Audio device parameter configuration method, device, equipment and storage medium

Abstract

The present invention relates to the technical field of audio device configuration, and discloses a parameter configuration method, apparatus, device, and storage medium for audio devices, for improving the accuracy of audio device parameter configuration. The parameter configuration method for an audio device includes: obtaining the type and audio format information of a current input signal source; identifying the audio content type and determining an optimal playback mode based on the type and audio format information of the input signal source; adjusting the speaker combination and channel configuration of the audio device based on the optimal playback mode; matching the volume level according to the audio content type, and adaptively adjusting the volume of the audio device based on user preferences and environmental analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of audio device configuration, and in particular to a parameter configuration method, apparatus, device and storage medium for an audio device. Background Art

[0002] In the prior art, the parameter configuration method for audio equipment is usually to directly configure the channel of the speaker based on the audio format of the input signal source in terms of channel configuration; and to rely on simple ambient noise detection to adjust the volume in terms of volume configuration. Since the parameter configuration method of the existing audio equipment ignores the characteristics of the audio itself when configuring the channel, it only considers a single factor when configuring the volume without comprehensively considering other relevant factors. Therefore, this configuration method cannot adapt to different audio content and diverse scenarios, resulting in inaccurate configuration results. Summary of the Invention

[0003] The present invention provides a parameter configuration method, apparatus, device and storage medium for an audio device to solve the problem in the prior art that the configuration method cannot adapt to different audio contents and diverse scenarios, resulting in inaccurate configuration results.

[0004] A first aspect of the present invention provides a parameter configuration method for an audio device, comprising: obtaining the type and audio format information of a current input signal source; identifying the audio content type and determining an optimal playback mode based on the type and audio format information of the input signal source; adjusting the speaker combination and channel configuration of the audio device based on the optimal playback mode; matching the volume level according to the audio content type, and performing adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis.

[0005] In a feasible implementation, obtaining the type and audio format information of the current input signal source includes: detecting the type of the currently connected input signal source through the interface of the audio device, the type of the input signal source including at least one of Bluetooth, Wi-Fi, and a wired interface; parsing the audio format of the input signal source, the audio format including at least one of MP3, WAV, FLAC, and AAC; identifying the sampling rate and bit depth of the input signal source to obtain complete audio format information.

[0006] In a feasible implementation, identifying the audio content type and determining the optimal playback mode based on the type and audio format information of the input signal source includes: querying the corresponding audio content type in a database based on the type and audio format information of the input signal source; calculating the suitability score of each playback mode corresponding to the current audio content type based on the hardware performance of the audio device, current environmental conditions and user historical preferences; and selecting the playback mode with the highest suitability score as the optimal playback mode.

[0007] In a feasible implementation, the adjusting of the speaker combination and channel configuration of the audio device based on the optimal playback mode includes: analyzing the sound effect requirements based on the optimal playback mode, and generating a speaker layout optimization plan based on the speaker performance parameter set and the spatial acoustic characteristics; adjusting the relative position, angle and spatial distribution of the speakers in the audio device according to the speaker layout optimization plan; and performing channel configuration based on the adjusted speaker layout and the optimal playback mode.

[0008] In a feasible implementation, the analyzing the sound effect requirements based on the optimal playback mode and generating a speaker layout optimization plan in combination with the speaker performance parameter set and the room acoustic characteristic parameters include: parsing the sound effect characteristic parameters in the optimal playback mode, and determining the sound effect requirement index based on the sound effect characteristic parameters; evaluating the matching degree between the sound effect requirement index and the speaker performance parameter set, and screening the speakers in the audio device based on the matching evaluation result to obtain a speaker screening result; obtaining the room acoustic characteristic parameters, the room acoustic characteristic parameters including room size, shape, reverberation time, reflection path, sound absorption coefficient and sound field distribution; and generating a speaker layout optimization plan based on the speaker screening result and the room acoustic characteristic parameters.

[0009] In a feasible implementation, the evaluating the matching degree between the sound effect requirement index and the speaker performance parameter set, and screening the speakers in the audio device based on the matching evaluation result to obtain the speaker screening result, includes: collecting the frequency response range, power output capability and distortion of each speaker in the audio device to obtain the speaker performance parameter set, wherein the speaker performance parameter set includes the performance parameters of each speaker; calculating the similarity between the performance parameters of each speaker and the sound effect index to obtain the corresponding matching degree; and eliminating speakers with a matching degree lower than a preset threshold to obtain the speaker screening result.

[0010] In a feasible implementation, the generating of the speaker layout optimization scheme based on the speaker screening results and the room acoustic characteristic parameters includes: setting an objective function for speaker layout optimization based on the speaker screening results and the room acoustic characteristic parameters; setting constraints based on the physical size and installation position of each speaker; using a genetic algorithm to perform iterative calculations under the set objective function and constraints to find the optimal combination of speaker position, angle and spatial distribution, and outputting the speaker layout optimization scheme.

[0011] In a feasible implementation, adjusting the relative position, angle and spatial distribution of speakers in an audio device according to the speaker layout optimization plan includes: controlling an electric adjustment structure in the audio device to adjust the relative position and angle of the speakers according to the speaker layout optimization plan; using an angle sensor to determine whether the angle of each speaker is correctly adjusted; and verifying whether the adjusted speaker spatial distribution meets the requirements of the speaker layout optimization plan.

[0012] In a feasible implementation, the channel configuration based on the adjusted speaker layout and the optimal playback mode includes: determining the correspondence between each sound element and the available channels according to the acoustic requirements of the optimal playback mode; and allocating the sound signals of each channel to the corresponding speakers based on the adjusted speaker layout.

[0013] In a feasible implementation, matching the volume level according to the audio content type and performing adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis includes: obtaining initial volume parameters that match the audio content type from a preset volume level library; obtaining user historical volume adjustment records from user historical preference data; collecting noise intensity values, spatial echo parameters, and ambient light intensity data of the current environment to generate an environmental feature vector; adjusting the initial volume parameters based on the user historical volume adjustment records and the environmental feature vector, and applying the adjusted volume parameters to the audio device.

