulse feedback of the virtual room is filtered to obtain the target impulse feedback, which is obtained through sound wave tracking.

[0010] On the other hand, embodiments of this application provide a pulse feedback determination device, the device comprising:

[0011] The feature determination module is used to determine the path filtering features of each sound wave path in the virtual room. The path filtering features are used to characterize the sound absorption of the sound wave when it propagates on the sound wave path. The sound wave path is the path generated after the sound wave is reflected by the sound reflecting surface in the virtual room.

[0012] The feature fusion module is used to perform feature fusion on the path filtering features based on the energy of the sound waves when they reach the microphone in each of the sound wave paths, so as to obtain the total filtering features of the virtual room. The total filtering features are used to characterize the sound absorption of the virtual room.

[0013] A filtering module is used to filter the total pulse feedback of the virtual room based on the total filtering characteristics to obtain the target pulse feedback, wherein the total pulse feedback is obtained through sound wave tracking.

[0014] On the other hand, embodiments of this application provide a computer device including a processor and a memory; the memory stores at least one instruction, which is executed by the processor to implement the pulse feedback determination method as described above.

[0015] On the other hand, embodiments of this application provide a computer-readable storage medium storing at least one piece of program code, which is loaded and executed by a processor to implement the pulse feedback determination method as described above.

[0016] On the other hand, embodiments of this application provide a computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the pulse feedback determination method provided in various optional implementations of the above aspects.

[0017] In this embodiment, the computer device fuses the path filtering characteristics of each sound wave path into a total filtering characteristic based on the path filtering characteristics of each sound wave path and the energy of the sound waves reaching the microphone in each sound wave path. This total filtering characteristic can characterize the sound absorption of the virtual room. After obtaining the total filtering characteristic, the total impulse feedback obtained through sound wave tracking is then filtered. The resulting target impulse feedback can reflect the sound absorption characteristics of the virtual room for sound waves of different frequencies. Furthermore, using the scheme provided in this application to determine the impulse feedback of the virtual room can improve the accuracy of determining the impulse feedback. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram of an exemplary embodiment of this application is shown;

[0020] Figure 2 A schematic diagram of virtual room pulse feedback provided in an exemplary embodiment of this application is shown;

[0021] Figure 3 A flowchart illustrating a method for determining pulse feedback provided in an exemplary embodiment of this application is shown.

[0022] Figure 4 A flowchart illustrating the process of determining path filtering features provided in an exemplary embodiment of this application is shown;

[0023] Figure 5 This invention provides a flowchart illustrating a process for feature fusion of path filtering features according to an exemplary embodiment of the present application.

[0024] Figure 6 A flowchart illustrating the pulse feedback determination process provided in an exemplary embodiment of this application is shown;

[0025] Figure 7 A structural block diagram of a pulse feedback determination device provided in an exemplary embodiment of this application is shown;

[0026] Figure 8 A structural block diagram of a computer device provided in an exemplary embodiment of this application is shown. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0028] The sound absorption coefficient is the ratio of the sound energy absorbed and transmitted by a material to the total sound energy incident on the material.

[0029] The reflection coefficient refers to the ratio of the energy of the reflected light to the energy of the incident light when incident light is incident on a material.

[0030] Impulse feedback refers to the time-domain feedback characteristic of a system under test when a pulse excitation signal is input. This feedback characteristic refers to the relationship between time and energy. The system under test can be a microphone, a loudspeaker, a filter on an equalizer, or even a room, a complete sound system, or the combination of a room and a sound system.

[0031] It should be noted that the method for determining the pulse feedback provided in this application embodiment can be applied to any of the above-mentioned systems under test. For ease of understanding, this application embodiment takes a virtual room as an example to illustrate the method for determining the pulse feedback.

[0032] It should be noted that in the embodiments of this application, the scattering and resonance phenomena of the sound wave remaining on the reflecting surface are not considered when the sound wave propagates. During the process of the sound wave being reflected by the sound reflecting surface, the energy of the sound wave is only affected by the two phenomena of absorption and reflection.

[0033] The impulse feedback in a virtual room includes the propagation results of sound waves along multiple sound wave paths from the sound source location to the pickup location. Figure 1 The diagram illustrates a sound wave path provided in an exemplary embodiment of this application. After sound source 101 emits sound, multiple sound wave paths propagate. One sound wave may originate from the sound source via a first sound wave path 103, arriving directly at the microphone 102 without reflection. Other sound waves may be reflected upon reaching the sound reflecting surface, arriving at the microphone 102 after at least one reflection. For example, a sound wave may propagate via a second sound wave path 104, arriving at the microphone 102 after one reflection; or a sound wave may propagate via a third sound wave path 105, arriving at the microphone 102 after two reflections. Because different sound waves have different paths, the time it takes for sound waves propagating via different paths to reach the microphone may also differ. The propagation time of a sound wave from the sound source to the microphone is related to the number of reflections it undergoes; the more reflections, the longer the propagation time.

[0034] Because sound waves from the same sound source undergo different reflections along different paths, and the reflecting surfaces attenuate the energy of the sound waves—the degree of attenuation being determined by the sound absorption coefficient of the reflecting surface—the energy of the sound waves reaching the microphone varies depending on the number of reflections along each path. When the energy of the sound waves emitted from the source is uniform, sound waves that undergo more reflections reach the microphone with lower energy, those that undergo fewer reflections have higher energy, and those that reach the microphone directly without reflection have the highest energy. Therefore, the energy values ​​of the sound waves propagating along different paths in the pulse feedback corresponding to this virtual room differ.

[0035] Indicative, Figure 2This illustration shows a schematic diagram of virtual room impulse feedback provided in an exemplary embodiment of this application, which is similar to the above-described... Figure 1 Correspondingly, the horizontal axis represents time, and the vertical axis represents energy. The first pulse feedback 201 received by the pickup at time t1 corresponds to... Figure 1 The sound wave propagating through the first sound wave path 103 reaches the microphone directly without reflection, resulting in the shortest propagation time and minimal energy attenuation. The second pulse feedback 202 received by the microphone at time t2 corresponds to... Figure 1 The sound wave propagating through the second sound wave path 104 undergoes one feedback, therefore the energy of this sound wave received by the microphone is lower than the energy of the sound wave propagating through the first sound wave path. The third pulse feedback 203 received by the microphone at time t3 corresponds to... Figure 1 The sound wave energy in the third sound wave path 105, compared to the first and second pulse feedback, undergoes two reflections. Its arrival time at the pickup, t3, is greater than t2, which is greater than t1. Furthermore, the energy attenuation of this sound wave is significant after the two reflections. For sound waves arriving after time t3 in the schematic diagram of this pulse feedback, the energy attenuation is even greater.

[0036] In the solutions provided by related technologies, since different sound waves undergo different reflections before reaching the microphone, the pulse feedback corresponding to the sound waves received at the same time after sound wave tracking is added together to obtain the pulse feedback of the virtual room.

