An audio adaptation method, system, computing device, and storage medium

Abstract

This specification provides an audio adaptation method, system, computing device, and storage medium. The audio adaptation method includes: acquiring a user's audio perception information and initial audio data in a virtual scene; determining a first matching degree between the audio perception information and the initial audio data; and adjusting the initial audio data based on the first matching degree to obtain first audio data. This enables the adjusted audio data to match the user's auditory characteristics, avoiding situations where the user cannot perceive key sound effects due to excessively low loudness, or where excessively high loudness causes auditory fatigue and hearing damage. It satisfies the personalized needs of users with different hearing abilities for audio output effects, improves the user's auditory experience, and can be widely applied in the fields of digital cultural and creative product production software and digital cultural and creative software in the next-generation information technology field (such as artificial intelligence, virtual reality, etc.).

Description

Technical Field

[0001] The embodiments in this specification relate to the field of audio processing technology, and in particular to an audio adaptation method, system, computing device, and storage medium. Background Technology

[0002] With the development of digital cultural products, users have developed personalized requirements for the audio output effects in these products.

[0003] Current methods for processing audio in digital cultural products primarily involve setting uniform audio parameters (such as frequency distribution, loudness, and channel allocation) based on the hearing levels of most users, meaning all users use the same audio configuration. While this approach meets the basic needs of most users with normal hearing, it suffers from the following problems: Firstly, individual differences in hearing among users make it difficult to capture key audio information under standardized audio modes. Secondly, some high-frequency or peak frequencies in standardized audio may cause auditory stimulation for users with normal hearing, easily leading to auditory fatigue or potential hearing damage, and it is also difficult to balance the delivery of key information with the creation of an immersive experience.

[0004] In conclusion, existing audio adaptation technologies cannot meet the personalized audio output needs of different hearing users. Summary of the Invention

[0005] In view of this, embodiments of this specification provide an audio adaptation method. One or more embodiments of this specification also relate to an audio adaptation system, a computing device, a computer-readable storage medium, and a computer program product, to address the technical deficiencies existing in the prior art.

[0006] According to a first aspect of the embodiments of this specification, an audio adaptation method is provided, comprising: Acquire the user's audio perception information, as well as the initial audio data in the virtual scene; Determine the initial matching degree between the audio perception information and the initial audio data; The initial audio data is adjusted based on the first matching degree to obtain the first audio data.

[0007] According to a second aspect of the embodiments of this specification, an audio adaptation system is provided, comprising: The hearing feature acquisition module is configured to acquire the user's audio perception information and the initial audio data in the virtual scene; The scene adaptive verification module is configured to determine the first degree of matching between the audio perception information and the initial audio data; The audio dynamic adaptation module is configured to adjust the initial audio data based on a first matching degree to obtain the first audio data.

[0008] According to a third aspect of the embodiments of this specification, a computing device is provided, comprising: Memory and processor; The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions, which implement the steps of the above method when executed by the processor.

[0009] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0010] According to a fifth aspect of the embodiments of this specification, a computer program product is provided, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0011] An embodiment of this specification provides an audio adaptation method that acquires a user's audio perception information and initial audio data in a virtual scene; determines a first matching degree between the audio perception information and the initial audio data; and adjusts the initial audio data based on the first matching degree to obtain first audio data. By determining the matching degree between the user's auditory perception and the initial audio data, and making targeted adjustments to the initial audio data according to the matching degree, the adjusted audio data can match the user's auditory characteristics. This constrains the audio parameters of the initial audio data within the user's audible and tolerable threshold range, avoiding situations where the user cannot perceive key sound effects due to excessively low loudness, or where excessively high loudness causes auditory fatigue and hearing damage. This satisfies the personalized audio output needs of users with different hearing conditions, avoids the mismatch between standardized audio parameters and user hearing differences leading to missing key sound effects or auditory discomfort, thereby improving user auditory comfort and enhancing the fit between audio output and user auditory perception characteristics, thus improving the user's auditory experience. Attached Figure Description

[0012] Figure 1 This is a flowchart illustrating an audio adaptation method provided in one embodiment of this specification; Figure 2 This is a flowchart of a hearing feature acquisition method provided in one embodiment of this specification; Figure 3 This is a schematic diagram illustrating a logic for adjusting audio data according to one embodiment of this specification; Figure 4 This is a schematic diagram of the logic of an audio dynamic adaptation engine provided in one embodiment of this specification; Figure 5 This is a schematic diagram illustrating another logic for adjusting audio data, provided in one embodiment of this specification. Figure 6 This is a schematic diagram of the structure of an audio adaptation system provided in one embodiment of this specification; Figure 7 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0013] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0014] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0015] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0016] Furthermore, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0017] First, the terms and concepts used in one or more embodiments of this specification will be explained.

[0018] Virtual scenes: Virtual scenes are computer-generated simulated environments that users can interact with through their senses, such as sight and hearing. Examples include virtual reality scenes, augmented reality scenes, game scenes, and metaverse social scenes.

[0019] Audio adaptation: Audio adaptation is the process of matching the playback parameters of audio data with the user's auditory characteristics to improve the user's auditory experience. For example, adjusting the loudness of audio data in each frequency band according to the user's hearing profile.

[0020] Audio data: Audio data refers to digital signals that carry sound information. Examples include background music, skill sound effects, environmental sound effects, and dialogue voice in virtual scenes.

[0021] Computing devices: Computer devices are computer devices designed to perform one or more dedicated tasks. Compared to personal mainframes, they are weaker in performance but have significant advantages in terms of size and power consumption. They are commonly used in various electronic and mechanical control devices.

[0022] This specification provides an audio adaptation method, and also relates to an audio adaptation system, a computing device, a computer-readable storage medium, and a computer program product, which will be described in detail in the following embodiments.

[0023] See Figure 1 , Figure 1 A flowchart of an audio adaptation method provided in one embodiment of this specification is shown, including the following specific steps: Step 102: Obtain the user's audio perception information and the initial audio data in the virtual scene.

[0024] The embodiments in this specification are applied to scenarios where the playback effect of audio needs to be optimized. For example, optimizing background audio in virtual reality applications.

[0025] Audio perception information refers to data that characterizes a user's auditory physiological characteristics of sound (i.e., auditory perception properties). For example, the minimum loudness a user can perceive and the maximum loudness they can tolerate across multiple frequency bands.

[0026] The initial audio data consists of pre-set raw audio signals from the virtual scene. For example, unadjusted background music, skill sound effects, and environmental sound effects from a game scene.

[0027] Optionally, one way to obtain a user's audio perception information is to play test sounds of various frequency bands to the user through a hearing test module and record the audible threshold and tolerance threshold reported by the user. Another way to obtain a user's audio perception information is to read preset hearing characteristic parameters from a user database. Optionally, one way to obtain initial audio data in a virtual scene is to read the audio file associated with the current scene and its initial loudness parameters from a scene resource file. This specification does not limit this approach in the embodiments.

[0028] For example, Figure 2 A flowchart illustrating a hearing feature acquisition process provided in one embodiment of this specification is shown.

[0029] refer to Figure 2 In a certain virtual reality application, upon a user's first login, a test and user feedback are triggered. The hearing feature acquisition module plays a pure tone signal from 20Hz to 20kHz, divided into six key frequency bands (low frequency 20-250Hz, low-mid frequency 250Hz-500Hz, mid frequency 500Hz-2kHz, mid-high frequency 2kHz-4kHz, high frequency 4kHz-8kHz, and ultra-high frequency 8kHz-20kHz) through headphones. Each frequency band plays a pure tone signal with different loudness levels in 5dB steps. The user provides feedback by clicking on a screen button: "Hearable," "Harsh," or "None of Perception." The hearing feature acquisition module records the lowest perceptible loudness (perceived loudness) and the highest tolerable loudness (tolerable loudness) for each frequency band. It also marks the harsh frequency bands reported by the user (frequency bands with sensitivity greater than a preset sensitivity threshold). Combined with a scene adaptive verification module, the acquired audio perception information is verified to generate / update the user's personalized hearing profile. Simultaneously, the system loads the audio configuration file of the current virtual scene to obtain initial audio data.

[0030] Step 102 obtains the user's audio perception information and the initial audio data in the virtual scene, providing a data foundation for subsequently determining the matching degree between the audio perception information and the initial audio data.

[0031] Step 104: Determine the first degree of matching between the audio perception information and the initial audio data.

[0032] The first degree of matching is a quantitative indicator that measures the degree of fit between the initial audio data and the user's audio perception information. The higher the first degree of matching, the better the parameter settings of the initial audio data match the user's auditory physiological characteristics. For example, the closer the loudness of the initial audio data in each frequency band is to the center value of the dynamic range formed by the user's perceived loudness and tolerable loudness, the higher the first degree of matching.