[0014] In a feasible embodiment, the method of collecting the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment to generate an environmental feature vector includes: using an environmental sensor to collect the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment; inputting the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment into a preset environmental analysis model to obtain an environmental feature vector. The environmental analysis model is used in a machine learning model based on multimodal data fusion to output a normalized environmental feature vector by jointly learning the nonlinear mapping relationship between noise intensity, spatial echo and light intensity.

[0015] In a feasible implementation, the adjusting the initial volume parameter based on the user's historical volume adjustment record and the environmental feature vector includes: using the user's historical volume adjustment record to calculate the user's average volume adjustment offset for the same type of audio content and in a similar environment; inputting a preset volume compensation regression model based on the environmental feature vector, and outputting a corresponding environmental volume compensation coefficient by analyzing the synergistic influence of noise intensity, spatial echo, and light intensity; and determining the adjusted volume parameter based on the average volume adjustment offset, the environmental volume compensation coefficient, and the initial volume parameter.

[0016] A second aspect of the present invention provides a parameter configuration device for an audio device, comprising: an acquisition module for acquiring the type and audio format information of a current input signal source; an identification module for identifying the audio content type and determining an optimal playback mode based on the type and audio format information of the input signal source; an adjustment module for adjusting the speaker combination and channel configuration of the audio device based on the optimal playback mode; and an adjustment module for matching the volume level according to the audio content type, and performing adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis.

[0017] In a feasible implementation, the acquisition module is specifically used to: detect the type of the currently connected input signal source through the interface of the audio device, the type of the input signal source including at least one of Bluetooth, Wi-Fi, and a wired interface; parse the audio format of the input signal source, the audio format including at least one of MP3, WAV, FLAC, and AAC; identify the sampling rate and bit depth of the input signal source to obtain complete audio format information.

[0018] In a feasible implementation, the identification module is specifically used to: query the corresponding audio content type in the database based on the type and audio format information of the input signal source; calculate the adaptability score of each playback mode corresponding to the current audio content type based on the hardware performance of the audio device, current environmental conditions and user historical preferences; and select the playback mode with the highest adaptability score as the optimal playback mode.

[0019] In a feasible embodiment, the adjustment module includes: a first generation unit, used to analyze the sound effect requirements based on the optimal playback mode, and generate a speaker layout optimization plan in combination with the speaker performance parameter set and the spatial acoustic characteristics; a first adjustment unit, used to adjust the relative position, angle and spatial distribution of the speakers in the audio device according to the speaker layout optimization plan; a configuration unit, used to perform channel configuration based on the adjusted speaker layout and the optimal playback mode.

[0020] In a feasible embodiment, the first generating unit includes: a determining subunit, used to analyze the sound effect characteristic parameters in the optimal playback mode, and determine the sound effect requirement index based on the sound effect characteristic parameters; a screening subunit, used to evaluate the matching degree between the sound effect requirement index and the speaker performance parameter set, and screen the speakers in the audio device based on the matching evaluation result to obtain the speaker screening result; an acquiring subunit, used to acquire the room acoustic characteristic parameters, the room acoustic characteristic parameters including room size, shape, reverberation time, reflection path, sound absorption coefficient and sound field distribution; a generating subunit, used to generate a speaker layout optimization plan based on the speaker screening result and the room acoustic characteristic parameters.

[0021] In a feasible embodiment, the screening sub-unit is specifically used to: collect the frequency response range, power output capability and distortion of each speaker in the audio device to obtain a speaker performance parameter set, wherein the speaker performance parameter set includes the performance parameters of each speaker; calculate the similarity between the performance parameters of each speaker and the sound effect index to obtain the corresponding matching degree; eliminate speakers with a matching degree lower than a preset threshold to obtain a speaker screening result.

[0022] In a feasible embodiment, the generation subunit is specifically used to: set the objective function of speaker layout optimization based on the speaker screening results and the room acoustic characteristic parameters; set constraints based on the physical size and installation position of each speaker; use a genetic algorithm to perform iterative calculations under the set objective function and constraints to find the optimal speaker position, angle and spatial distribution combination, and output a speaker layout optimization plan.

[0023] In a feasible embodiment, the first adjustment unit is specifically used to: control the electric adjustment structure in the audio device to adjust the relative position and angle of the speakers according to the speaker layout optimization plan; use the angle sensor to determine whether the angle of each speaker is correctly adjusted; and verify whether the adjusted speaker spatial distribution meets the requirements of the speaker layout optimization plan.

[0024] In a feasible implementation, the configuration unit is specifically used to: determine the correspondence between each sound element and the available channels according to the acoustic requirements of the optimal playback mode; and distribute the sound signals of each channel to the corresponding speakers based on the adjusted speaker layout.

[0025] In a feasible embodiment, the adjustment module includes: a matching unit, used to obtain an initial volume parameter that matches the audio content type from a preset volume level library; an acquisition unit, used to obtain the user's historical volume adjustment records in the user's historical preference data; a second generation unit, used to collect the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment to generate an environmental feature vector; a second adjustment unit, used to adjust the initial volume parameter based on the user's historical volume adjustment record and the environmental feature vector, and apply the adjusted volume parameter to the audio device.

[0026] In a feasible embodiment, the second generation unit is specifically used to: use environmental sensors to collect the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment; input the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment into a preset environmental analysis model to obtain an environmental feature vector. The environmental analysis model is used in a machine learning model based on multimodal data fusion to output a normalized environmental feature vector by jointly learning the nonlinear mapping relationship between noise intensity, spatial echo and light intensity.

[0027] In a feasible embodiment, the second adjustment unit is specifically used to: use the user's historical volume adjustment records to calculate the user's average volume adjustment offset for the same type of audio content and in a similar environment; input a preset volume compensation regression model based on the environmental feature vector, and output a corresponding environmental volume compensation coefficient by analyzing the synergistic influence of noise intensity, spatial echo, and light intensity; and determine the adjusted volume parameter based on the average volume adjustment offset, the environmental volume compensation coefficient, and the initial volume parameter.