[0037] In determining the impulse feedback, the sound-reflecting surfaces in the virtual room are usually made of materials commonly found in the real world. For example, the floor in the virtual room may be made of wood flooring, tiles, carpets, etc. Different materials have different sound absorption coefficients for different frequencies of sound waves. For example, the sound absorption coefficient of wood flooring is 0.04 for 125Hz, 0.04 for 250Hz, 0.08 for 500Hz, and so on.

[0038] In this scenario, the pulse feedback from different paths to the microphone varies depending on the number of reflections. Furthermore, because the absorption coefficient of a sound reflector differs at different frequencies, the filtering effect of the reflector on the sound wave varies. For example, consider a first sound wave path and a second sound wave path. The first sound wave path is reflected by the wooden floor. Because the wooden floor has a high-pass filtering effect on the sound waves from the first sound wave path (meaning the energy of low-frequency sound waves is less than that of high-frequency sound waves), the second sound wave path, which does not pass through the wooden floor, will not exhibit the same filtering effect as the first sound wave path. When the sound waves from the first and second sound wave paths arrive at the microphone simultaneously, directly adding the pulse feedback from the first and second sound wave paths linearly to obtain the pulse feedback at that moment will result in a poorly accurate total pulse feedback, failing to accurately reflect the filtering effect of the virtual room.

[0039] Therefore, to avoid the poor accuracy caused by linearly adding pulse feedbacks with different filtering characteristics in related technical solutions, this application provides a method for determining pulse feedback, which can effectively improve the accuracy of determining the pulse feedback of a virtual room.

[0040] Figure 3 A flowchart illustrating a method for determining impulse feedback provided in an exemplary embodiment of this application is shown. The method includes:

[0041] Step 301: Determine the path filtering characteristics of each sound wave path in the virtual room.

[0042] Among them, the path filtering feature is used to characterize the sound absorption of sound waves when they propagate along the sound wave path, which is the path generated after the sound wave is reflected by the sound reflecting surface in the virtual room.

[0043] Since sound reflecting surfaces attenuate the sound energy projected onto them, and different sound wave paths have different numbers of reflections, different sound wave paths have their own corresponding path filtering characteristics.

[0044] Since the absorption coefficient of a sound reflector varies at different frequencies, each frequency should have its own absorption characteristics. Correspondingly, for a single sound wave path, each sound wave frequency also has its own corresponding absorption coefficient. This allows the sound wave path filtering characteristics corresponding to different sound wave paths to indicate the energy changes at different sound wave frequencies.

[0045] Therefore, this path filtering feature can represent the energy corresponding to different frequencies of the sound wave emitted by the sound source after it passes through the sound wave path and reaches the microphone.

[0046] Optionally, the sound absorption effect at different frequencies may vary for sound-reflecting surfaces made of different materials. Table 1 shows a path filtering characteristic, which is presented through a table showing the correspondence between frequency and the energy of the sound wave reaching the pickup.

[0047] Table 1

[0048] frequency Frequency 1 Frequency 2 Frequency 3 ...... Frequency n energy <![CDATA[X1]]> <![CDATA[X2]]> <![CDATA[X3]]> ...... <![CDATA[X n ]]>

[0049] This includes n frequencies, which are selected based on the sound absorption frequency points of the sound-reflecting surface material. Furthermore, the energy ranges from X1 to X... n These represent the energy values ​​corresponding to different frequencies of sound waves that arrive at the microphone along the same sound wave path.

[0050] In one possible implementation, the path filtering characteristics are obtained through acoustic wave tracking. Each time a sound wave undergoes a reflection, the energy value corresponding to different frequencies needs to be updated. The number of data updates is related to the number of reflections along the corresponding acoustic wave path.

[0051] Step 302: Based on the energy of the sound waves reaching the microphone in each sound wave path, perform feature fusion on the path filtering features to obtain the total filtering features of the virtual room.

[0052] The total filtering feature is used to characterize the sound absorption of the virtual room.

[0053] To obtain the sound absorption of a virtual room, i.e. the filtering of sound waves in the virtual room, it is necessary to perform feature fusion on the path filtering characteristics based on the energy of the sound waves when they reach the microphone in each sound wave path.

[0054] During feature fusion, the computer device performs fusion after weighting the path filtering features of each sound wave path and the energy of the sound wave reaching the microphone in that path. Optionally, the weighting coefficients are calculated based on the energy of the sound wave reaching the microphone and the cumulative energy value of the sound waves that have reached the microphone.

[0055] The overall filtering characteristics obtained by fusion have the characteristics of different sound wave paths and different frequencies in the virtual room. Therefore, the overall filtering characteristics can reflect the overall sound absorption characteristics of the virtual room.

[0056] Step 303: Based on the total filtering characteristics, filter the total impulse feedback of the virtual room to obtain the target impulse feedback.

[0057] The total impulse feedback is obtained through acoustic wave tracking.

[0058] Sound tracing involves tracking a sound source. This tracing process is performed by computer equipment based on the path of the sound wave as it propagates, and the energy of the sound wave received by the microphone is determined based on the number of reflections along the sound wave path.

[0059] Optionally, during the process of obtaining total pulse feedback by sound wave tracing, it is set that the sound absorption coefficient of each frequency of the reflective surface through which the sound wave path passes is equal. That is, after the sound wave is reflected by each sound reflective surface, the energy of different sound wave frequencies absorbed by the sound reflective surface is equal. Therefore, the obtained total pulse feedback cannot express the sound absorption of the virtual room at different frequencies.

[0060] Therefore, in order to obtain a representation of the sound absorption of the virtual room at different frequencies, it is necessary to filter the total pulse feedback based on the total filtering characteristics that can represent the sound absorption of the virtual room at different frequencies. The target pulse feedback obtained after filtering can reflect the sound absorption characteristics of the virtual room at different frequencies.

[0061] In summary, in this embodiment, the computer device fuses the path filtering characteristics of each sound wave path into a total filtering characteristic based on the path filtering characteristics of each sound wave path and the energy of the sound waves reaching the microphone in each sound wave path. This total filtering characteristic can characterize the sound absorption of the virtual room. After obtaining the total filtering characteristic, the total impulse feedback obtained through sound wave tracking is then filtered, and the resulting target impulse feedback can reflect the sound absorption characteristics of the virtual room for sound waves of different frequencies. Furthermore, using the scheme provided in this application to determine the impulse feedback of the virtual room can improve the accuracy of determining the impulse feedback.

[0062] In this embodiment of the application, before determining the total filtering characteristics, it is necessary to first determine the path filtering characteristics of each sound wave path. The filtering characteristics of the sound wave path can be obtained by sound wave tracing. During the sound wave tracing process, the computer device needs to calculate the energy corresponding to different frequencies of sound waves based on the different absorption coefficients of sound waves at different frequencies on the sound reflection surface. The process of determining the path filtering characteristics of each sound wave path in the virtual room will be described below through an exemplary embodiment.