[0033] Optionally, one way to determine the first degree of matching between the audio perception information and the initial audio data is to calculate the degree of overlap between the loudness distribution of the initial audio data in each frequency range and the auditory sensitive intervals recorded in the user's audio perception information, and use the degree of overlap as the first degree of matching. Another way to determine the first degree of matching between the audio perception information and the initial audio data is to calculate the similarity between the auditory threshold curve in the user's audio perception information and the spectral envelope of the initial audio data, and use the similarity as the first degree of matching.

[0034] For example, the system acquires the user's audio perception information, which records the user's auditory characteristics of being more sensitive to high-frequency sounds and less sensitive to low-frequency sounds. In the initial audio data, the loudness of the high-frequency part is too high and the loudness of the low-frequency part is too low. The system calculates the degree of matching between the spectral distribution of the initial audio data and the user's auditory sensitive range, and obtains a first matching degree of 0.7, indicating that there is a deviation between the current audio settings and the user's auditory characteristics.

[0035] Step 104, by determining the first degree of matching between the audio perception information and the initial audio data, can quantify the user's auditory physiological characteristics into a calculable degree of matching index, providing a basis for subsequent adjustments to the initial audio data.

[0036] Step 106: Adjust the initial audio data based on the first matching degree to obtain the first audio data.

[0037] Adjusting initial audio data involves modifying the audio parameters of the initial audio data. Examples include increasing or decreasing the loudness of specific frequency bands, adjusting the left and right channel balance, and enhancing or reducing the loudness of specific sound effects.

[0038] The first audio data is an audio signal that has been adjusted in terms of audio parameters to match the user's audio perception information. It is an audio signal that has been initially adapted to the user's auditory characteristics at the physiological level. For example, after gain compensation and attenuation processing, the loudness of each frequency band is within the user's audible threshold and tolerance threshold.

[0039] Optionally, one way to obtain the first audio data by adjusting the initial audio data based on the first matching degree is as follows: when the first matching degree is lower than a preset threshold, the initial audio data is adjusted overall according to the auditory sensitive range indicated in the user's audio perception information, so that the loudness distribution of the adjusted audio in each frequency range is closer to the user's auditory sensitive range. Another way to obtain the first audio data by adjusting the initial audio data based on the first matching degree is as follows: calculate the adjustment amount of loudness in each frequency band according to the difference between the first matching degree and the target matching degree, and apply it to the initial audio data. This specification does not limit this aspect in the embodiments.

[0040] For example, the system detects that the first matching degree of 0.7 is lower than the preset threshold of 0.85, and determines that there is a deviation between the initial audio data and the user's auditory characteristics. Based on the characteristic of "sensitive to high frequencies and insensitive to low frequencies" in the user's audio perception information, the system reduces the loudness of the high-frequency part of the initial audio data by 2dB and increases the loudness of the low-frequency part by 3dB, so that the adjusted audio spectrum distribution is closer to the user's auditory sensitivity range, thus obtaining the first audio data.

[0041] Step 106 adjusts the initial audio data based on the first matching degree to obtain the first audio data, which can match the frequency distribution of the first audio data with the user's auditory sensitivity characteristics. This avoids the user being unable to perceive key sound effects due to excessively low loudness, and also avoids auditory fatigue or discomfort caused by excessively high loudness, thus achieving a precise match between the audio output and the user's auditory physiological characteristics.

[0042] In the embodiments of this specification, by determining the matching degree between the user's auditory perception and the initial audio data, and making targeted adjustments to the initial audio data based on the matching degree, the adjusted audio data can match the user's auditory characteristics. The audio parameters of the initial audio data are constrained within the user's audible and tolerable threshold range, avoiding the inability of the user to perceive key sound effects due to excessively low loudness, or the auditory fatigue and hearing damage caused by excessively high loudness. This satisfies the personalized needs of users with different hearing conditions for audio output effects, avoids the mismatch between standardized audio parameters and user hearing differences that leads to the loss of key sound effects or auditory discomfort, thereby improving the user's auditory comfort and enhancing the matching degree between audio output and the user's auditory perception characteristics, thus improving the user's auditory experience.

[0043] In one optional embodiment of this specification, the audio sensing information includes frequency response sensing information and / or channel sensing information; Step 104 includes: Determine the frequency response matching degree between the frequency response perception information and the initial audio data; And / or, Determine the channel matching degree between the channel perception information and the initial audio data.

[0044] Step 106 includes: The initial audio data is adjusted based on the frequency response matching degree to obtain the first audio data; And / or, The initial audio data is adjusted based on the channel matching degree to obtain the first audio data.

[0045] Frequency response perception information is data that characterizes a user's perception of sounds at different frequencies. For example, a user's perceived loudness, tolerance to loudness, and sensitivity across multiple frequency bands.

[0046] Frequency response matching is a quantitative indicator that measures the degree of fit between the frequency response characteristics of initial audio data and the user's perceived frequency response information. A higher frequency response matching degree indicates that the loudness distribution of the initial audio data in each frequency band is more in line with the user's auditory characteristics. For example, if the loudness of the initial audio data in the user's sensitive frequency band is near the center of the dynamic range formed by perceived loudness and tolerable loudness, then the frequency response matching degree is high.

[0047] Channel perception information is data that characterizes the difference in hearing between a user's two ears. For example, the perceived difference between the left and right channels at various frequency bands.

[0048] Channel matching is a quantitative indicator that measures the degree of fit between the spatial localization features (spatial dimension) of the initial audio data and the user's channel perception information. A higher channel matching degree indicates that the loudness distribution of the initial audio data in the left and right channels is more able to compensate for the user's binaural hearing differences. For example, if the loudness of the initial audio data in the channel on the side with weaker hearing is compensated and then balanced with the perception of the other channel, the channel matching degree is improved.

[0049] Optionally, one way to determine the frequency response matching degree between the frequency response perception information and the initial audio data is to calculate the matching degree component for each frequency band based on the initial loudness of the initial audio data in each frequency band and the perceived loudness and tolerable loudness in the user's frequency response perception information, and then perform a weighted average of the matching degree components for each frequency band to obtain the frequency response matching degree. Another way to determine the frequency response matching degree between the frequency response perception information and the initial audio data is to calculate the similarity between the spectral envelope of the initial audio data and the user's auditory sensitivity curve, and use the similarity as the frequency response matching degree. This specification does not limit this approach in the embodiments.

[0050] Optionally, one way to determine the channel matching degree between the channel perception information and the initial audio data is to compare the loudness difference between the left and right channels of the initial audio data in each frequency band with the perceived difference in the user's channel perception information, and calculate the degree of closeness between the two as the channel matching degree. Another way to determine the channel matching degree between the channel perception information and the initial audio data is to calculate the deviation between the spatial audio parameters of the initial audio data and the user's binaural hearing balance requirements, and use the reciprocal of the deviation value as the channel matching degree. This specification does not limit this approach in the embodiments.

[0051] Optionally, one implementation of adjusting the initial audio data based on frequency response matching degree can be as follows: when the frequency response matching degree is lower than a preset threshold, the loudness of the initial audio data in each frequency band is adjusted by an equalizer according to the perceived loudness and tolerable loudness in the user's frequency response perception information, so that the adjusted loudness moves closer to the center of the dynamic range formed by the perceived loudness and tolerable loudness. Another implementation of adjusting the initial audio data based on frequency response matching degree can be as follows: the loudness adjustment amount of each frequency band is calculated according to the difference between the frequency response matching degree and the target matching degree, and applied to the initial audio data. This specification does not limit this approach in the embodiments.

[0052] Optionally, one implementation of adjusting the initial audio data based on channel matching degree can be as follows: when the channel matching degree is lower than a preset threshold, the loudness of the left and right channels of the initial audio data in each frequency band is compensated and adjusted according to the perceptual difference in the user's channel perception information, so that the key sound effects are amplified and output to the channel with stronger hearing. Another implementation of adjusting the initial audio data based on channel matching degree can be as follows: calculate the loudness distribution adjustment amount of the left and right channels according to the difference between the channel matching degree and the target matching degree, and apply it to the initial audio data. The embodiments in this specification do not limit this.

[0053] In the embodiments of this specification, by determining the frequency response matching degree between the frequency response perception information and the initial audio data and / or the channel matching degree between the channel perception information and the initial audio data, and adjusting the initial audio data based on the frequency response matching degree and / or channel matching degree, the audio parameters can be optimized from two dimensions: frequency response and spatial positioning. This ensures that the loudness of the audio data in each frequency band matches the user's hearing in each frequency band, avoiding timbre distortion caused by uneven frequency response. Furthermore, it can compensate for the difference in hearing between the user's two ears, improve the positioning accuracy of spatial audio, thereby meeting the personalized needs of users with different hearing abilities in terms of frequency perception and spatial perception. This makes the audio output effect more suitable for the user's auditory perception characteristics, enhancing the user's overall auditory experience and immersion.