[0028] A third aspect of the present invention provides an electronic device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory to enable the electronic device to execute the above-mentioned parameter configuration method of the audio device.

[0029] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned method for configuring parameters of an audio device.

[0030] In the technical solution provided by the present invention, the type and audio format information of the current input signal source are obtained; based on the type and audio format information of the input signal source, the audio content type is identified and the optimal playback mode is determined; based on the optimal playback mode, the speaker combination and channel configuration of the audio device are adjusted; the volume level is matched according to the audio content type, and the adaptive volume adjustment of the audio device is performed in combination with user preferences and environmental analysis. In an embodiment of the present invention, the audio content type is identified by obtaining the signal source type and format information, and then the optimal playback mode is determined, and the speaker combination and channel configuration are adjusted, so that the audio playback is more in line with the characteristics of different audio contents. At the same time, the adaptive volume adjustment is performed in combination with the audio content type, user preferences and environmental analysis, which fully considers multiple factors, improves the accuracy of the configuration, and realizes personalized volume settings, which can bring high-quality and comfortable audio experience to users in different scenarios, greatly improving the use effect of the audio device and user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic diagram of an embodiment of a method for configuring parameters of an audio device according to an embodiment of the present invention;

[0032] Figure 2 Schematic diagram of another embodiment of a method for configuring parameters of an audio device according to an embodiment of the present invention;

[0033] Figure 3 A schematic diagram of an embodiment of a parameter configuration apparatus for an audio device according to an embodiment of the present invention;

[0034] Figure 4 A schematic diagram of another embodiment of a parameter configuration apparatus for an audio device according to an embodiment of the present invention;

[0035] Figure 5 FIG. 1 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The embodiments of the present invention provide a parameter configuration method, apparatus, device and storage medium for an audio device, which improve the configuration accuracy of the audio device by comprehensively configuring parameters based on multiple factors.

[0037] The terms "first," "second," "third," "fourth," and so on (if any) in the description and claims of the present invention and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that shown or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, product, or apparatus.

[0038] It is understandable that the execution subject of the present invention may be a parameter configuration device for an audio device, or a terminal or a server, which is not limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0039] It should be noted that the data sources used in this invention are all obtained through legal channels to ensure that all data processing complies with relevant laws and regulations and protect user privacy and data security.

[0040] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of a parameter configuration method for an audio device in an embodiment of the present invention includes:

[0041] 101. Obtain the type and audio format information of the current input signal source;

[0042] The audio input interface's detection circuitry can be utilized. Different interfaces, such as HDMI, optical fiber, and AUX, have unique electrical characteristics and protocol standards, which the detection circuitry can use to identify the signal source type. For HDMI interfaces, this can be accomplished by reading the extended display identification data, which contains detailed parameters such as the audio formats and resolutions supported by the source device. Alternatively, the driver and signal processing algorithms can be utilized. When a signal is connected, the driver performs a preliminary analysis of the input signal, extracting identification information from the signal to determine the source type. The signal processing algorithm further analyzes the audio data, identifying the audio format by identifying information such as the encoding identifier, sampling rate, and bit depth in the audio data frame header. Furthermore, the algorithm utilizes the operating system's API to obtain system identification information for the audio device. This information, combined with the hardware detection and software analysis results, provides accurate and comprehensive information on the current input signal source type and audio format.

[0043] 102. Based on the type of input signal source and audio format information, identify the audio content type and determine the optimal playback mode;

[0044] Signal source types include interfaces such as HDMI, optical fiber, or AUX, while audio format information includes key parameters such as sampling rate, bit depth, and encoding format. For example, when the input signal comes from an HDMI interface and the audio format is multi-channel LPCM or Dolby Atmos, the audio content type can be determined to be a high-definition movie or game. If the signal source is an AUX interface and the audio format is two-channel 44.1kHz and 16-bit bit depth, the audio content type may belong to the music or podcast category. Furthermore, based on a preset matching rule library, the optimal playback mode is accurately matched for different types of audio content. For example, for high-definition movies or games, a playback mode with immersive surround sound effects will be enabled, fully utilizing the advantages of multi-channel sound to enhance the spatial and three-dimensional sense of sound, making the audience or player feel as if they are in the scene. For music or podcasts, a playback mode that focuses on sound quality restoration and detail expression is adopted, optimizing the audio frequency response curve, improving the clarity and purity of the sound, and ensuring that every note and every word can be clearly distinguished, thereby providing users with the best audio playback experience.

[0045] 103. Adjust the speaker combination and channel configuration of the audio device based on the optimal playback mode;

[0046] Analyze the specific requirements of the optimal playback mode for speaker combination and channel configuration.

[0047] For example, for immersive surround sound playback modes, the position and angle of each speaker in the audio device are calculated based on spatial acoustics principles and speaker performance parameters. For playback modes that prioritize sound quality and detail, the position and angle of each speaker in the audio device are calculated based on the spectral characteristics of the audio signal, the speaker's frequency response curve, and the required uniformity of the sound field.

[0048] For the immersive surround sound playback mode, a sound wave propagation simulation algorithm is used to analyze the reflection, diffraction and other phenomena of sound in the space. Combined with the speaker's frequency response curve, directional characteristics and other performance parameters, a genetic algorithm or particle swarm optimization algorithm is used to iteratively calculate the optimal position and angle of each speaker with the goal of creating a uniform sound field and reducing sound coloration.

[0049] For playback modes that focus on sound quality restoration and detail expression, audio analysis software is used to analyze the spectral characteristics of the audio signal, clarify the energy distribution in different frequency bands, and combine the frequency response curves of each speaker to determine the optimal frequency band for each speaker through mathematical modeling. A three-dimensional model of the listening room is constructed. Based on the requirements of sound field uniformity, a particle swarm optimization algorithm is used. With the goal of minimizing the difference in sound pressure levels in each frequency band, the speaker positions and angles are iteratively calculated. For example, high-frequency speakers are placed at a height close to ear level to reduce reflections, low-frequency speakers are placed in corners to optimize standing waves, and mid-frequency speakers are placed directly opposite the listening position to ensure clarity, thereby achieving accurate sound quality restoration.