[0063] Figure 4 A flowchart illustrating a process for determining path filtering features according to an exemplary embodiment of this application is shown, the process including:

[0064] Step 401: Determine the reflection filtering characteristics of the sound reflecting surface based on the sound absorption characteristics.

[0065] Among them, the sound absorption feature is used to indicate the correspondence between the sound absorption coefficient of the sound reflecting surface and the frequency, and the reflection filtering feature is used to describe the correspondence between the reflection coefficient of the sound reflecting surface and the frequency.

[0066] Table 2

[0067] frequency Frequency 1 Frequency 2 Frequency 3 ...... Frequency n Sound absorption coefficient <![CDATA[A1]]> <![CDATA[A2]]> <![CDATA[A3]]> ...... <![CDATA[A n ]]>

[0068] Table 2 shows the correspondence between sound absorption coefficient and frequency, provided in the embodiments of this application, for characterizing sound absorption features. Here, frequency is the sound absorption frequency point corresponding to the sound reflecting surface, and sound absorption coefficient is the sound absorption coefficient of the sound reflecting surface for sound waves of different frequencies.

[0069] Optionally, the path filtering characteristics of the sound wave path are determined based on sound wave tracing. Therefore, it is necessary to calculate the reflection filtering characteristics based on each sound reflecting surface. The reflection filtering characteristics are determined based on the sound absorption characteristics. First, the reflection coefficient corresponding to the sound absorption coefficient at the same frequency needs to be calculated. Then, the reflection filtering characteristics are determined based on the reflection coefficient and the frequency corresponding to the reflection coefficient.

[0070] At the same frequency, the sum of the absorption coefficient and the reflection coefficient is 1, and the reflection coefficient = 1 - the absorption coefficient. According to Table 2 above, the reflection filtering characteristics of the same sound reflecting surface can be obtained as shown in Table 3.

[0071] Table 3

[0072] frequency Frequency 1 Frequency 2 Frequency 3 ...... Frequency n Reflectance coefficient <![CDATA[1-A1]]> <![CDATA[1-A2]]> <![CDATA[1-A3]]> ...... <![CDATA[1-A n ]]>

[0073] Wherein, frequency is the sound absorption frequency point corresponding to the sound reflecting surface, and sound absorption coefficient is the reflection coefficient of the sound reflecting surface for sound waves of different frequencies.

[0074] Step 402: Based on the reflection filtering characteristics, the path filtering characteristics of the sound wave path are determined by sound wave tracing technology.

[0075] Among them, the path filtering feature is used to describe the correspondence between the energy and frequency of the sound wave after it has been reflected n times before it reaches the microphone, where n is greater than or equal to 1.

[0076] It should be noted that in the embodiments of this application, the sound absorption characteristics of the sound reflecting surfaces corresponding to the n reflections of the sound wave may not be the same, that is, the sound wave energy attenuation value of each reflection may be different, or the sound absorption characteristics of the sound reflecting surfaces corresponding to the n reflections may be the same, that is, the sound wave energy attenuation value of each reflection may be the same. This embodiment does not limit this.

[0077] Determining the path filtering features of an acoustic wave based on reflection filtering features requires the following process:

[0078] I. Initialize path filtering features.

[0079] In the initialized path filtering features, the energy value corresponding to each frequency is 0.

[0080] Table 4

[0081]

[0082]

[0083] Specifically, the initialized path filtering features are shown in Table 4.

[0084] Second, when a sound wave undergoes n reflections, the sound wave energy indicated by the reflection filtering characteristics corresponding to the n reflections is accumulated to obtain the path filtering characteristics of the reflection path.

[0085] In one possible embodiment, the reflection filtering characteristics corresponding to the n reflections of the sound wave are all the same. Therefore, it is only necessary to accumulate the sound wave energy corresponding to different frequencies indicated by the reflectivity wave characteristics n times to obtain the path filtering characteristics of the reflection path.

[0086] Schematic illustration: assuming the sound wave undergoes two reflections in its path, and the reflection filtering characteristics of the reflecting surfaces of the two reflections are as shown in Table 4 above, then the path filtering characteristics corresponding to this sound wave path when the sound wave reaches the pickup after two reflections are shown in Table 5.

[0087] Table 5

[0088] frequency Frequency 1 Frequency 2 Frequency 3 ...... Frequency n energy <![CDATA[2(1-A1)]]> <![CDATA[2(1-A2)]]> <![CDATA[2(1-A3)]]> ...... <![CDATA[2(1-A n )]]>

[0089] Since the reflection coefficients are different for different frequencies, the acoustic energy corresponding to different frequencies is also different in the path filtering characteristics.

[0090] In another possible implementation, if the materials of the reflecting surfaces after n reflections in the sound wave path are different, the reflection coefficients after n reflections will also be different, so it is necessary to calculate the sound wave energy after each reflection.

[0091] To illustrate, assuming the reflection filtering characteristics of the sound wave reflecting surface at the first reflection in the sound wave path are as shown in Table 4 above, then the sound wave energy after the first reflection is shown in Table 6:

[0092] Table 6

[0093] frequency Frequency 1 Frequency 2 Frequency 3 ...... Frequency n energy <![CDATA[1-A1]]> <![CDATA[1-A2]]> <![CDATA[1-A3]]> ...... <![CDATA[1-A n ]]>

[0094] Assuming the sound wave reaches the pickup after a first reflection and a second reflection, and the reflection coefficients for different frequencies in the reflection filtering characteristics of the sound reflecting surface corresponding to the second reflection are all B, then the path filtering characteristics are shown in Table 7:

[0095] Table 7

[0096] frequency Frequency 1 Frequency 2 Frequency 3 ...... Frequency n energy <![CDATA[B+1-A1]]> <![CDATA[B+1-A2]]> <![CDATA[B+1-A3]]> ...... <![CDATA[B+1-A n ]]>

[0097] In this embodiment, the computer device determines the reflection filtering characteristics of the sound reflecting surface based on the sound absorption characteristics of the sound reflecting surface, thereby determining the path filtering characteristics of each sound wave path. This enables each path filtering characteristic to reflect the sound absorption characteristics of different sound wave paths for different frequencies of sound waves, and the total filtering characteristics obtained by feature fusion of the path filtering characteristics can accurately reflect the sound absorption of the virtual room.

[0098] In this embodiment of the application, after the computer device obtains the path filtering features corresponding to each virtual path in the virtual room, it will perform feature fusion on the path filtering features based on the energy of the sound waves when they reach the microphone in each sound wave path. The feature fusion process will be described below through an exemplary embodiment.

[0099] Figure 5 This application illustrates a flowchart of a process for feature fusion of path filtering features, provided by an exemplary embodiment of the present application. The process includes:

[0100] Step 501: Initialize the total filter characteristics.

[0101] Initializing the overall filtering characteristics involves constructing a table mapping frequency to sound wave energy, where sound wave energy refers to the energy of the sound wave after it reaches the microphone. After initialization, the energy value corresponding to different frequencies is 0. Table 8 shows one example of the initialized overall filtering characteristics in an embodiment of this application:

[0102] Table 8

[0103] frequency Frequency 1 Frequency 2 Frequency 3 ...... Frequency n energy 0 0 0 ...... 0

[0104] Step 502: Update the feature weighting coefficients based on the energy of the sound wave currently received by the microphone and the accumulated energy of the microphone.