[0054] In one optional embodiment of this specification, the frequency response perception information includes perceived loudness and tolerable loudness in multiple frequency bands, and the initial audio data has corresponding initial loudness in multiple frequency bands; Determining the frequency response matching degree between the perceived frequency response information and the initial audio data includes: The first loudness difference is determined based on the perceived loudness and the initial loudness in each frequency band. The second loudness difference is determined based on the tolerance loudness and the initial loudness in each frequency band. The frequency response matching degree is determined based on the first loudness difference and the second loudness difference.

[0055] The initial audio data is adjusted based on the frequency response matching degree to obtain the first audio data, including: The initial loudness of each frequency band is adjusted based on the frequency response matching degree to obtain the first audio data.

[0056] Perceived loudness is the lowest loudness that a user can perceive in a specific frequency band. For example, a user's perceived loudness in the 2kHz-4kHz frequency band is 35dB.

[0057] Tolerance loudness is the highest loudness a user can tolerate in a specific frequency band. For example, a user's tolerance loudness in the 2kHz-4kHz frequency band is 55dB.

[0058] The initial loudness is the preset loudness of the initial audio data in a specific frequency band. For example, the initial loudness of the initial audio data in the 2kHz-4kHz frequency band is 40dB.

[0059] The first loudness difference is the difference between the perceived loudness and the initial loudness. For example, if the perceived loudness is 35 dB and the initial loudness is 40 dB, then the first loudness difference is -5 dB.

[0060] The second loudness difference is the difference between the tolerable loudness and the initial loudness. For example, if the tolerable loudness is 55 dB and the initial loudness is 40 dB, then the second loudness difference is 15 dB.

[0061] Optionally, one way to determine the frequency response matching degree based on the first loudness difference and the second loudness difference is to calculate the ratio of the first loudness difference to the second loudness difference in each frequency band, determine the matching degree component of that frequency band according to the ratio and a preset mapping relationship, and then perform a weighted average of the matching degree components of each frequency band to obtain the frequency response matching degree. Another way to determine the frequency response matching degree based on the first loudness difference and the second loudness difference is to calculate the deviation degree according to the degree to which the initial loudness deviates from the dynamic range formed by the perceived loudness and the tolerated loudness in each frequency band, take the reciprocal of the deviation degree as the matching degree component of that frequency band, and then synthesize them to obtain the frequency response matching degree. The embodiments in this specification do not limit this approach.

[0062] For example, the system obtains that the user's perceived loudness in the low-frequency range (20-250Hz) is 35dB and the tolerable loudness is 65dB. The initial loudness of the initial audio data in this frequency range is 30dB. The system calculates a first loudness difference of -5dB and a second loudness difference of 35dB. In the mid-frequency range (500Hz-2kHz), the perceived loudness is 40dB and the tolerable loudness is 80dB. The initial loudness is 70dB, the first loudness difference is 30dB, and the second loudness difference is 10dB. In the high-frequency range (4kHz-8kHz), the perceived loudness is 20dB and the tolerable loudness is 60dB. The initial loudness is 55dB, the first loudness difference is 35dB, and the second loudness difference is 5dB. The system calculated the frequency response matching degree to be 0.72 using a weighted average method based on the difference between the first and second loudness values ​​of each frequency band. This indicates that the initial audio data is close to the upper limit of tolerance in the high frequency range and deviates far from the lower limit of audibility in the mid frequency range, requiring adjustment.

[0063] In the embodiments of this specification, a first loudness difference is determined based on the perceived loudness and the initial loudness in each frequency band, a second loudness difference is determined based on the tolerable loudness and the initial loudness in each frequency band, and a frequency response matching degree is determined based on the first loudness difference and the second loudness difference. The initial loudness in each frequency band is adjusted based on the frequency response matching degree. This can precisely constrain the audio loudness within the dynamic range formed by the user's audible threshold and tolerable threshold. This avoids the user being unable to perceive key sound effects due to excessively low loudness, and also avoids auditory fatigue or discomfort caused by excessively high loudness. It achieves precise matching of audio data output in multiple frequency bands with the user's hearing, so that users with different hearing conditions can obtain a clear and comfortable auditory experience, and meet the user's personalized needs for audio output effects.

[0064] In one optional embodiment of this specification, the frequency response sensing information further includes the sensitivity corresponding to each frequency band; After adjusting the initial loudness of each frequency band based on frequency response matching to obtain the first audio data, the following steps are also included: Based on the sensitivity corresponding to each frequency band, the loudness of the first audio data in each frequency band is fine-tuned to obtain the fine-tuned first audio data.

[0065] Sensitivity is a quantitative indicator that characterizes how well a user perceives a unit change in loudness. For example, a user's sensitivity of 0.8 in the 2kHz-4kHz frequency band means that the user perceives a change of 0.8 units when the loudness changes by 1dB in that band.

[0066] Fine-tuning refers to further adjustments made to the audio parameters of the first audio data. For example, the loudness of the first audio data in the sensitive frequency band is slightly corrected based on sensitivity to make the timbre more natural.

[0067] Optionally, one way to fine-tune the loudness of the first audio data in each frequency band based on the sensitivity of each band is to use a smaller adjustment step size for frequency bands with higher sensitivity to avoid over-adjustment that could cause abrupt changes in timbre. Another way to fine-tune the loudness of the first audio data in each frequency band based on the sensitivity of each band is to perform a weighted correction on the loudness of each frequency band according to the difference between the sensitivity and a preset benchmark. This specification does not limit the scope of this method in the embodiments.

[0068] For example, in the 500Hz-2kHz frequency band, the user sensitivity is 0.9 (higher than the average of 0.7), and the loudness of the first audio data in this frequency band is 50dB. The system will fine-tune the loudness by -1dB to 49dB to make the timbre softer. In the 4kHz-8kHz frequency band, the user sensitivity is 0.5 (lower than the average of 0.7), and the loudness of the first audio data in this frequency band is 45dB. The system will keep the loudness unchanged to avoid over-adjustment.

[0069] In the embodiments of this specification, by fine-tuning the loudness of the first audio data in each frequency band based on the sensitivity corresponding to each frequency band, it is possible to further optimize the timbre of the audio data in each frequency band based on the user's perceptual sensitivity to the loudness of each frequency band, on the basis that the audio data already meets the requirements of audibility and comfort. This reduces the harsh frequency bands that the user is more sensitive to, and compensates for the sound details in the frequency bands that the user is less sensitive to. This makes the audio output more natural and delicate in terms of the user's auditory perception, and avoids the listening discomfort or loss of details caused by the user's different sensitivity to audio in each frequency band. Thus, while improving auditory comfort, it meets the personalized needs of different users for timbre performance.

[0070] In one optional embodiment of this specification, the channel perception information includes the perception difference between the left and right channels in each frequency band, and the initial audio data has corresponding initial loudness in multiple frequency bands. Determine the channel matching degree between the channel perception information and the initial audio data, including: Based on the perceived difference between the left and right channels in each frequency band, and the initial loudness of the initial audio data in each frequency band, the channel matching degree is determined.

[0071] The initial audio data is adjusted based on the channel matching degree to obtain the first audio data, including: Based on the channel matching degree, the initial loudness corresponding to each frequency band is adjusted to obtain the first audio data.

[0072] The left channel is the channel signal corresponding to the left playback device in the audio data. For example, the left channel signal in stereo audio.

[0073] The right channel is the channel signal corresponding to the right playback device in the audio data. For example, the right channel signal in stereo audio.

[0074] Perceived difference is an indicator that characterizes the difference in loudness or clarity perceived by a user between the left and right channels. For example, a perceived difference of 20% in the 2kHz-4kHz frequency band means that the perceived loudness difference between the left and right channels is 20%.

[0075] Optionally, one way to determine channel matching degree based on the perceived difference between the left and right channels in each frequency band and the initial loudness of the initial audio data in each frequency band is as follows: calculate the ratio of the perceived loudness ratio of the left and right channels to the initial loudness ratio of the left and right channels of the initial audio data, and use the ratio of the perceived loudness ratio of the left and right channels as the channel matching degree. For example, if a user perceives a loudness of 40dB in the left ear and 45dB in the right ear in the 2kHz-4kHz frequency band, then the perceived loudness ratio is 40 / 45≈0.89; if the initial loudness of the left channel in the initial audio data in this frequency band is 50dB and the initial loudness of the right channel is 55dB, then the initial loudness ratio of the left and right channels is 50 / 55≈0.91; the channel matching degree is 0.89 / 0.91≈0.98. The closer this value is to 1, the better the left and right channel allocation of the current audio can compensate for the user's hearing differences, and the higher the channel matching degree. Another way to determine channel matching degree based on the perceived difference between the left and right channels in each frequency band and the initial loudness of the initial audio data in each frequency band is to calculate the ratio of the perceived loudness difference between the left and right channels to the initial loudness difference between the left and right channels of the initial audio data. For example, if a user perceives a loudness of 40dB in the left ear and 45dB in the right ear in the 2kHz-4kHz frequency band, the perceived loudness difference is 5dB; if the initial loudness of the initial audio data in this frequency band is 50dB in the left channel and 55dB in the right channel, the initial loudness difference between the left and right channels is 5dB; the channel matching degree is 5 / 5 = 1, indicating that the current left and right channel allocation of the audio perfectly matches the user's hearing differences. This specification does not limit this specific approach in the embodiments.