[0050] For example, in a living room environment, the front left and right speakers will be placed at an appropriate distance on both sides of the screen, the center speaker will be located in the center of the screen, and the rear surround speakers will be installed on the rear sides or rear corners according to the size and shape of the room to create a realistic surround sound field.

[0051] For example, in a professional listening room of moderate size, in order to accurately restore the high-frequency details in the audio signal, speakers with excellent high-frequency response will be placed close to the listening position and at a moderate height to reduce the reflection and attenuation of high-frequency signals; for the mid-frequency part, speakers with flat frequency response and low distortion are selected and placed directly in front of the listening area to ensure the clear presentation of the fundamental frequencies of human voices and instruments; low-frequency speakers are placed in the corners of the room or in acoustically treated locations according to the low-frequency standing waves in the room. By adjusting their position and angle, the low-frequency energy is evenly distributed throughout the listening space to avoid low-frequency roar or local over-intensity, thereby achieving high-fidelity restoration of full-band sound quality.

[0052] In terms of channel configuration, a digital signal processor (DSP) can distribute and process audio signals in real time. Specifically, for multi-channel audio sources, the DSP accurately distributes the sound signals of different channels to the corresponding speakers, while adjusting parameters such as gain, delay, and phase of each channel to ensure that the sound is synchronized and coordinated in the space. Furthermore, the DSP can monitor the operating status of the speakers in real time, such as temperature and power, and dynamically adjust the speaker combination and channel configuration based on actual conditions to ensure that the audio equipment is always in optimal working condition, providing users with a superior audio experience.

[0053] 104. Match the volume level according to the audio content type, and perform adaptive volume adjustment of the audio device based on user preferences and environmental analysis.

[0054] A database mapping audio content types to initial volume levels is pre-established. For different audio types, such as movies, music, and news, appropriate initial volume ranges are set based on their dynamic ranges and acoustic characteristics. Once the currently playing audio content type is identified, the corresponding initial volume level is extracted from the database.

[0055] Collect user volume preference information, including customary volume settings for different time periods and scenarios, as well as personalized volume adjustments. Also, collect real-time ambient noise data and use digital signal processing algorithms to analyze noise intensity, frequency distribution, and other characteristics to calculate the equivalent sound level of the ambient noise.

[0056] The final volume parameters are determined based on the user's volume preference information, the equivalent sound level of ambient noise, and the initial volume level. Specifically, different weight coefficients are set for the initial volume level, user volume preference information, and the equivalent sound level of ambient noise. These weight coefficients can be dynamically adjusted based on actual application scenarios and user feedback. For the initial volume level, its weight mainly reflects the acoustic characteristic benchmark of different types of audio content. For example, due to the large dynamic range of movie audio, the initial volume level weight is relatively high to ensure basic sound expressiveness. The weight of the user's volume preference information reflects their personalized needs. If the user frequently adjusts the volume during specific time periods and scenarios, the weight of their corresponding preference information will increase accordingly. The weight of the equivalent sound level of ambient noise is used to balance external noise interference. When the ambient noise is high, this weight will increase to ensure that the audio can still be heard clearly in noisy environments. Then, the initial volume level, the quantized user volume preference value (for example, mapping the preferred volume for different time periods to a specific numerical range), and the equivalent sound level of ambient noise are weighted and summed to obtain a preliminary volume adjustment value. Next, a fuzzy logic control mechanism is introduced to fine-tune the preliminary adjustment value, considering the smoothness and comfort of volume changes to avoid sudden volume changes that may cause discomfort to the user. For example, if the initial calculated volume change is too large, the fuzzy logic will appropriately reduce the change to achieve gradual volume adjustment. Finally, after multi-weight fusion and fuzzy logic fine-tuning, the final volume parameter that best meets the user's needs and environmental conditions is determined, achieving adaptive volume adjustment of the audio device.

[0057] For example, consider watching a movie in the living room at night using audio equipment. If the initial volume level is 50 and the equivalent sound level of the current living room ambient noise is 30, based on the user volume preference information, it is determined that the user is accustomed to setting the volume between 40 and 45 when watching movies between 8 and 10 p.m., and has previously manually adjusted the volume to 42 multiple times during this time period. Considering the characteristics and importance of movie audio, the weight of the initial volume level is set to 0.4. Since users have clear volume preferences during this time period, the weight of user volume preference information is set to 0.4. Ambient noise will have a certain impact on the viewing experience, and the weight of the equivalent sound level of ambient noise is set to 0.2. The user volume preference information is quantified, and the middle value of the user's accustomed volume range, 42.5, is taken as the representative value. According to the weighted summation formula: Initial volume adjustment value = Initial volume level × weight of initial volume level + user volume preference value × weight of user volume preference information + equivalent sound level of ambient noise × weight of equivalent sound level of ambient noise = 50 × 0.4 + 42.5 × 0.4 + 30 × 0.2 = 20 + 17 + 6 = 43. Considering the smoothness of volume changes, if the initial calculated volume change amplitude is compared with the current volume (assuming the current volume is 40), the change amplitude is 3, which is within the acceptable range. However, to further improve the user experience, the fuzzy logic control mechanism decides to fine-tune the volume to 42. After multi-weight fusion and fuzzy logic fine-tuning, the final volume parameter was determined to be 42. The audio device will play movies at this volume, which not only takes into account the characteristics of movie audio, but also meets the personalized needs of users, while adapting to environmental noise conditions and providing users with a comfortable viewing experience.

[0058] In an embodiment of the present invention, by obtaining the type and audio format information of the current input signal source; based on the type and audio format information of the input signal source, identifying the audio content type and determining the optimal playback mode, adjusting the speaker combination and channel configuration of the audio device based on the optimal playback mode, matching the volume level according to the audio content type, and combining user preferences and environmental analysis to perform adaptive volume adjustment of the audio device, full consideration is given to multiple factors, adapting to different audio content and diverse scenarios, improving the accuracy of audio device parameter configuration, and realizing personalized volume setting, which can bring users a high-quality and comfortable audio experience in different scenarios, and greatly improving the use effect and user satisfaction of the audio device.