[0105] The feature weighting coefficients are used to update the overall filter features. Furthermore, when performing feature fusion based on the energy of the currently received sound wave, the filter features of different paths need to be weighted according to these feature weighting coefficients before fusion. The process of updating the feature weighting coefficients is as follows:

[0106] 1. Initialize the accumulated energy of the sound waves received by the microphone.

[0107] The accumulated energy in a microphone is the sum of the energy values ​​of the sound waves emitted by the sound source and received by the microphone. After initialization, the accumulated energy of the microphone contains zero energy for each frequency.

[0108] 2. Calculate the sum of the energy of the sound wave currently received by the microphone and the accumulated energy to obtain the intermediate energy.

[0109] When determining the feature weighting coefficients, it is necessary to determine the feature weighting coefficients based on the ratio between the energy currently received by the microphone and the cumulative energy of the microphone.

[0110] Since the energy of the currently received sound wave is different from the energy value corresponding to different frequencies in the accumulated energy, the energy value corresponding to different sound wave frequencies in the intermediate energy is obtained by calculating the sum of the energy of the sound wave currently received by the microphone at a certain frequency and the energy of the accumulated energy at the corresponding frequency.

[0111] 3. Calculate the ratio of the energy of the sound wave currently received by the microphone to the intermediate energy to obtain the first characteristic weighting coefficient; calculate the ratio of the cumulative energy to the intermediate energy to obtain the second characteristic weighting coefficient.

[0112] The first feature weighting coefficient corresponds to the path filtering feature of the currently received sound wave, and the second feature weighting coefficient corresponds to the unupdated total filtering feature.

[0113] To illustrate, let's assume S is the energy value of the sound wave when it reaches the microphone, which is related to the number of reflections the sound wave passes through, and Z is the cumulative energy. Then the intermediate energy value should be S+Z.

[0114] Based on the above process, the first feature weighting coefficient is S / (S+Z), and the second feature weighting coefficient is Z / (S+Z).

[0115] It is understood that the S and Z assumed in this embodiment may correspond to different sound wave energies at different frequencies, which will not be elaborated here.

[0116] IV. Update the cumulative energy based on the energy of the sound wave currently received by the microphone and the updated feature weighting coefficients.

[0117] After determining the feature weighting coefficients, since the microphone has received a new sound wave, the microphone's accumulated energy needs to be updated. The updated accumulated energy includes the sound wave energy of the sound wave currently received by the microphone.

[0118] Optionally, when updating the accumulated energy, the energy of the received sound waves can be directly superimposed to obtain the updated accumulated energy.

[0119] Optionally, during the process of updating the accumulated energy, the accumulated energy can be updated based on the first new feature coefficient and the second feature filter coefficient. During the update process, after obtaining the updated feature weighting coefficients, the energy of the currently received sound wave and the unupdated accumulated energy value are weighted and summed using the first feature weighting coefficient and the second feature filter coefficient, respectively, to obtain the updated accumulated energy.

[0120] To illustrate, if the acoustic energy of the sound wave in a sound wave path currently received by the microphone is S, and the unupdated cumulative energy is Z, then the updated cumulative energy is: S × first filter new feature coefficient + Z × second filter new feature coefficient.

[0121] In this process, considering the energy ratio between the energy of the currently received sound wave and the accumulated energy, it is possible to reasonably allocate the proportion of sound wave energy in different sound wave paths in the updated accumulated energy.

[0122] Step 503: Based on the feature weighting coefficients and the energy of the sound wave currently received by the microphone, fuse the path filtering features to obtain the total filtering features of the virtual room.

[0123] The updated total filtering features are obtained by weighting and summing the unupdated total filtering features and path filtering features based on the first feature weighting coefficient and the second feature weighting coefficient.

[0124] In one possible implementation, after a sound wave along a certain sound path reaches the microphone, the computer device updates the overall filter characteristics based on the energy of the sound wave reaching the microphone and the path filtering characteristics corresponding to that sound wave path. After all sound waves with n sound wave paths in the virtual room have reached the microphone, the finally updated overall filter characteristics can be used to characterize the sound absorption effect of the entire virtual room.

[0125] Indicatively, when a microphone receives a sound wave along a specific sound wave path, the path filtering feature T1 of that sound wave path can be obtained using sound wave tracking technology. Furthermore, by analyzing the energy of the sound wave reaching the microphone and its accumulated energy, the first feature weighting coefficient and the second feature weighting coefficient can be determined. Assuming there exists an unupdated total filtering feature T2, the updated total filtering feature is: T1 × first feature weighting coefficient + T2 × second feature weighting coefficient.

[0126] It is understood that the weighted summation of the unupdated total filter features and path filter features described in the embodiments of this application refers to the weighted summation of the energy values ​​corresponding to each frequency in the unupdated total filter features and the energy values ​​corresponding to different frequencies indicated by the path filter features, to obtain the total sound wave energy values ​​corresponding to different frequencies.

[0127] In this embodiment, the path filtering features of the sound wave path are gradually fused based on the energy value of the sound wave currently received by the microphone, so that the total filtering features can be fused with the features of each path filter. Furthermore, weighted summation based on the filtering feature fusion coefficients can give higher weights to the path filtering features corresponding to the sound wave path with higher received energy.

[0128] In one possible implementation, before filtering the total impulse feedback of the virtual room based on the total filtering characteristics, the computer device normalizes the total filtering characteristics. Specifically, it normalizes the total filtering characteristics after ensuring that the sound waves reach the pickup in each sound wave path within the virtual room, resulting in normalized total filtering characteristics. These normalized total filtering characteristics characterize the gain of the virtual room on the sound waves.

[0129] Optionally, in one possible implementation, the sound wave energy corresponding to different frequencies in the total filtering characteristics is in dB (decibels). During normalization, the maximum energy value among the sound wave energies corresponding to different frequencies indicated by the total filtering characteristics can be extracted. Then, the maximum energy value is subtracted from the energy values ​​corresponding to each frequency after the total filtering characteristics are applied. The result of the subtraction is converted from an integer decibel to a decibel between 0 and 1 to represent the gain of the virtual room on the sound waves. Since the sound wave energy is attenuated by the sound reflection surface during the reflection process, the gain of the virtual room is always less than or equal to 1.

[0130] In this embodiment, during the acquisition of total pulse feedback, the sound absorption coefficients of each reflective surface at different frequencies are set to be consistent. However, in this embodiment, the sound absorption coefficients of the reflective surfaces of the virtual room differ at different frequencies. Therefore, before acquiring the total pulse feedback, the reflection coefficients of each reflective surface need to be standardized. The specific process is as follows:

[0131] First, a unified reflection coefficient is calculated based on the sound absorption characteristics of the sound-reflecting surfaces in the virtual room.