[0076] For example, the system obtains that the user's perceived loudness in the low-frequency range (20-250Hz) is 35dB in the left ear and 40dB in the right ear, with a perceived loudness ratio of 35 / 40=0.875; the initial audio data in this frequency range has an initial loudness of 55dB in the left channel and 60dB in the right channel, with an initial loudness ratio of 55 / 60≈0.917; the channel matching degree is calculated to be 0.875 / 0.917≈0.95. In the high-frequency range (4kHz-8kHz), the user's perceived loudness is 45dB in the left ear and 50dB in the right ear, with a perceived loudness ratio of 45 / 50 = 0.9. The initial audio data for this frequency band shows an initial loudness of 48dB in the left channel and 52dB in the right channel, with an initial loudness ratio of 48 / 52 ≈ 0.923. The calculated channel matching degree is 0.9 / 0.923 ≈ 0.975. The system performs a weighted average of the channel matching degree components across all frequency bands, resulting in an overall channel matching degree of 0.96.

[0077] For example, Figure 3 This specification illustrates a logic diagram of adjusting audio data according to one embodiment.

[0078] refer to Figure 3 First, the user inputs their hearing profile, scene data, and audio data. A channel perception test is then performed, playing audio signals of the same frequency (covering the low, mid, and high frequency bands) and loudness (initial loudness 60dB) to both the left and right channels. The user uses a slider to provide feedback on the perceived clarity difference between the two channels (0-100 points). The system then uses a channel allocation optimization layer combined with multi-band test results to determine the strength and difference (0-50%) of hearing in each ear. If a user is detected to have weak hearing in one ear (perceptual difference ≥10% between the left and right channels), key sound effects such as enemy footsteps, skill warning sounds, and mission prompts will be amplified and output to the channel with stronger hearing. The amplification gain will be calculated as "perceptual difference × 0.2" and controlled between 3-8dB. At the same time, the dual-channel balance of ambient sounds (such as wind, rain, and background noise) will be preserved. The channel mixing algorithm will ensure that the volume attenuation of ambient sounds in the amplified channel does not exceed 2dB, so as not to disrupt the immersive experience. When the user is in a non-critical sound effect scene (such as the main menu or cutscenes without interaction), the channel amplification will be automatically reduced to 1-3dB to balance the naturalness of the listening experience. If the perceptual difference between the user's left and right channels is detected to be <10%, the channel allocation will be maintained normally. The frequency parameter adjustment layer applies a gain of 0.8 times the threshold difference (0-15dB) to frequency bands with low hearing thresholds, and attenuates the gain of 0.6 times the tolerance difference (0-10dB) to harsh / over-tolerance frequency bands. The original frequency response is preserved in indifferent frequency bands. The threshold difference is the player's actual hearing threshold in the target frequency band minus the original minimum loudness of the audio in that band (i.e., the difference between the lowest loudness the player can hear and the lowest loudness of the audio itself). The tolerance difference is the original maximum loudness of the audio in that band minus the player's actual loudness tolerance in the target frequency band (i.e., the difference between the highest loudness of the audio itself and the highest loudness the player can tolerate).

[0079] Optionally, after acquiring the user's audio perception information, the method further includes: generating the user's hearing profile based on the audio perception information; and after determining the matching degree between the audio perception information and the initial audio data according to the operation output, the method further includes: updating the hearing profile based on the matching degree. This specification does not limit the scope of the embodiments described herein.

[0080] For example, Figure 4 This specification illustrates a schematic diagram of the logic of an audio dynamic adaptation engine provided in one embodiment.

[0081] refer to Figure 4Once a user enters the virtual environment, the system determines whether a test should be triggered. If not, it retrieves the user's historical hearing profile. If so, it performs frequency response perception information testing and tract perception information testing. After acquiring the user's audio perception information, the system integrates this information to generate a personalized hearing profile containing the user's perceived loudness, tolerance, perceived difference, sensitivity, and test timestamps for each frequency band. The profile supports both local encrypted storage and cloud synchronization (users can choose their preferred storage method). It also allows users to initiate a retest every 30 days, with the system automatically comparing historical data and updating hearing profile parameters to adapt to dynamic changes in the user's hearing condition.

[0082] Optionally, one way to adjust the initial loudness of each frequency band based on perceptual difference is to amplify the key sound effects by outputting them to the channel with stronger hearing, where the amplification gain is positively correlated with the perceptual difference. Another way to adjust the initial loudness of each frequency band based on perceptual difference is to adjust the loudness distribution of the left and right channels using a channel mixing algorithm to make the key sound effects perceptually balanced in both ears. This specification does not limit the scope of this method in the embodiments.

[0083] For example, for users with weaker hearing in their left ear and stronger hearing in their right ear, with a perceived difference of 20% in the 2kHz-4kHz frequency band, the system amplifies key sound effects such as footsteps and gunshots by 4dB to the right channel, while maintaining the dual-channel balance of ambient sound. This ensures that the attenuation of ambient sound in the right channel is controlled within 1dB, ensuring that users can clearly perceive key sound effects in combat scenarios, while not disrupting the immersive experience of ambient sound in non-combat scenarios.

[0084] In the embodiments of this specification, the channel matching degree is determined based on the difference in perception between the left and right channels in the channel perception information and the initial loudness corresponding to the initial audio data in each frequency band. Based on this, the initial loudness in each frequency band is adjusted, which can accurately compensate for the user's hearing imbalance in both ears. Key sound effects are amplified and output to the channel with stronger hearing, thereby making full use of the user's hearing ability on the stronger side, improving the user's perception sensitivity to key sound effects, and enabling the user to capture important sound information in the virtual scene more clearly by using the dominant channel on the stronger side of hearing.

[0085] In one optional embodiment of this specification, the initial audio data includes multiple types of audio data, and the virtual scene has a specific scene type; Before adjusting the initial audio data based on the first matching degree to obtain the first audio data, the process also includes: Based on the scene type of the virtual scene, determine the adjustment priority of various types of audio data in the virtual scene; The initial audio data is adjusted based on the first matching degree to obtain the first audio data, including: Based on the first matching degree, various types of audio data are adjusted according to the adjustment priority to obtain the first audio data.

[0086] Audio data types are categorized based on audio content or function. For example, there are sound effects audio, background music audio, and human dialogue audio.

[0087] Scene type refers to the function or atmosphere category of a virtual scene. For example, battle scenes, exploration scenes, story animation scenes, main menu scenes, social interaction scenes, etc.

[0088] Priority adjustment refers to the order in which different types of audio data are adjusted within the same scenario. For example, in a combat scenario, sound effects audio has a higher priority than background music audio. In resource scheduling and parameter adjustment for each type of audio data, adjusting the frequency gain of key target sound effects (such as warning sounds and footsteps in a combat scenario) is given higher priority. Gain compensation for these sound effects is completed first, followed by parameter adjustments for other audio (such as background music). This ensures the accuracy of key sound effect adaptation and the efficiency of information transmission.

[0089] For example, refer to Figure 3 The system acquires game scene tags in real time (combat, exploration, story animations, main menu, social interaction) and optimizes adaptation strategies for different scenes: In combat scenes, it prioritizes the adaptation of warning sounds and footsteps, increases the frequency gain priority of key sound effects by 30%, and reduces the volume of background music overlapping with key sound effect frequency bands (attenuation by 3-5dB) to reduce audio interference. In exploration scenes, it optimizes the layering of ambient sounds, slightly increasing the gain (2-3dB) of distant ambient sounds (such as distant waterfall sounds and birdsong), while maintaining the original adaptation parameters for nearby ambient sounds to enhance spatial awareness. In story animation scenes, it maintains a balance between the adaptation of dialogue and background music, increasing the frequency gain priority of dialogue by 20% to ensure clear and distinguishable dialogue and prevent it from being masked by background music. In main menu and social interaction scenes, it adopts a gentle adaptation strategy, reducing the frequency gain / attenuation range (controlled within 0-5dB) to prioritize comfortable audio listening.

[0090] Optionally, specific adaptation rules are adopted for different types of audio resources: sound effect audio focuses on the transmission of key information, and the adaptation strength is increased by 20%; background music audio focuses on atmosphere creation, and the adaptation strength is reduced by 15%; human voice dialogue audio focuses on clarity, and the mid-frequency band (500Hz-2kHz) adaptation parameters are optimized first.

[0091] Optionally, one way to determine the adjustment priority of multiple types of audio data in a virtual scene based on the scene type is to query the priority of each type of audio corresponding to the current scene according to a preset scene priority mapping table. Another way to determine the adjustment priority of multiple types of audio data in a virtual scene based on the scene type is to dynamically predict the priority of each type of audio based on scene characteristics using a machine learning model. This specification does not limit the implementation of this method.