[0059] See also Figure 2 Another embodiment of the parameter configuration method of the audio device in the embodiment of the present invention includes:

[0060] 201. Obtain the type and audio format information of the current input signal source;

[0061] Detect the type of the currently connected input signal source through the interface of the audio device, and the type of the input signal source includes at least one of Bluetooth, Wi-Fi, and wired interface; parse the audio format of the input signal source, and the audio format includes at least one of MP3, WAV, FLAC, and AAC; identify the sampling rate and bit depth of the input signal source to obtain complete audio format information.

[0062] 202. Based on the type of the input signal source and the audio format information, identify the audio content type and determine the optimal playback mode;

[0063] Based on the type and audio format information of the input signal source, the corresponding audio content type is queried in the database; based on the hardware performance of the audio device, the current environmental conditions and the user's historical preferences, the adaptability score of each playback mode corresponding to the current audio content type is calculated; and the playback mode with the highest adaptability score is selected as the optimal playback mode.

[0064] A pre-built database containing the correspondence between signal source type, audio format information, and audio content type is used. Using a data retrieval algorithm, the corresponding audio content type is quickly retrieved based on the acquired signal source type and audio format information. For example, when a user connects a device via Bluetooth and plays an MP3 song, the data retrieval algorithm can quickly find the corresponding audio content type in the database as "music" based on the signal source type (Bluetooth) and audio format information (MP3).

[0065] Collect hardware performance parameters of audio devices, such as the frequency response range, power, distortion of speakers, and computing power of processors; collect current environmental condition data through environmental sensors, including room size, reverberation time, background noise intensity, etc.; extract user historical preferences from user historical usage records, such as the frequency of selecting playback modes for different types of audio, volume adjustment habits, etc.; use a multi-factor weighted scoring model to set reasonable weight coefficients for hardware performance, environmental conditions, and user historical preferences, and quantitatively score the degree of adaptability of each playback mode to the current audio content type based on each factor, and calculate the adaptability score of each playback mode. For example, for immersive playback mode, if the audio device hardware supports multi-channel output and the room reverberation time is moderate, and the user has a historical preference for this mode, then the mode will score higher; by comparing the adaptability scores of each playback mode, select the playback mode with the highest score as the optimal playback mode.

[0066] 203. Analyze sound effect requirements based on the optimal playback mode, and generate a speaker layout optimization plan based on the speaker performance parameter set and spatial acoustic characteristics;

[0067] Analyze the sound effect characteristic parameters in the optimal playback mode and determine the sound effect requirement indicators based on the sound effect characteristic parameters; evaluate the matching degree between the sound effect requirement indicators and the speaker performance parameter set, and screen the speakers in the audio equipment based on the matching evaluation results to obtain the speaker screening results; obtain the room acoustic characteristic parameters, which include room size, shape, reverberation time, reflection path, sound absorption coefficient and sound field distribution; generate a speaker layout optimization plan based on the speaker screening results and room acoustic characteristic parameters.

[0068] Extract sound effect characteristic parameters such as frequency response range, dynamic range, sound field width, surround sound effect intensity from the optimal playback mode, and determine the multi-dimensional sound effect demand indicators covering low-frequency impact, mid-frequency clarity, high-frequency delicacy, sound field uniformity, etc. based on these parameters; collect detailed performance parameters of each speaker in the audio equipment, including frequency response curve, power output capacity, distortion, directivity characteristics, etc., to obtain a speaker performance parameter set, and use a similarity calculation model and matching evaluation algorithm to compare and quantify the performance parameters of each speaker with the sound effect demand indicators one by one, evaluate the matching between them, set a reasonable matching threshold, and eliminate speakers with a matching degree lower than the threshold to obtain speaker screening results that meet the sound effect requirements, and use advanced acoustic measurement equipment and professional acoustic analysis software to obtain the room acoustic characteristic parameters. Specifically, by arranging multiple measurement points in the room, using sound level meters, microphone arrays, etc. The equipment collects sound signals and analyzes them to obtain parameters such as room size, shape, reverberation time, reflection path, sound absorption coefficient and sound field distribution. For the reverberation time, the impulse response measurement method is used to accurately calculate it by analyzing the attenuation process of sound in the room. The reflection path is determined by simulating the propagation trajectory of sound in the room through the sound ray tracing algorithm; the sound absorption coefficient is obtained by measuring the sound absorption performance of different materials using the standing wave tube method or the reverberation chamber method; based on the speaker screening results and the acoustic characteristic parameters of the room, a multi-objective optimization algorithm is used to generate an optimization plan for the speaker layout. Specifically, the objective function is to achieve the highest sound field uniformity, the most accurate sound positioning, and the minimum low-frequency standing wave interference. At the same time, considering the constraints such as the physical size of the speaker, installation location restrictions, and wiring rationality, a genetic algorithm or a particle swarm optimization algorithm is used to iteratively search in the multi-dimensional solution space, and continuously adjust the position, angle, and spatial distribution of the speakers to find the optimal speaker layout combination, and finally obtain the speaker layout optimization plan.

[0069] Evaluate the matching degree between the sound effect requirement index and the speaker performance parameter set, and screen the speakers in the audio device based on the matching evaluation result. The specific execution steps to obtain the speaker screening result are: collect the frequency response range, power output capacity and distortion of each speaker in the audio device to obtain the speaker performance parameter set, which includes the performance parameters of each speaker; calculate the similarity between the performance parameters of each speaker and the sound effect index to obtain the corresponding matching degree; eliminate the speakers with a matching degree lower than the preset threshold to obtain the speaker screening result.