[0132] The uniform reflection coefficient refers to the reflection coefficient of a sound-reflecting surface at different frequencies in a virtual room, while the sound absorption characteristics indicate the relationship between the sound absorption coefficient of the sound-reflecting surface and its frequency. The sound absorption characteristics refer to the sound absorption of a sound-reflecting surface at different sound wave frequencies in a virtual room.

[0133] Optionally, the sound absorption characteristic can be input by the user. Alternatively, the sound absorption characteristic can be obtained by a computer by querying online data or offline data stored in the computer, based on the material of the sound-reflecting surface, to find the sound absorption coefficient corresponding to the sound absorption frequency point.

[0134] Without considering scattering and resonance, the sum of the reflection coefficient and absorption coefficient of a sound-reflecting surface should equal 1. Furthermore, based on the equal loudness curves, it can be determined that the human ear has different sensitivities to different frequencies. Therefore, computer equipment determines the absorption weighting coefficients for different frequencies based on the human ear's sensitivity to these frequencies. These absorption weighting coefficients are positively correlated with the human ear's sensitivity to different frequencies; that is, the higher the sensitivity of the human ear, the higher the absorption weighting coefficient. For example, the human ear is most sensitive to sounds in the 1K-5KHz frequency range, so the absorption weighting coefficient for this frequency range is the highest.

[0135] The computer equipment uses this sound absorption weighting coefficient to perform weighted calculations on the sound absorption characteristics at different frequencies, resulting in a unified sound absorption coefficient. The unified sound absorption coefficient represents the unified sound absorption of the sound reflector at different frequency sound waves.

[0136] As shown in Table 2, assuming that the human ear is less sensitive to frequencies 1, 2, and n than to frequencies 3 to n-1, the first absorption weighting coefficient is determined for frequencies 1, 2, and n, and the second absorption weighting coefficient is determined for frequencies 3 to n-1. Then, the standardized sound absorption coefficient of the sound reflecting surface is ((A1+A2+A...)). n () / 3)×First sound absorption weighting coefficient+((A3+A4+...+A) n-1 ) / (n-3))×Second sound absorption weighting coefficient.

[0137] The unified reflection coefficient is calculated based on the unified sound absorption coefficient. Since the sum of the reflection coefficient and the sound absorption coefficient of the sound reflecting surface is 1, the sum of the unified reflection coefficient and the unified sound absorption coefficient is also 1, that is, the unified reflection coefficient = 1 - the unified sound absorption coefficient.

[0138] Optionally, considering scattering, assuming the scattering coefficient is 'a', then the unified reflection coefficient = 1 - a - unified absorption coefficient. Without considering scattering, a = 0.

[0139] Secondly, after the computer device obtains the unified reflection coefficient, sound wave tracking is performed based on the unified reflection coefficient to obtain the total pulse feedback.

[0140] In this embodiment of the application, the process of filtering the total impulse feedback of the virtual room based on the total filtering characteristics is a process of making the total impulse feedback obtained by sound wave tracing based on the unified reflection coefficient reflect the filtering characteristics of different sound wave paths and different frequencies of sound waves in the virtual room.

[0141] In one possible implementation, before filtering the total impulse feedback, the computer device constructs a filter bank based on the total filtering characteristics. The number of filters in the filter bank is consistent with the number of frequencies indicated by the total filtering characteristics, and the center frequency of each filter in the filter bank is consistent with the frequency indicated by the total filtering characteristics. For example, if the total filtering characteristics include two frequency points, frequency 1 and frequency 2, then the constructed filter bank contains 2 filters, and the center frequencies of the two filters are frequency 1 and frequency 2, respectively.

[0142] Optionally, after normalizing the total filtering characteristics, the gain value of the filter bank is consistent with the incremental gain indicated by the total filtering characteristics. That is, after the total pulse feedback is input into the filter bank, the energy of the output target pulse feedback is consistent with the energy value indicated by the total filtering characteristics, and the frequency response curve of the filter bank conforms to the relationship between frequency and gain in the total filtering characteristics.

[0143] Optionally, multiple peak-type second-order IIR (Infinite Impulse Response) filters can be connected in series to form a filter bank; alternatively, multiple bandpass filters can be connected in parallel to form a filter bank. It is understood that the filters in the filter bank can also be other types of filters, and the connection methods for different types of filters forming the filter bank will also differ. Those skilled in the art should select the appropriate type of filter and use the corresponding connection method according to the specific circumstances.

[0144] After constructing the filter, the computer equipment inputs the total pulse feedback into the filter bank for filtering, thereby obtaining the target pulse feedback that can reflect the different sound absorption characteristics of different frequencies in the virtual room.

[0145] In this embodiment, the computer device constructs a filter bank based on the total filtering characteristics and filters the total pulse feedback. The resulting target pulse feedback can reflect the differences in sound absorption characteristics of the virtual room at different frequencies, thus making the determination of the target pulse feedback more accurate.

[0146] Figure 6A flowchart illustrating the pulse feedback determination process provided in an exemplary embodiment of this application is shown. First, before any sound wave reaches the microphone, the computer device initializes various data, including at least the total filtering characteristics, the microphone's accumulated energy, and path filtering characteristics. Then, based on the acquired sound absorption characteristics, the reflection filtering characteristics of the sound reflecting surface are determined, and the uniform reflection coefficient of the sound reflecting surface is determined based on the sound absorption characteristics. Next, when the microphone receives a sound wave, the path filtering characteristics of the sound wave path corresponding to that sound wave are determined based on sound wave tracing. The computer device also updates the feature weighting coefficients based on the energy of the sound wave currently received by the microphone and the accumulated energy. After obtaining these feature weighting coefficients, the total filtering characteristics are updated based on these feature weighting coefficients and the path filtering characteristics of the currently received sound wave. During this process, the computer device also updates the accumulated energy based on the feature weighting coefficients and the energy of the currently received sound wave.

[0147] With sound waves reaching the pickup along all sound paths, the computer normalizes the total filtering characteristics to obtain normalized total filtering characteristics. Subsequently, a filter bank is constructed based on these normalized total filtering characteristics to filter the total impulse feedback, obtaining the target impulse feedback. The total impulse feedback is obtained by sound wave tracking based on a unified reflection coefficient.

[0148] In illustrative terms, this embodiment of the application uses a virtual room with six sound-reflecting surfaces, and the sound absorption coefficients of the six sound-reflecting surfaces are identical, as an example to illustrate the above. Figure 6 The process will be further explained.

[0149] The sound absorption characteristics of the sound-reflecting surfaces in this room are shown in Table 9:

[0150] Table 9

[0151] frequency 62.5Hz 125Hz 250Hz 500Hz 1kHz 2kHz 4kHz 8kHz 16kHz Sound absorption 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.1 0.1

[0152] First, based on the sound absorption characteristics, the reflection filtering characteristics of the six walls are shown in Table 10:

[0153] Table 10

[0154] frequency 62.5Hz 125Hz 250Hz 500Hz 1kHz 2kHz 4kHz 8kHz 16kHz energy -1dB -1dB -1dB -2dB -2dB -2dB -2dB -1dB -1dB

[0155] Among them, the energy value X corresponding to each frequency in the reflection filtering characteristics is 20*lg(reflection coefficient). Without considering scattering, X = 20*lg(1-reflection coefficient).