[0092] Optionally, one implementation of adjusting multiple types of audio data according to matching degree and adjustment priority to obtain adjusted initial audio data can be: first, adjust the frequency band of the high-priority audio type, and then adjust the low-priority audio type. Another implementation of adjusting multiple types of audio data according to matching degree and adjustment priority to obtain adjusted initial audio data can be: allocate the adjustment amount according to priority weight, with higher-priority audio types receiving a larger adjustment range. This specification does not limit the implementation in this way.

[0093] For example, in a combat scenario, the system prioritizes adjusting sound effects (such as gunshots and footsteps) the highest, followed by dialogue, and then background music. When the matching degree is below a threshold, the system first boosts the frequency band containing gunshots by 2dB, then boosts the frequency band containing dialogue by 1dB, and finally attenuates the frequency bands in the background music that overlap with the gunshots by 1dB, thus obtaining the adjusted initial audio data.

[0094] It should be noted that attenuating the part of the background music that overlaps with the frequency band of a specific sound effect is done by using an EQ (equalizer) to attenuate the energy of the frequency band that overlaps with the specific sound effect (e.g., attenuating 3-5dB in a battle scene). This precise reduction of volume is only applied to the overlapping frequency band, while the non-overlapping frequency bands retain their original adaptation parameters. This reduces audio interference without disrupting the overall atmosphere of the background music.

[0095] In the embodiments of this specification, the adjustment priority of various types of audio data is determined based on the scene type of the virtual scene, and the initial audio data is adjusted according to the adjustment priority based on the first matching degree. This enables the audio adaptation strategy to adaptively adjust according to different scene types. In battle scenes, the perceptibility of key sound effects is automatically enhanced; in story scenes, the clarity of human dialogue is automatically improved; and in exploration scenes, the layering of ambient sound is automatically optimized. This achieves refined audio adaptation that is scene-adaptive and meets the differentiated audio output effects required by users in different types of virtual scenes.

[0096] In one optional embodiment of this specification, after step 106, the method further includes: Play the first audio data in the virtual scene; In response to user input in the virtual scene, obtain the corresponding operation output; Based on the operation output, determine the second degree of matching between the audio perception information and the first audio data; The first audio data is adjusted based on the second matching degree to obtain the second audio data.

[0097] Optionally, one way to play the first audio data in a virtual scene is to output the initial audio data to the user's audio playback device via an audio rendering engine. Another way to play the first audio data in a virtual scene is to push the first audio data to the user's audio playback device via a streaming protocol, dynamically adjusting the buffering strategy and bitrate of the audio data according to the network status during playback. This specification does not limit this approach.

[0098] For example, when a user enters a combat-type virtual scene, the system mixes the initial audio data using an audio rendering engine and outputs it to the user's audio playback device. By playing the initial audio data within the virtual scene, an auditory basis can be provided for the user's subsequent input.

[0099] User input refers to commands issued by the user through interactive devices within a virtual environment. Examples include keyboard keys, mouse clicks, gamepad button presses, touchscreen gestures, and voice commands.

[0100] The operation output is the response result calculated based on the operation input. For example, shooting accuracy, reaction time, mission completion rate, score, and level completion result.

[0101] Optionally, one way to obtain the operation output corresponding to the user's operation input in the virtual scene is to: listen to the user's operation input event, record the event occurrence time and the corresponding scene state, and calculate the operation output based on the operation input. Another way to obtain the operation output corresponding to the user's operation input in the virtual scene is to: capture the user's operation through the virtual engine's event system and read the feedback data corresponding to the operation from the game state. This specification does not limit the scope of this method in the embodiments.

[0102] For example, in a virtual scene, after hearing a gunshot sound effect, the user presses the left mouse button to fire. The system records this button press and the firing time, and detects whether the bullet hits the target. If the bullet hits the target, the operation output is "Hit"; if it misses, the operation output is "Miss". By responding to the user's operation input in the virtual scene and obtaining the operation output corresponding to the operation input, a data foundation is provided for determining the second matching degree between the audio perception information and the first audio data.

[0103] The second matching degree is a quantitative indicator that measures the degree of fit between the first audio data and the user's audio perception information. A higher second matching degree indicates that the audio parameter settings of the first audio data are more compatible with the user's hearing, which is more conducive to the user achieving good operating performance. For example, the higher the hit rate and the shorter the reaction time, the higher the second matching degree.

[0104] Optionally, one way to determine the second matching degree between the audio perception information and the first audio data based on the operation output is to count the number of positive operation outputs (such as hits) within a preset time period, and use the proportion of the number of positive operation outputs to the total number of operations as the second matching degree. Another way to determine the second matching degree between the audio perception information and the first audio data based on the operation output is to calculate the ratio of the user's average reaction time to the baseline reaction time, and use the reciprocal of this ratio as the second matching degree. This specification does not limit this approach in the embodiments.

[0105] For example, the system analyzes the user's reaction time from hearing the gunshot sound to firing in the last 10 encounters, calculating an average reaction time of 0.35 seconds, and comparing it to the game's baseline reaction time of 0.3 seconds. The system also counts 7 hits in these 10 encounters. The system then calculates a weighted average of the reciprocal (0.85) of the ratio of the average reaction time to the baseline time (0.35 / 0.3≈1.17) and a hit rate of 0.7, resulting in a second matching degree of 0.75. A second matching degree closer to 1 indicates that the current audio settings are more favorable to the user's performance. By determining the second matching degree between the audio perception information and the first audio data based on the user's operational output, the system can quantify the user's auditory effect on the first audio data, providing a basis for subsequent audio adjustments.

[0106] Optionally, one way to adjust the first audio data based on the second matching degree to obtain the second audio data is to increase the loudness of the frequency band associated with the operation input by a preset step size when the second matching degree is lower than a preset threshold. Another way to adjust the first audio data based on the second matching degree to obtain the second audio data is to calculate the adjustment amount of the loudness of each frequency band according to the difference between the second matching degree and the target matching degree, and apply it to the first audio data. This specification does not limit this approach in the embodiments.

[0107] For example, the system detects that the second matching degree of 0.75 is lower than the preset threshold of 0.85, determining that the audio settings of the current first audio data do not adequately support user operation performance. Since the operation input (shooting) is strongly correlated with the gunshot sound effect, and the gunshot sound effect is mainly distributed in the 2kHz-4kHz frequency band, the system increases the loudness of this frequency band by 2dB, while attenuating the part of the background music that overlaps with this frequency band by 1dB to avoid the masking effect. In the adjusted second audio data, the gunshot sound effect is more prominent, making it easier for the user to capture the shooting opportunity in complex ambient sounds.

[0108] In this embodiment, after adjusting the initial audio data based on the matching degree to obtain the first audio data, the first audio data is played in a virtual scene. In response to the user's input in the virtual scene, the corresponding operation output is obtained. Based on the operation output, a second matching degree between the audio perception information and the first audio data is determined. The first audio data is then adjusted based on the second matching degree to obtain the second audio data. By using the user's operation output in the virtual scene as the evaluation criterion for audio adaptation, the second matching degree is used to quantify the degree of fit between the first audio data and the user's audio perception information. Based on this, the first audio data is dynamically adjusted so that the second audio data, while satisfying the user's auditory perception characteristics, further matches the user's actual operation performance. This ensures auditory comfort while enabling the audio output to better support the user's operation performance in the virtual scene, meeting the personalized needs of users with different hearing abilities for audio output effects.

[0109] In one optional embodiment of this specification, the operation output includes a positive operation output and a negative operation output; Based on the operation output, determine the second matching degree between the audio perception information and the first audio data, including: The statistical operation output is the first count of a positive operation output, and / or the second count of a negative operation output; Based on the first count and / or the second count, determine the second degree of matching between the audio perception information and the first audio data.

[0110] Positive operation output represents the result indicating the success of a user's operation. Examples include hitting a target, completing a task, and earning a score.

[0111] Negative operation outputs represent the results of a failed user operation. Examples include missing the target, mission failure, or being defeated.

[0112] For example, Figure 5 This specification illustrates another logical diagram of adjusting audio data according to an embodiment of the present specification.

[0113] refer to Figure 5Real-time capture of user operation data establishes a correlation model between operation behavior and audio perception information, focusing on monitoring the following scenarios: whether skill dodging errors are caused by failure to perceive key sound effects, failure to react to enemy attacks, and failure to respond to task prompts; combining operation timestamps, corresponding scene audio parameters, and operation outputs (success / failure) extracted from program logs, and using algorithms to analyze the correlation between operation errors and audio perception information (correlation ≥ 60% is considered relevant); if the operation error is determined to be related to audio perception information, parameters are automatically fine-tuned according to the following rules: failure to dodge skills with warning sounds twice consecutively: adjust the corresponding warning sound... Increase the gain of the alarm frequency band by 2dB, and increase the channel enhancement of that frequency band (if enabled) by 1dB; if a single instance of not detecting enemy footsteps leads to a surprise attack: increase the gain of the footstep frequency band by 1.5dB, optimize the spectrum preservation algorithm parameters for that frequency band, and improve recognition; if there are 3 consecutive unresponsive task prompts: increase the gain of the human dialogue frequency band by 2dB, and reduce the volume of background music in that frequency band by 1dB; the fine-tuning range should not exceed ±2dB per instance, and the cumulative fine-tuning range should not exceed 30% of the initial adaptation parameters to avoid excessive adjustments that could cause sudden changes in the listening experience.