[0070] By sending test signals of varying frequencies, the frequency response range of each speaker was measured, and its output amplitude and phase response at different frequencies were recorded. A power meter was used to measure the speaker's power output capacity under different input signals, obtaining parameters such as maximum power and rated power. A distortion meter was used to test the speaker's distortion at various volume levels and frequencies, obtaining specific values ​​such as harmonic distortion and intermodulation distortion. This data was then integrated into a speaker performance parameter set containing detailed information on each speaker's frequency response range, power output capacity, and distortion. For each speaker, a cosine similarity algorithm was used to calculate the similarity between its performance parameters and the sound quality index. The frequency response range of the speaker was compared with the frequency distribution requirements of the sound quality requirements, and the similarity between the two was calculated in the frequency domain. For power output capacity, the speaker's power was evaluated based on the dynamic range requirements of the sound quality requirements, and the similarity was calculated. For distortion, the similarity between the speaker's distortion and the expected value was calculated based on the sound purity requirements of the sound quality requirements. The similarities in these three dimensions were weighted and combined to determine the matching degree between each speaker and the sound quality index. A reasonable preset threshold is set, which can be adjusted according to the overall performance requirements of the audio device and the importance of the sound effect requirements. Speakers with a matching degree lower than the preset threshold are judged as unable to meet the sound effect requirements and are removed from the speaker list, thereby obtaining a speaker screening result that meets the sound effect requirements.

[0071] The specific execution steps for generating a speaker layout optimization plan based on the speaker screening results and room acoustic characteristic parameters are as follows: based on the speaker screening results and room acoustic characteristic parameters, set the objective function for speaker layout optimization; based on the physical size and installation position of each speaker, set constraints; use a genetic algorithm to perform iterative calculations under the set objective function and constraints to find the optimal combination of speaker position, angle and spatial distribution, and output the speaker layout optimization plan.

[0072] Based on the speaker screening results, the speaker set participating in the layout optimization is determined. Combined with the room acoustic characteristic parameters, such as room size, shape, reverberation time, reflection path, sound absorption coefficient and sound field distribution, the objective function of the speaker layout optimization is set. The objective function can comprehensively consider the sound field uniformity, sound clarity and surround sound effect. Among them, the sound field uniformity is measured by calculating the difference in sound pressure levels at different positions in the room, the sound clarity is evaluated based on the proportional relationship between direct sound and reflected sound, and the surround sound effect is determined based on the phase difference and time difference between the speakers. These indicators are quantified and weightedly summed to construct an objective function that can comprehensively reflect the advantages and disadvantages of the speaker layout.

[0073] Based on the physical size and installation location of each speaker, set constraints. Specifically, measure the length, width, and height of the speakers to determine their space occupancy. Combined with the room layout, consider the wall load-bearing capacity and wiring direction to determine the installation area. Based on acoustic requirements, set the minimum distance between speakers to prevent sound interference and ensure optimal sound quality.

[0074] When using a genetic algorithm to perform iterative calculations under the set objective function and constraints to output a speaker layout optimization plan, a group of random speaker positions, angles and spatial distributions are first initialized as population individuals, and objective functions such as sound field uniformity and sound clarity are quantified and weights are set to construct a fitness function. Feasible solutions are screened based on constraints such as the physical size, installation position and minimum spacing of the speakers. A new population is generated through selection, crossover and mutation operations, and it is iterated generation by generation, retaining individuals with high fitness and eliminating individuals with low fitness until the termination conditions are met. Finally, an optimization plan for the optimal combination of speaker positions, angles and spatial distribution is output.

[0075] 204. Adjust the relative position, angle and spatial distribution of speakers in the audio equipment according to the optimal speaker layout plan;

[0076] Control the electric adjustment structure in the audio equipment to adjust the relative position and angle of the speakers according to the speaker layout optimization plan; use angle sensors to determine whether the angle of each speaker is adjusted correctly; and verify whether the adjusted speaker spatial distribution meets the requirements of the speaker layout optimization plan.

[0077] With the help of the electric adjustment structure equipped with the audio equipment, the speakers are driven to move to the specified position and adjusted to the corresponding angle through preset control instructions. During the adjustment process, the angle sensor is used to monitor the angle changes of each speaker in real time, and the data fed back by the sensor is compared with the set value of the speaker layout optimization plan to determine whether the angle is accurately adjusted. After the adjustment is completed, three-dimensional space measurement technology and acoustic simulation software are used to comprehensively verify whether the adjusted speaker space distribution strictly meets the requirements of the speaker layout optimization plan.

[0078] 205. Perform channel configuration based on the adjusted speaker layout and optimal playback mode;

[0079] According to the acoustic requirements of the optimal playback mode, the correspondence between each sound element and the available channels is determined; based on the adjusted speaker layout, the sound signals of each channel are distributed to the corresponding speakers.

[0080] Analyze the acoustic characteristics of the optimal playback mode, clarify the positioning and performance requirements of different sound elements in the sound field, such as dialogue, background music, and ambient sound effects, so as to determine the correspondence between each sound element and the available channels. Combined with the adjusted speaker layout, considering the position, angle, and performance characteristics of the speakers, use audio processing algorithms and mapping rules to distribute the sound signals of each channel to the corresponding speakers to ensure that each speaker can accurately reproduce the sound element it is responsible for.

[0081] 206. Obtaining an initial volume parameter that matches the audio content type from a preset volume level library;

[0082] Identify the audio content type and determine its category, such as music, movies, news, etc. The preset volume level library sets professionally adjusted initial volume parameter ranges for different audio types. Based on the recognition results, quickly search and extract the matching initial volume parameters in the volume level library.

[0083] 207. Obtain the user's historical volume adjustment records in the user's historical preference data;

[0084] Access a database dedicated to storing user preference data, which records the volume adjustment operations performed by users for different audio content types when using audio devices in the past, including adjustment time, amplitude, audio type and other information. Through a specific query algorithm, historical volume adjustment records related to the target audio are accurately filtered out from massive data.

[0085] 208. Collect the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment to generate an environmental feature vector;

[0086] Environmental sensors are used to collect the noise intensity value, spatial echo parameters, and ambient light intensity data of the current environment. The noise intensity value, spatial echo parameters, and ambient light intensity data of the current environment are input into a preset environmental analysis model to obtain an environmental feature vector. The environmental analysis model is used in a machine learning model based on multimodal data fusion to output a normalized environmental feature vector by jointly learning the nonlinear mapping relationship between noise intensity, spatial echo, and light intensity.