[0156] Furthermore, after determining the sound absorption characteristics of the reflective surface, the computer equipment calculates the standardized sound absorption coefficient. Since the human ear is most sensitive to sound in the range of 1kHz to 5kHz, the sound absorption weighting coefficient for frequencies within this range is 0.7, and the sound absorption weighting coefficient for other frequencies is 0.3. Therefore, the standardized sound absorption coefficient UA = ((X5+X6+X7) / 3)*0.7 + ((X1+X2+X3+X4+X8+X9) / 6)*0.3 = 0.175, and the standardized reflection coefficient UR = 1 - UA = 0.825.

[0157] Acoustic wave tracking is performed based on the unified reflection coefficient UR to obtain the total pulse feedback.

[0158] Based on sound wave tracing to determine path filtering characteristics, when a sound wave reaches the wall and is reflected, the energy values ​​of the reflection filtering characteristics of the energy reflecting surface in the path filtering characteristics are added together to obtain the path filtering characteristics of a sound wave path.

[0159] If the sound wave reaches the pickup after two reflections, the path filtering characteristics of the sound wave after the first reflection are shown in Table 11:

[0160] Table 11

[0161] frequency 62.5Hz 125Hz 250Hz 500Hz 1kHz 2kHz 4kHz 8kHz 16kHz Y(n) -1dB -1dB -1dB -2dB -2dB -2dB -2dB -1dB -1dB

[0162] Since the energy values ​​corresponding to different frequencies in the path filtering feature are all 0 after initialization, the energy value corresponding to the path filtering is the same as the energy value of the reflection filtering feature of the reflecting surface after one reflection.

[0163] After the sound wave undergoes a second reflection, the path filtering characteristics of the sound wave path are shown in Table 12, where Y(n) represents the energy value corresponding to the nth frequency. In this embodiment, n is a positive integer less than or equal to 9.

[0164] Table 12

[0165] frequency 62.5Hz 125Hz 250Hz 500Hz 1kHz 2kHz 4kHz 8kHz 16kHz Y(n) -2dB -2dB -2dB -4dB -4dB -4dB -4dB -2dB -2dB

[0166] After the sound wave propagates in its path and reaches the microphone, the computer device updates the feature weighting coefficients based on the energy of the currently received sound wave and the accumulated energy within the microphone. Assuming the sound wave reaches the microphone after only two reflections, the energy value of the currently received sound wave is consistent with the energy shown in Table 12.

[0167] Let S represent the energy of the currently received sound wave and Z represent the cumulative energy. Then, the first characteristic weighting coefficient = S / (S+Z) and the second characteristic weighting coefficient = Z / (Z+S).

[0168] After obtaining the first feature weighting coefficient and the second feature weighting coefficient corresponding to each frequency, the cumulative energy and the total filter feature are updated using these coefficients.

[0169] The updated cumulative energy Z = Z * second feature weighting coefficient + S * first feature weighting coefficient. The updated cumulative energy corresponding to different frequencies needs to be calculated by weighting the features weighting coefficients corresponding to that frequency.

[0170] For example, Table 13 shows a correspondence between the first feature weighting coefficient and the second filter feature coefficient and the frequency, where P(n) represents the first feature weighting coefficient and Q(n) represents the second feature weighting coefficient:

[0171] Table 13

[0172]

[0173]

[0174] Assuming the total filter characteristics before the update are shown in Table 14, X(n) represents the energy value corresponding to the nth frequency. In this embodiment, n is a positive integer less than or equal to 9.

[0175] Table 14

[0176] frequency 62.5Hz 125Hz 250Hz 500Hz 1kHz 2kHz 4kHz 8kHz 16kHz X(n) -2dB -2dB -2dB -4dB -4dB -4dB -4dB -2dB -2dB

[0177] Updated total filter feature = X(n)*Q(n) + Y(n)*P(n), (0 <n≤9)。

[0178] After tracing all sound wave paths, the total filter characteristics are normalized. This involves finding the maximum value M in X(n), subtracting the maximum value M from the energy values ​​corresponding to all frequencies in the total filter characteristics, and converting all energy values ​​to decibels (dBs) as decibels (0-1). The normalized total characteristic frequencies are shown in Table 15, where C(n) represents the gain corresponding to each frequency after the normalization of the total filter characteristics.

[0179] Table 15

[0180] frequency 62.5Hz 125Hz 250Hz 500Hz 1kHz 2kHz 4kHz 8kHz 16kHz C(n) 1 1 1 0.6 -0.6 0.6 0.6 0.6 0.6

[0181] Based on the overall filtering characteristics, nine peak-type second-order IIR filters were constructed with center frequencies of 62.5 Hz, 125 Hz, 500 Hz, 1 kHz, 2 kHz, 4 kHz, 8 kHz, and 16 kHz, respectively, and gains of C(1)-C(9). These nine filters were then connected in series to form a filter bank.

[0182] Optionally, based on the experience of those skilled in the art, the quality factor of all nine filters can be 0.667. The quality factor can affect the passband bandwidth corresponding to each center frequency, and those skilled in the art can adjust it according to the actual application scenario. This embodiment does not constitute a limitation in this regard.

[0183] The total pulse feedback is filtered by this filter bank to obtain the target pulse feedback.

[0184] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0185] Please refer to Figure 7 This diagram illustrates a structural block diagram of a pulse feedback determination device according to an embodiment of this application. The device may include:

[0186] The feature determination module 701 is used to determine the path filtering features of each sound wave path in the virtual room. The path filtering features are used to characterize the sound absorption of the sound wave when it propagates on the sound wave path. The sound wave path is the path generated after the sound wave is reflected by the sound reflecting surface in the virtual room.

[0187] The feature fusion module 702 is used to perform feature fusion on the path filtering features based on the energy of the sound waves when they reach the microphone in each of the sound wave paths, so as to obtain the total filtering features of the virtual room. The total filtering features are used to characterize the sound absorption of the virtual room.

[0188] The filtering module 703 is used to filter the total pulse feedback of the virtual room based on the total filtering characteristics to obtain the target pulse feedback, wherein the total pulse feedback is obtained by sound wave tracking.

[0189] Optionally, the device further includes:

[0190] An initialization module is used to initialize the total filter characteristics;

[0191] The feature fusion module 702 is used to update the feature weighting coefficients based on the energy of the sound wave currently received by the microphone and the accumulated energy of the microphone. The feature weighting coefficients are used to update the total filtering features.

[0192] The feature fusion module 702 is used to fuse the path filtering features based on the feature weighting coefficients and the energy of the sound wave currently received by the microphone to obtain the total filtering features of the virtual room.