[0114] Optionally, the fine-tuned parameters are synchronized to the audio dynamic adaptation engine in real time, while recording the adjustment time, adjustment range, and corresponding operation scenario. Subsequently, in the same or similar scenarios, user operation feedback is continuously monitored. If there are no similar errors in 5 consecutive operations, the adaptation optimization is deemed effective, and the parameter is updated to the adaptation preference in the user's hearing profile. If there are still operational errors, the fine-tuning process is repeated (the fine-tuning range decreases by 0.5dB each time) until the adaptation effect meets the standard or the cumulative number of fine-tunings reaches 5 (if it still does not meet the standard, a pop-up window is triggered to prompt the user to retake the hearing test).

[0115] Optionally, users can temporarily adjust the adaptation strength (weak / standard / strong) during operation using shortcut keys (which can be customized). The system records the user's manual adjustment behavior as a reference for subsequent automatic adaptation optimization, realizing two-way adaptation of "automatic optimization + manual intervention".

[0116] Optionally, one way to count the first number of positive operation outputs and / or the second number of negative operation outputs can be to record user operation outputs in real time using an event listener and count the number of times based on operation type. Another way to count the first number of positive operation outputs and / or the second number of negative operation outputs can be to extract operation output records from the game log and aggregate and count them according to a preset time window. This specification does not limit the scope of these implementations.

[0117] For example, the system counts that in the user's last 20 shooting operations, the number of times the target was hit was 12 and the number of times the target was missed was 8, resulting in a first count of 12 and a second count of 8. The hit rate of 60% is used as the second matching degree.

[0118] This embodiment determines the second matching degree between audio perception information and first audio data by statistically analyzing the first number of positive operation outputs and / or the second number of negative operation outputs. This eliminates the randomness of a single operation, making the matching degree evaluation more scientific and stable, and providing a reliable quantitative basis for subsequent audio adjustments. This ensures that the optimization direction of audio parameters is consistent with the user's actual operation performance, avoids incorrect adjustments due to individual operation errors, and makes the audio adaptation process more accurate and effective.

[0119] In one optional embodiment of this specification, the initial audio data includes multiple types of audio data, each type of audio data is distributed in different frequency bands, and the operation input has a specific operation type; Before adjusting the first audio data based on the second matching degree to obtain the second audio data, the process also includes: Based on the operation type of the operation input, determine the target type of audio data associated with the operation input from multiple types of audio data; The first audio data is adjusted based on the second matching degree to obtain the second audio data, including: Based on the second matching degree, the loudness of the frequency bands distributed by the first audio data is adjusted to obtain the second audio data.

[0120] Operation type is a category that represents the user's intention or nature of the operation. For example, shooting operation, movement operation, jumping operation, interaction operation, skill release operation, etc.

[0121] Target type audio data refers to audio data types that are associated with user input. For example, gunshot sound effects associated with shooting, footsteps associated with movement, and task prompts associated with interactive operations.

[0122] Optionally, one way to determine the target type of audio data associated with an operation input from multiple types of audio data based on the operation type of the operation input can be to query the audio data type corresponding to the current operation type through a preset operation-audio mapping table. Another way to determine the target type of audio data associated with an operation input from multiple types of audio data based on the operation type of the operation input can be to predict the associated audio data type based on the operation type and scene context using a machine learning model.

[0123] Optionally, one way to adjust the loudness of the frequency band where the target type audio data is distributed based on the second matching degree to obtain the second audio data is to increase the loudness of the frequency band where the target type audio data is distributed by a preset step size when the second matching degree is lower than a preset threshold. Another way to adjust the loudness of the frequency band where the target type audio data is distributed based on the second matching degree to obtain the second audio data is to calculate the loudness adjustment amount of the frequency band where the target type audio data is distributed based on the difference between the second matching degree and the target matching degree, and apply it to that frequency band.

[0124] For example, in a virtual scene, when a user performs a shooting operation, the system identifies the operation type as "shooting" and determines the target audio data associated with the shooting operation as "gunshot sound effect" from various types of audio data. Gunshot sound effects are mainly distributed in the 2kHz-4kHz frequency band. The system detects that the current matching degree of 0.75 is lower than the preset threshold of 0.85, increases the loudness of this frequency band by 2dB, and attenuates the part of the background music that overlaps with this frequency band by 1dB to obtain the target audio data.

[0125] In the embodiments of this specification, by determining the associated target type audio data based on the operation type of the operation input, and adjusting only the loudness of the frequency bands distributed by the target type audio data, it is possible to achieve accurate attribution and precise implementation of audio adjustment, avoid unnecessary adjustments to irrelevant audio frequency bands, improve the perceptibility of key sound effects, and preserve the original listening experience of other audio to the greatest extent, thereby improving adjustment efficiency while ensuring audio adaptation effect.

[0126] In one optional embodiment of this specification, after adjusting the loudness of the frequency bands where the target type audio data is distributed based on the second matching degree to obtain the second audio data, the method further includes: Play the second audio data in the virtual scene; In response to user input in the virtual scene, obtain the corresponding operation output; Based on the operation output, determine the third degree of matching between the audio perception information and the second audio data; The target audio data is adjusted based on the third matching degree to obtain the third audio data.

[0127] For example, in a shooting game scenario, the system adjusts the frequency band of the gunshot sound effect based on a second matching degree, obtains second audio data, and plays it in the virtual scene. After hearing the adjusted gunshot sound effect, the user performs a shooting operation, and the system records the hit result as "hit". The system continues to count the subsequent 10 shooting operations, increasing the number of hits to 9, and calculates a new matching degree (third matching degree) of 0.9. The system detects that the new matching degree is still lower than the target threshold of 0.95, so it boosts the frequency band of the gunshot sound effect by 0.5dB again, while attenuating the part of the background music that overlaps with this frequency band by 0.3dB, to obtain the third audio data.

[0128] In the embodiments of this specification, after obtaining and playing the second audio data, the user's operation output is continuously collected to redetermine the matching degree between the audio perception information and the second audio data. Based on the new matching degree, the second audio data is readjusted again, which can form a continuous iterative optimization. This allows the audio parameters to continuously approach the optimal adaptation state as user operation data accumulates. It also maintains the dynamic adaptation capability of the audio output when the user's hearing condition changes or the operation habits evolve, thereby achieving continuous optimization of the audio adaptation effect.

[0129] The following example illustrates the audio adaptation method using a user in an action-based virtual scenario: The fitting process for users with mild high-frequency hearing loss: Step 1: When a user enters an action-based virtual scene for the first time, the user triggers the hearing feature acquisition module through the virtual scene client settings. After completing the frequency perception test, the profile shows that the user's hearing threshold in the 4-8kHz high-frequency band is 45dB (the normal threshold is 35dB), the feedback in the 8-10kHz frequency band is harsh, and the hearing in both ears is balanced (difference range 5%).

[0130] Step 2: When the user enters the battle scene, the audio dynamic adaptation engine performs gain compensation for the 4-8kHz frequency band by "(45-35)×0.8=8dB" (not exceeding the 15dB upper limit), and attenuates the 8-10kHz frequency band by "tolerance difference×0.6=6dB" while maintaining normal channel allocation; because it is in a battle scene, the frequency gain priority of skill warning sound and footstep sound is increased by 30%, and the volume of the 4-8kHz frequency band in the background music is reduced by 3dB.

[0131] Step 3: During the virtual interaction, if the user fails to dodge the skill with a high-frequency warning sound twice in a row, the scene adaptive verification module analyzes the operation timestamp and audio parameters, determines the correlation to be 75% (≥60%), and automatically fine-tunes the gain of the 4-8kHz frequency band to 10dB while maintaining the attenuation parameter of the 8-10kHz frequency band.

[0132] Step 4: In subsequent battles, the user can clearly perceive the warning sound, successfully dodge skills 6 times in a row, and make no similar operational errors. The verification module confirms that the adaptation optimization is effective and updates the parameters of 10dB gain in the 4-8kHz frequency band and 6dB attenuation in the 8-10kHz frequency band to the adaptation preferences of the hearing profile.

[0133] Step 5: Three months later, the user initiated a new hearing test. The file showed that the hearing threshold in the 4-8kHz frequency band dropped to 42dB. The system automatically adjusted the gain of this frequency band to "(42-35)×0.8=5.6dB", and then fine-tuned it to 6dB based on historical adaptation preferences to achieve dynamic adaptation after changes in hearing status.