[0087] 209. Adjust the initial volume parameter based on the user's historical volume adjustment record and the environment feature vector, and apply the adjusted volume parameter to the audio device.

[0088] Using the user's historical volume adjustment records, the average volume adjustment offset of the user under the same audio content type and in similar environment is calculated; based on the environmental feature vector input, a preset volume compensation regression model is input, and by analyzing the synergistic influence of noise intensity, spatial echo and light intensity, the corresponding environmental volume compensation coefficient is output; based on the average volume adjustment offset, the environmental volume compensation coefficient and the initial volume parameter, the adjusted volume parameter is determined.

[0089] The audio content types in the user's historical volume adjustment records are classified through text recognition and feature extraction technology. At the same time, sensor data and pattern recognition algorithms are combined to quantify environmental similarity indicators based on factors such as temperature, humidity, and spatial layout. Adjustment records with similar audio content and within the similarity threshold are screened out, and the offset data of each adjustment is extracted. The arithmetic average method is used to add up all valid offsets and divide them by the number of records to obtain the average volume adjustment offset, which reflects the user's general volume preference trend in this type of audio and environment.

[0090] The volume compensation regression model utilizes a deep learning architecture and is pre-trained using a large amount of labeled environmental features and corresponding volume compensation coefficients. During model training, a backpropagation algorithm continuously optimizes network parameters to accurately learn the synergistic influence of noise intensity, spatial echo, and light intensity. In practical applications, the collected environmental feature vectors are input into the trained model, which then calculates and outputs the corresponding environmental volume compensation coefficients through forward propagation.

[0091] Sets the first weight for the average volume adjustment offset , the environmental volume compensation coefficient sets the second weight , + =1, the comprehensive adjustment coefficient is calculated based on the initial volume parameter, average volume adjustment offset, ambient volume compensation coefficient, first weight and second weight , and calculate the adjusted volume parameters based on the comprehensive adjustment coefficient and the initial volume parameters.

[0092] Comprehensive adjustment parameters The calculation formula is:

[0093]

[0094] Adjusted volume parameter = initial volume parameter ×

[0095] For example, if the initial volume parameter is set to 50, the average volume adjustment offset is 7.2, and the ambient volume compensation coefficient is 0.8, =0.5, =0.5, then , then the adjusted volume parameter = 50 × 0.972 ≈ 49. If the initial volume parameter is set to 50, the average volume adjustment offset is 7.2, and the ambient volume compensation coefficient is 0.8, =0.7, =0.3, then , then the adjusted volume parameter = 50×1.0408≈52.

[0096] In an embodiment of the present invention, by obtaining the type and audio format information of the current input signal source, identifying the audio content type and determining the optimal playback mode based on the type and audio format information of the input signal source, analyzing sound effect requirements based on the optimal playback mode, and generating a speaker layout optimization plan based on a speaker performance parameter set and spatial acoustic characteristics, the relative position, angle, and spatial distribution of the speakers in the audio device are adjusted according to the speaker layout optimization plan, and channel configuration is performed based on the adjusted speaker layout and optimal playback mode. Initial volume parameters matching the audio content type are obtained from a preset volume level library, user historical volume adjustment records are obtained from user historical preference data, and noise intensity values, spatial echo parameters, and ambient light intensity data of the current environment are collected to generate an environmental feature vector. The initial volume parameters are adjusted based on the user historical volume adjustment records and the environmental feature vector, thereby achieving personalized adaptive volume adjustment. Parameter configuration is performed based on multiple factors to adapt to different audio content and diverse scenarios, greatly improving the configuration accuracy of the audio device and providing users with a higher-quality, more comfortable, and more customized audio experience in different scenarios.

[0097] The above describes the parameter configuration method of the audio device in the embodiment of the present invention. The following describes the parameter configuration device of the audio device in the embodiment of the present invention. Figure 3 In one embodiment of the present invention, a parameter configuration apparatus for an audio device includes:

[0098] The acquisition module 301 is used to obtain the type and audio format information of the current input signal source;

[0099] Identification module 302, for identifying the audio content type and determining the optimal playback mode based on the type of input signal source and audio format information;

[0100] An adjustment module 303 is configured to adjust the speaker combination and channel configuration of the audio device based on the optimal playback mode;

[0101] The adjustment module 304 is configured to match the volume level according to the audio content type and perform adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis.

[0102] In an embodiment of the present invention, by obtaining the type and audio format information of the current input signal source; based on the type and audio format information of the input signal source, identifying the audio content type and determining the optimal playback mode, adjusting the speaker combination and channel configuration of the audio device based on the optimal playback mode, matching the volume level according to the audio content type, and combining user preferences and environmental analysis to perform adaptive volume adjustment of the audio device, full consideration is given to multiple factors, adapting to different audio content and diverse scenarios, improving the accuracy of audio device parameter configuration, and realizing personalized volume setting, which can bring users a high-quality and comfortable audio experience in different scenarios, and greatly improving the use effect and user satisfaction of the audio device.

[0103] See also Figure 4 Another embodiment of the parameter configuration apparatus for an audio device according to the present invention includes:

[0104] The acquisition module 301 is used to obtain the type and audio format information of the current input signal source;

[0105] Identification module 302, for identifying the audio content type and determining the optimal playback mode based on the type of input signal source and audio format information;

[0106] An adjustment module 303 is configured to adjust the speaker combination and channel configuration of the audio device based on the optimal playback mode;

[0107] The adjustment module 304 is configured to match the volume level according to the audio content type and perform adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis.

[0108] Optionally, the acquisition module 301 may be specifically configured to:

[0109] Detect the type of the currently connected input signal source through the interface of the audio device, and the type of the input signal source includes at least one of Bluetooth, Wi-Fi, and wired interface; parse the audio format of the input signal source, and the audio format includes at least one of MP3, WAV, FLAC, and AAC; identify the sampling rate and bit depth of the input signal source to obtain complete audio format information.

[0110] Optionally, the identification module 302 may be specifically configured to:

[0111] Based on the type and audio format information of the input signal source, the corresponding audio content type is queried in the database; based on the hardware performance of the audio device, the current environmental conditions and the user's historical preferences, the adaptability score of each playback mode corresponding to the current audio content type is calculated; and the playback mode with the highest adaptability score is selected as the optimal playback mode.