[0193] Optionally, the feature fusion module 702 is used for:

[0194] The energy of the sound wave currently received by the microphone is calculated as the sum of the accumulated energy to obtain the intermediate energy;

[0195] The ratio of the energy of the sound wave currently received by the microphone to the intermediate energy is calculated to obtain the first feature weighting coefficient, which corresponds to the path filtering feature of the currently received sound wave.

[0196] The ratio of the accumulated energy to the intermediate energy is calculated to obtain the second feature weighting coefficient, which corresponds to the unupdated total filter feature.

[0197] The updated total filtering features are obtained by weighting and summing the unupdated total filtering features and path filtering features based on the first feature weighting coefficient and the second feature weighting coefficient.

[0198] Optionally, the device further includes:

[0199] An energy update module is used to initialize the accumulated energy of the sound waves received by the microphone; and to update the accumulated energy based on the energy of the sound waves currently received by the microphone and the updated feature weighting coefficients.

[0200] Optionally, the device further includes:

[0201] The normalization module is used to normalize the total filtering characteristics when the sound waves in each of the sound wave paths in the virtual room reach the microphone, so as to obtain the normalized total filtering characteristics. The normalized total filtering characteristics are used to characterize the gain of the virtual room on the sound waves.

[0202] Optionally, the filtering module 703 is used for:

[0203] Construct a filter bank based on the total filtering characteristics;

[0204] The total pulse feedback is input into the filter bank for filtering to obtain the target pulse feedback.

[0205] Optional,

[0206] The number of filters contained in the filter bank is consistent with the number of frequencies indicated by the total filtering characteristics;

[0207] The center frequency of each filter in the filter bank is consistent with the frequency indicated by the overall filtering characteristic;

[0208] The gain value of the filter bank is consistent with the gain of the energy indicated by the total filtering characteristics;

[0209] The filters are connected in series to form the filter bank.

[0210] Optionally, the feature determination module 701 is used for:

[0211] The reflection filtering characteristics of the sound reflecting surface are determined based on the sound absorption characteristics. The sound absorption characteristics are used to indicate the correspondence between the sound absorption coefficient of the sound reflecting surface and the frequency. The reflection filtering characteristics are used to describe the correspondence between the reflection coefficient of the sound reflecting surface and the frequency.

[0212] Based on the reflection filtering characteristics, the path filtering characteristics of the sound wave path are determined by sound wave tracking technology. The path filtering characteristics are used to describe the correspondence between the energy and frequency of the sound wave after n reflections before the sound wave reaches the microphone, where n is greater than or equal to 1.

[0213] Optionally, the feature determination module 701 is used for:

[0214] Initialize the path filtering features;

[0215] When the sound wave undergoes n reflections, the sound wave energy indicated by the reflection filtering feature corresponding to the n reflections is accumulated to obtain the path filtering feature of the reflection path.

[0216] Optionally, the feature determination module 701 is used for:

[0217] Calculate the reflection coefficient corresponding to the sound absorption coefficient at the same frequency, where the sum of the sound absorption coefficient and the reflection coefficient at the same frequency is 1;

[0218] The reflection filtering characteristics are determined based on the reflection coefficient and the frequency corresponding to the reflection coefficient.

[0219] Optionally, the device further includes:

[0220] The unification module is used to calculate the unified reflection coefficient based on the sound absorption characteristics of the sound reflecting surface in the virtual room. The unified reflection coefficient refers to the reflection coefficient of the sound reflecting surface in the virtual room for sound waves of different frequencies. The sound absorption characteristics are used to indicate the correspondence between the sound absorption coefficient of the sound reflecting surface and the frequency.

[0221] The acoustic wave tracking module is used to perform acoustic wave tracking based on the unified reflection coefficient to obtain the total pulse feedback.

[0222] Optionally, the unification module is used for:

[0223] Based on the sensitivity of the human ear to sounds of different frequencies, the sound absorption weighting coefficients corresponding to different frequencies are determined, and the sound absorption weighting coefficients are positively correlated with the sensitivity of the human ear to sounds of different frequencies.

[0224] Based on the sound absorption weighting coefficient, the sound absorption characteristics at different frequencies are weighted and calculated to obtain the unified sound absorption coefficient;

[0225] The unified reflection coefficient is calculated based on the unified sound absorption coefficient, and the sum of the unified reflection coefficient and the unified sound absorption coefficient is 1.

[0226] In this embodiment, the computer device fuses the path filtering characteristics of each sound wave path into a total filtering characteristic based on the path filtering characteristics of each sound wave path and the energy of the sound waves reaching the microphone in each sound wave path. This total filtering characteristic can characterize the sound absorption of the virtual room. After obtaining the total filtering characteristic, the total impulse feedback obtained through sound wave tracking is then filtered. The resulting target impulse feedback can reflect the sound absorption characteristics of the virtual room for sound waves of different frequencies. Furthermore, using the scheme provided in this application to determine the impulse feedback of the virtual room can improve the accuracy of determining the impulse feedback.

[0227] Please refer to Figure 8 This diagram illustrates a structural block diagram of a computer device provided in an exemplary embodiment of this application. The computer device 800 can be implemented as the computer device in the various embodiments described above. The computer device 800 may include one or more components such as a processor 810 and a memory 820.

[0228] The processor 810 may include one or more processing cores. The processor 810 connects to various parts within the computer device 800 using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 820, and by calling data stored in the memory 820. Optionally, the processor 810 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 810 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), Neural-network Processing Unit (NPU), and modem. Specifically, the CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required to be displayed on the touch screen; the NPU is used to implement Artificial Intelligence (AI) functions; and the modem is used to handle wireless communication. It is understandable that the aforementioned modem may not be integrated into the processor 810, but may be implemented using a separate chip.

[0229] The memory 820 may include random access memory (RAM) or read-only memory (ROM). Optionally, the memory 820 may include a non-transitory computer-readable storage medium. The memory 820 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 820 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the various method embodiments described below, etc.; the data storage area may store data created according to the use of the computer device 800 (such as audio data, telephone directory, etc.).

[0230] In addition, those skilled in the art will understand that the structure of the computer device 800 shown in the above figures does not constitute a limitation on the computer device. The computer device may include more or fewer components than shown, or combine certain components, or have different component arrangements. For example, the computer device 800 also includes a display screen, camera assembly, microphone, speaker, radio frequency circuit, input unit, sensors (such as accelerometer, angular velocity sensor, light sensor, etc.), audio circuit, WiFi module, power supply, Bluetooth module, etc., which will not be described in detail here.

[0231] This application also provides a computer-readable storage medium storing at least one piece of program code, which is loaded and executed by a processor to implement the pulse feedback determination method described in the above embodiments.

[0232] This application provides a computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the pulse feedback determination method provided in various optional implementations of the above aspects.

[0233] It should be understood that "multiple" as used herein refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. Furthermore, the step numbers described herein are merely illustrative of one possible execution order. In some other embodiments, the steps may not be executed in numerical order, such as two steps with different numbers being executed simultaneously, or two steps with different numbers being executed in the reverse order of the illustration. This application does not limit this.