[0134] Example 2: Adaptation process for users with unilateral hearing loss: Step 1: When a user first enters a role-playing virtual scene and completes the sound channel perception test, the file records that the hearing in the left ear is weaker than that in the right ear (difference range of 30%), the hearing threshold in the left ear in the 4-6kHz frequency band is 12dB higher than that in the right ear, and there are no obviously harsh frequency bands.

[0135] Step 2: The user enters the exploration scene. Enemies appear from the left. The audio dynamic adaptation engine amplifies the enemy footsteps on the left (mainly concentrated in the 4-6kHz frequency band) and outputs them to the right channel. The amplification gain is calculated as "30% × 0.2 = 6dB" (not exceeding the 8dB limit), while retaining the basic volume of ambient sounds on the left (wind, grass rustling) with only a 1dB attenuation to ensure spatial perception. Because it is an exploration scene, the ambient sounds in the distance (distant stream sound) are amplified by 2dB to enhance the sense of scene layering. The player's left ear hearing is weaker than the right ear, resulting in insufficient audio perception of the left ear channel. Amplifying the enemy footsteps on the left to the right (stronger side) allows the player to accurately capture key directional sound effects and avoid misjudging location due to weaker left ear perception. It should be noted that amplifying the output to the right channel does not completely abandon the weaker channel, but rather retains the basic volume of the ambient sounds on the left (with only a 1dB attenuation) to ensure that the player can perceive the spatial ambient sounds on the left (wind, grass rustling), balancing the recognition of key sound effects and the integrity of spatial perception.

[0136] Step 3: The user successfully captures the enemy's position on the left and responds accordingly. The verification module determines that the adaptation is effective and no parameter fine-tuning is required. Subsequently, the user can accurately locate the enemy in multiple scenes where the enemy appears on the left. The system then solidifies the 6dB channel enhancement parameter as the default adaptation parameter for that scene.

[0137] Step 4: When the user switches to the story animation scene, the system automatically reduces the channel enhancement amplitude to 2dB and increases the gain priority of the mid-frequency band (500Hz-2kHz) of the human voice dialogue to ensure clear dialogue while maintaining the volume balance between background music and dialogue.

[0138] Step 5: During virtual interaction, the user adjusts the adaptation strength to "weak" using a custom shortcut key. The system records this operation and automatically reduces the channel enhancement by 1dB in subsequent non-combat scenarios to match the user's manual intervention preference. Adaptation strength refers to the intensity of frequency gain / attenuation, channel optimization, and other adaptation operations performed for different audio types: For sound effects (critical information transmission): a 20% increase in adaptation strength → greater intensity of gain / attenuation and channel enhancement, focusing more on the recognizability of key sound effects; For background music (atmosphere creation): a 15% decrease in adaptation strength → gentler adaptation operations, reducing disruption to the overall quality of background sound; For human dialogue: no direct adjustment of adaptation strength, but targeted optimization of mid-frequency parameters (500Hz-2kHz) to prioritize clarity.

[0139] In this embodiment, personalized hearing profiles are used to accurately match individual user differences, enabling users with mild hearing loss, weak hearing in one ear, or other special hearing conditions to clearly perceive key sound effects and avoid game disadvantages caused by hearing differences. Simultaneously, dynamic updates to hearing conditions are supported to adapt to changes in user hearing over time, expanding the game's user base and enhancing product competitiveness. Targeted attenuation of harsh frequencies and strict control of loudness within the user's tolerance range effectively reduce auditory fatigue from prolonged gaming. Fine-tuning of frequency parameters reduces the potential damage to hearing from high-frequency sound effects, improving the comfort and sustainability of the gaming experience. Combined with differentiated adaptation strategies for real-time game scenarios, audio output is highly synchronized with the game progress. Closed-loop optimization through scene adaptive verification ensures that audio adaptation not only matches user hearing characteristics but also aligns with actual gaming habits and operational feedback, achieving a dynamic cycle of "perception-operation-optimization" and significantly enhancing user immersion. Furthermore, it supports users in choosing file storage methods, actively updating hearing data, and manually intervening in the adaptation effect, with flexible and diverse adaptation logic. The adaptation engine is compatible with audio resources of different types of games (action, role-playing, casual, etc.), without requiring significant modifications to the original audio production process. It can be achieved simply by integrating relevant modules into the game client, making it easy to quickly deploy in various game products.

[0140] It should be noted that the audio adaptation method provided in this manual can be applied to multiple industries or scenarios, such as virtual reality processing software, home entertainment product software, digital cultural product production software, digital cultural creative software, digital cultural creative design, education, news, cultural content industry software, digital publishing software, digital music development and production, and digital mobile multimedia development and production. In some cases, it can also be applied to fields such as animation and game production engine software and development systems, game and animation software, animation and game digital content services, digital film and television development and production, and digital performance development and production.

[0141] Corresponding to the above method embodiments, this application also provides an audio adaptation system. Figure 6 A schematic diagram of an audio adaptation system according to an embodiment of this application is shown. Figure 6 As shown, the system includes: The hearing feature acquisition module 602 is configured to acquire the user's audio perception information and the initial audio data in the virtual scene; The scene adaptive verification module 604 is configured to determine the first degree of matching between the audio perception information and the initial audio data; The audio dynamic adaptation module 606 is configured to adjust the initial audio data based on the first matching degree to obtain the first audio data.

[0142] Optionally, the audio perception information includes frequency response perception information and / or channel perception information; The scene adaptive verification module 604 is further configured as follows: Determine the frequency response matching degree between the frequency response perception information and the initial audio data; And / or, Determine the degree of channel matching between the channel perception information and the initial audio data; The audio dynamic adaptation module 606 is further configured as follows: The initial audio data is adjusted based on the frequency response matching degree to obtain the first audio data; And / or, The initial audio data is adjusted based on the channel matching degree to obtain the first audio data.

[0143] Optionally, the frequency response perception information includes perceived loudness and tolerable loudness in multiple frequency bands, and the initial audio data has corresponding initial loudness in multiple frequency bands; The scene adaptive verification module 604 is further configured as follows: The first loudness difference is determined based on the perceived loudness and the initial loudness in each frequency band. The second loudness difference is determined based on the tolerance loudness and the initial loudness in each frequency band. The frequency response matching degree is determined based on the first loudness difference and the second loudness difference; The audio dynamic adaptation module 606 is further configured as follows: The initial loudness of each frequency band is adjusted based on the frequency response matching degree to obtain the first audio data.

[0144] Optionally, the frequency response sensing information also includes the sensitivity corresponding to each frequency band; After adjusting the initial loudness of each frequency band based on the frequency response matching degree to obtain the first audio data, the audio dynamic adaptation module 606 is further configured as follows: Based on the sensitivity corresponding to each frequency band, the loudness of the first audio data in each frequency band is fine-tuned to obtain the fine-tuned first audio data.

[0145] Optionally, the channel perception information includes the perceptual difference between the left and right channels in each frequency band, and the initial audio data has corresponding initial loudness in multiple frequency bands; The scene adaptive verification module 604 is further configured as follows: Based on the perceptual difference between the left and right channels in each frequency band and the initial loudness of the initial audio data in each frequency band, the channel matching degree is determined. The audio dynamic adaptation module 606 is further configured as follows: Based on the channel matching degree, the initial loudness corresponding to each frequency band is adjusted to obtain the first audio data.

[0146] Optionally, the initial audio data includes multiple types of audio data, and the virtual scene has a specific scene type; The scene adaptive verification module 604 is further configured as follows: Based on the scene type of the virtual scene, determine the adjustment priority of various types of audio data in the virtual scene; The audio dynamic adaptation module 606 is further configured as follows: Based on the first matching degree, various types of audio data are adjusted according to the adjustment priority to obtain the first audio data.

[0147] Optionally, the audio adaptation system also includes an audio data output module, configured as follows: Play the first audio data in the virtual scene; The scene adaptive verification module 604 is further configured as follows: In response to user input in the virtual scene, obtain the corresponding operation output; Based on the operation output, determine the second degree of matching between the audio perception information and the first audio data; The audio dynamic adaptation module 606 is further configured as follows: The first audio data is adjusted based on the second matching degree to obtain the second audio data.

[0148] Optionally, the operation output includes positive operation output and negative operation output; The scene adaptive verification module 604 is further configured as follows: The statistical operation output is the first count of a positive operation output, and / or the second count of a negative operation output; Based on the first count and / or the second count, determine the second degree of matching between the audio perception information and the first audio data.

[0149] Optionally, the first audio data includes multiple types of audio data, and the virtual scene has a specific scene type; Before adjusting the initial audio data based on the first matching degree to obtain the first audio data, the scene adaptive verification module 604 is further configured as follows: Based on the scene type of the virtual scene, determine the adjustment priority of various types of audio data in the virtual scene; The audio dynamic adaptation module 606 is further configured as follows: Based on the matching degree, various types of audio data are adjusted according to the adjustment priority to obtain the first audio data.