[0234] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for determining pulse feedback, characterized in that, The method includes: Initialize the total filtering feature, which is used to characterize the sound absorption of the virtual room; The path filtering characteristics of each sound wave path in the virtual room are determined. The path filtering characteristics are used to characterize the sound absorption of the sound wave when it propagates along the sound wave path. The sound wave path is the path generated after the sound wave is reflected by the sound reflecting surface in the virtual room. Based on the energy of the sound wave currently received by the microphone and the accumulated energy of the microphone, the feature weighting coefficients are updated, and the feature weighting coefficients are used to update the total filtering features; based on the feature weighting coefficients and the energy of the sound wave currently received by the microphone, the path filtering features are fused to obtain the total filtering features of the virtual room; Based on the total filtering characteristics, the total impulse feedback of the virtual room is filtered to obtain the target impulse feedback, which is obtained through sound wave tracking.

2. The method according to claim 1, characterized in that, The step of updating the feature weighting coefficients based on the energy of the sound wave currently received by the microphone and the accumulated energy of the microphone includes: The energy of the sound wave currently received by the microphone is calculated as the sum of the accumulated energy to obtain the intermediate energy; The ratio of the energy of the sound wave currently received by the microphone to the intermediate energy is calculated to obtain the first feature weighting coefficient, which corresponds to the path filtering feature of the currently received sound wave. The ratio of the accumulated energy to the intermediate energy is calculated to obtain the second feature weighting coefficient, which corresponds to the unupdated total filter feature. The process of obtaining the total filtering characteristics of the virtual room includes: The updated total filtering features are obtained by weighting and summing the unupdated total filtering features and path filtering features based on the first feature weighting coefficient and the second feature weighting coefficient.

3. The method according to claim 1, characterized in that, The method further includes: Initialize the accumulated energy of the sound waves received by the microphone; The accumulated energy is updated based on the energy of the sound wave currently received by the microphone and the updated feature weighting coefficients.

4. The method according to claim 1, characterized in that, The method further includes: When the sound waves reach the microphone in each of the sound wave paths in the virtual room, the total filtering characteristics are normalized to obtain the normalized total filtering characteristics. The normalized total filtering characteristics are used to characterize the gain of the virtual room on the sound waves.

5. The method according to claim 1, characterized in that, The step of filtering the total impulse feedback of the virtual room based on the total filtering characteristics to obtain the target impulse feedback includes: Construct a filter bank based on the total filtering characteristics; The total pulse feedback is input into the filter bank for filtering to obtain the target pulse feedback.

6. The method according to claim 5, characterized in that, The number of filters contained in the filter bank is consistent with the number of frequencies indicated by the total filtering characteristics; The center frequency of each filter in the filter bank is consistent with the frequency indicated by the overall filtering characteristic; The gain value of the filter bank is consistent with the gain of the energy indicated by the total filtering characteristics; The filters are connected in series to form the filter bank.

7. The method according to claim 1, characterized in that, The determination of the path filtering characteristics of each sound wave path in the virtual room includes: The reflection filtering characteristics of the sound reflecting surface are determined based on the sound absorption characteristics. The sound absorption characteristics are used to indicate the correspondence between the sound absorption coefficient of the sound reflecting surface and the frequency. The reflection filtering characteristics are used to describe the correspondence between the reflection coefficient of the sound reflecting surface and the frequency. Based on the reflection filtering characteristics, the path filtering characteristics of the sound wave path are determined by sound wave tracking technology. The path filtering characteristics are used to describe the correspondence between the energy and frequency of the sound wave after n reflections before the sound wave reaches the microphone, where n is greater than or equal to 1.

8. The method according to claim 7, characterized in that, The determination of the path filtering features of the acoustic wave path includes: Initialize the path filtering features; When the sound wave undergoes n reflections, the sound wave energy indicated by the reflection filtering feature corresponding to the n reflections is accumulated to obtain the path filtering feature of the sound wave path.

9. The method according to claim 7, characterized in that, The determination of the reflection filtering characteristics of the sound reflecting surface based on sound absorption characteristics includes: Calculate the reflection coefficient corresponding to the sound absorption coefficient at the same frequency, where the sum of the sound absorption coefficient and the reflection coefficient at the same frequency is 1; The reflection filtering characteristics are determined based on the reflection coefficient and the frequency corresponding to the reflection coefficient.

10. The method according to claim 1, characterized in that, The method further includes: Based on the sound absorption characteristics of the sound reflecting surface in the virtual room, a unified reflection coefficient is calculated. The unified reflection coefficient refers to the reflection coefficient of the sound reflecting surface in the virtual room for sound waves of different frequencies. The sound absorption characteristics are used to indicate the correspondence between the sound absorption coefficient of the sound reflecting surface and the frequency. Based on the unified reflection coefficient, acoustic wave tracking is performed to obtain the total pulse feedback.

11. The method according to claim 10, characterized in that, The calculation of the standardized reflection coefficient based on the sound absorption characteristics of the sound-reflecting surface in the virtual room includes: Based on the sensitivity of the human ear to sounds of different frequencies, the sound absorption weighting coefficients corresponding to different frequencies are determined, and the sound absorption weighting coefficients are positively correlated with the sensitivity of the human ear to sounds of different frequencies. Based on the sound absorption weighting coefficient, the sound absorption characteristics at different frequencies are weighted and calculated to obtain a unified sound absorption coefficient; The unified reflection coefficient is calculated based on the unified sound absorption coefficient, and the sum of the unified reflection coefficient and the unified sound absorption coefficient is 1.

12. A pulse feedback determination device, characterized in that, The device includes: An initialization module is used to initialize the total filtering characteristics, which are used to characterize the sound absorption of the virtual room. The feature determination module is used to determine the path filtering features of each sound wave path in the virtual room. The path filtering features are used to characterize the sound absorption of the sound wave when it propagates on the sound wave path. The sound wave path is the path generated after the sound wave is reflected by the sound reflecting surface in the virtual room. The feature fusion module is used to update the feature weighting coefficients based on the energy of the sound wave currently received by the microphone and the accumulated energy of the microphone. The feature weighting coefficients are used to update the total filtering features. Based on the feature weighting coefficients and the energy of the sound wave currently received by the microphone, the path filtering features are fused to obtain the total filtering features of the virtual room. A filtering module is used to filter the total pulse feedback of the virtual room based on the total filtering characteristics to obtain the target pulse feedback, wherein the total pulse feedback is obtained through sound wave tracking.

13. A computer device, characterized in that, The computer device includes a processor and a memory; the memory stores at least one instruction, which is executed by the processor to implement the pulse feedback determination method as described in any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to implement the pulse feedback determination method as described in any one of claims 1 to 11.

15. A computer program product, characterized in that, The computer program product includes computer instructions stored in a computer-readable storage medium; a processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the pulse feedback determination method as described in any one of claims 1 to 11.

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