[0150] Optionally, the first audio data includes multiple types of audio data, each type of audio data is distributed in different frequency bands, and the operation input has a specific operation type; Before adjusting the initial audio data based on the matching degree to obtain the target audio data, the scene adaptive verification module 604 is further configured as follows: Based on the operation type of the operation input, determine the target type of audio data associated with the operation input from multiple types of audio data; The audio dynamic adaptation module 606 is further configured as follows: Based on the second matching degree, the loudness of the frequency bands distributed by the target type audio data is adjusted to obtain the second audio data.

[0151] Optionally, after adjusting the loudness of the frequency bands where the target type audio data is distributed based on the second matching degree to obtain the second audio data, the audio data output module is further configured as follows: Play the second audio data in a virtual scene.

[0152] The audio adaptation system provided in this application acquires the user's audio perception information and initial audio data in a virtual scene; determines a first degree of matching between the audio perception information and the initial audio data; and adjusts the initial audio data based on the first degree of matching to obtain first audio data. By determining the degree of matching between the user's auditory perception and the initial audio data, and making targeted adjustments to the initial audio data according to the degree of matching, the adjusted audio data can match the user's auditory characteristics. This constrains the audio parameters of the initial audio data within the user's audible and tolerable threshold range, avoiding situations where the user cannot perceive key sound effects due to excessively low loudness, or where excessively high loudness causes auditory fatigue and hearing damage. This satisfies the personalized needs of users with different hearing conditions for audio output effects, avoids the mismatch between standardized audio parameters and user hearing differences that leads to the loss of key sound effects or auditory discomfort, thereby improving user auditory comfort and enhancing the fit between audio output and user auditory perception characteristics, thus improving the user's auditory experience.

[0153] The above is an illustrative scheme of an audio adaptation system according to this embodiment. It should be noted that the technical solution of this audio adaptation system and the technical solution of the aforementioned audio adaptation method belong to the same concept. Details not described in detail in the technical solution of the audio adaptation system can be found in the description of the technical solution of the aforementioned audio adaptation method. Furthermore, the components in the system embodiment should be understood as functional modules necessary to implement each step of the program flow or each step of the method; these functional modules are not actual functional divisions or separations. The system claims defined by such a set of functional modules should be understood as a functional module architecture that primarily implements the solution through the computer program described in the specification, and not as a physical system that primarily implements the solution through hardware.

[0154] Figure 7 A structural block diagram of a computing device according to one embodiment of this specification is shown. The components of the computing device 700 include, but are not limited to, a memory 710 and a processor 720. The processor 720 is connected to the memory 710 via a bus 730, and a database 750 is used to store data.

[0155] The computing device 700 also includes an access device 740, which enables the computing device 700 to communicate via one or more networks 760. Examples of these networks include a Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 740 may include one or more of any type of wired or wireless network interface (e.g., a Network Interface Controller (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0156] In one embodiment of this specification, the above-described components of the computing device 700 and Figure 7 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 7 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0157] The computing device 700 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.), smart home appliances, multimedia playback devices, smart voice interaction devices, or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 700 can also be a mobile or stationary server. A server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0158] The memory 710 is used to store computer programs / instructions, and the processor 720 is used to execute the following computer programs / instructions, which, when executed by the processor, implement the steps of the above-mentioned audio adaptation method.

[0159] The above is an illustrative scheme of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the audio adaptation method described above belong to the same concept. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the audio adaptation method described above.

[0160] An embodiment of this specification also provides a computer-readable storage medium storing a computer program / instructions that, when executed by a processor, implement the steps of the above-described audio adaptation method.

[0161] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the audio adaptation method described above belong to the same concept. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the audio adaptation method described above.

[0162] An embodiment of this specification also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described audio adaptation method.

[0163] The above is an illustrative scheme of a computer program product according to this embodiment. It should be noted that the technical solution of this computer program product and the technical solution of the audio adaptation method described above belong to the same concept. For details not described in detail in the technical solution of the computer program product, please refer to the description of the technical solution of the audio adaptation method described above.

[0164] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0165] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added or removed according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0166] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0167] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0168] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. An audio adaptation method, characterized in that, include: Acquire the user's audio perception information, as well as the initial audio data in the virtual scene; Determine the first degree of matching between the audio perception information and the initial audio data; The initial audio data is adjusted based on the first matching degree to obtain the first audio data.

2. The method according to claim 1, characterized in that, The audio perception information includes frequency response perception information and / or channel perception information. Determining the first matching degree between the audio perception information and the initial audio data includes: Determine the frequency response matching degree between the frequency response perception information and the initial audio data; And / or, Determine the channel matching degree between the channel perception information and the initial audio data; The step of adjusting the initial audio data based on the first matching degree to obtain the first audio data includes: The initial audio data is adjusted based on the frequency response matching degree to obtain the first audio data; And / or, The initial audio data is adjusted based on the channel matching degree to obtain the first audio data.

3. The method according to claim 2, characterized in that, The frequency response perception information includes perceived loudness and tolerable loudness in multiple frequency bands, and the initial audio data has corresponding initial loudness in multiple frequency bands; Determining the frequency response matching degree between the frequency response perception information and the initial audio data includes: The first loudness difference is determined based on the perceived loudness and the initial loudness in each frequency band. The second loudness difference is determined based on the tolerance loudness and the initial loudness in each frequency band. The frequency response matching degree is determined based on the first loudness difference and the second loudness difference; The adjustment of the initial audio data based on the frequency response matching degree to obtain the first audio data includes: The initial loudness of each frequency band is adjusted based on the frequency response matching degree to obtain the first audio data.

4. The method according to claim 3, characterized in that, The frequency response sensing information also includes the sensitivity corresponding to each frequency band; After adjusting the initial loudness of each frequency band based on the frequency response matching degree to obtain the first audio data, the method further includes: Based on the sensitivity corresponding to each frequency band, the loudness of the first audio data in each frequency band is fine-tuned to obtain the fine-tuned first audio data.

5. The method according to claim 2, characterized in that, The channel perception information includes the perception difference between the left and right channels in each frequency band, and the initial audio data has corresponding initial loudness in multiple frequency bands. Determining the channel matching degree between the channel perception information and the initial audio data includes: Based on the perceived difference between the left and right channels in each frequency band and the initial loudness of the initial audio data in each frequency band, the channel matching degree is determined. The adjustment of the initial audio data based on the channel matching degree to obtain the first audio data includes: Based on the channel matching degree, the initial loudness corresponding to each frequency band is adjusted to obtain the first audio data.

6. The method according to claim 1, characterized in that, The initial audio data includes various types of audio data, and the virtual scene has a specific scene type; Before adjusting the initial audio data based on the first matching degree to obtain the first audio data, the method further includes: Based on the scene type of the virtual scene, determine the adjustment priority of the various types of audio data in the virtual scene; The step of adjusting the initial audio data based on the first matching degree to obtain the first audio data includes: Based on the first matching degree, the various types of audio data are adjusted according to the adjustment priority to obtain the first audio data.

7. The method according to any one of claims 1-6, characterized in that, After adjusting the initial audio data based on the matching degree to obtain the first audio data, the method further includes: Play the first audio data in the virtual scene; In response to the user's operation input in the virtual scene, obtain the operation output corresponding to the operation input; Based on the operation output, determine the second matching degree between the audio perception information and the first audio data; The first audio data is adjusted based on the second matching degree to obtain the second audio data.

8. The method according to claim 7, characterized in that, The operation output includes positive operation output and negative operation output; Determining the second matching degree between the audio perception information and the first audio data based on the operation output includes: The first number of times the operation output is the positive operation output is counted, and / or the second number of times the operation output is the negative operation output is counted; Based on the first number of times and / or the second number of times, a second matching degree between the audio perception information and the first audio data is determined.

9. The method according to claim 7, characterized in that, The first audio data includes multiple types of audio data, each type of audio data is distributed in different frequency bands, and the operation input has a specific operation type; Before adjusting the first audio data based on the second matching degree to obtain the second audio data, the method further includes: Based on the operation type of the operation input, determine the target type audio data associated with the operation input from the multiple types of audio data; The step of adjusting the first audio data based on the second matching degree to obtain the second audio data includes: Based on the second matching degree, the loudness of the frequency bands in which the target type audio data is distributed is adjusted to obtain the second audio data.

10. The method according to claim 9, characterized in that, After adjusting the loudness of the frequency bands distributed by the target type audio data based on the second matching degree to obtain the second audio data, the method further includes: The second audio data is played in the virtual scene.

11. An audio adaptation system, characterized in that, include: The hearing feature acquisition module is configured to acquire the user's audio perception information and the initial audio data in the virtual scene; The scene adaptive verification module is configured to determine a first degree of matching between the audio perception information and the initial audio data; The audio dynamic adaptation module is configured to adjust the initial audio data based on the first matching degree to obtain the first audio data.

12. A computing device, characterized in that, include: Memory and processor; The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions, which, when executed by the processor, implement the steps of the method according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, It stores a computer program / instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 10.

14. A computer program product, characterized in that, Includes a computer program / instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 10.

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