[0112] Optionally, the adjustment module 303 includes:

[0113] The first generating unit 3031 is configured to analyze the sound effect requirements based on the optimal playback mode, and generate a speaker layout optimization solution based on the speaker performance parameter set and the spatial acoustic characteristics;

[0114] The first adjustment unit 3032 is configured to adjust the relative positions, angles, and spatial distribution of speakers in the audio device according to the speaker layout optimization plan;

[0115] The configuration unit 3033 is used to configure the sound channels based on the adjusted speaker layout and the optimal playback mode.

[0116] Optionally, the first generating unit 3031 includes:

[0117] The determination subunit 30311 is configured to analyze the sound effect characteristic parameters in the optimal playback mode and determine the sound effect requirement index based on the sound effect characteristic parameters;

[0118] The screening subunit 30312 is used to evaluate the matching degree between the sound effect requirement index and the speaker performance parameter set, and screen the speakers in the audio device based on the matching degree evaluation result to obtain a speaker screening result;

[0119] An acquisition subunit 30313 is used to acquire room acoustic characteristic parameters, which include room size, shape, reverberation time, reflection path, sound absorption coefficient, and sound field distribution;

[0120] The generating subunit 30314 is used to generate a speaker layout optimization solution based on the speaker screening results and the room acoustic characteristic parameters.

[0121] Optionally, the screening subunit 30312 may be specifically configured to:

[0122] The frequency response range, power output capability, and distortion of each speaker in the audio device are collected to obtain a speaker performance parameter set, which includes the performance parameters of each speaker. The similarity between the performance parameters of each speaker and the sound effect index is calculated to obtain the corresponding matching degree. Speakers with a matching degree lower than a preset threshold are eliminated to obtain the speaker screening result.

[0123] Optionally, the generating subunit 30314 may be specifically configured to:

[0124] Based on the speaker screening results and room acoustic characteristic parameters, the objective function for speaker layout optimization is set; based on the physical size and installation position of each speaker, constraints are set; a genetic algorithm is used to perform iterative calculations under the set objective function and constraints to find the optimal combination of speaker position, angle and spatial distribution, and output the speaker layout optimization plan.

[0125] Optionally, the configuration unit 3033 may be specifically configured to:

[0126] According to the acoustic requirements of the optimal playback mode, the correspondence between each sound element and the available channels is determined; based on the adjusted speaker layout, the sound signals of each channel are distributed to the corresponding speakers.

[0127] Optionally, the adjustment module 304 includes:

[0128] The matching unit 3041 is configured to obtain an initial volume parameter that matches the audio content type from a preset volume level library;

[0129] An acquiring unit 3042 is configured to acquire a user's historical volume adjustment records from the user's historical preference data;

[0130] The second generating unit 3043 is used to collect the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment to generate an environmental feature vector;

[0131] The second adjusting unit 3044 is configured to adjust the initial volume parameter based on the user's historical volume adjustment record and the environment feature vector, and apply the adjusted volume parameter to the audio device.

[0132] Optionally, the second generating unit 3043 may be specifically configured to:

[0133] Environmental sensors are used to collect the noise intensity value, spatial echo parameters, and ambient light intensity data of the current environment. The noise intensity value, spatial echo parameters, and ambient light intensity data of the current environment are input into a preset environmental analysis model to obtain an environmental feature vector. The environmental analysis model is used in a machine learning model based on multimodal data fusion to output a normalized environmental feature vector by jointly learning the nonlinear mapping relationship between noise intensity, spatial echo, and light intensity.

[0134] Optionally, the second adjusting unit 3044 may be specifically configured to:

[0135] Using the user's historical volume adjustment records, the average volume adjustment offset of the user under the same audio content type and in similar environment is calculated; based on the environmental feature vector input, a preset volume compensation regression model is input, and by analyzing the synergistic influence of noise intensity, spatial echo and light intensity, the corresponding environmental volume compensation coefficient is output; based on the average volume adjustment offset, the environmental volume compensation coefficient and the initial volume parameter, the adjusted volume parameter is determined.

[0136] In an embodiment of the present invention, by obtaining the type and audio format information of the current input signal source, identifying the audio content type and determining the optimal playback mode based on the type and audio format information of the input signal source, analyzing sound effect requirements based on the optimal playback mode, and generating a speaker layout optimization plan based on a speaker performance parameter set and spatial acoustic characteristics, the relative position, angle, and spatial distribution of the speakers in the audio device are adjusted according to the speaker layout optimization plan, and channel configuration is performed based on the adjusted speaker layout and optimal playback mode. Initial volume parameters matching the audio content type are obtained from a preset volume level library, user historical volume adjustment records are obtained from user historical preference data, and noise intensity values, spatial echo parameters, and ambient light intensity data of the current environment are collected to generate an environmental feature vector. The initial volume parameters are adjusted based on the user historical volume adjustment records and the environmental feature vector, thereby achieving personalized adaptive volume adjustment. Parameter configuration is performed based on multiple factors to adapt to different audio content and diverse scenarios, greatly improving the configuration accuracy of the audio device and providing users with a higher-quality, more comfortable, and more customized audio experience in different scenarios.

[0137] above Figure 3 and Figure 4 The parameter configuration apparatus of the audio device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The electronic device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0138] See also Figure 5 As shown, the electronic device includes a processor 500 and a memory 501 . The memory 501 stores machine-executable instructions that can be executed by the processor 500 . The processor 500 executes the machine-executable instructions to implement the above-mentioned parameter configuration method of the audio device.

[0139] Further, Figure 5 The electronic device shown further includes a bus 502 and a communication interface 503 , and the processor 500 , the communication interface 503 and the memory 501 are connected via the bus 502 .

[0140] The memory 501 may include a high-speed random access memory (RAM) and may also include a non-volatile memory (non-volatile memory), for example, at least one disk storage. The communication connection between the system network element and at least one other network element is achieved through at least one communication interface 503 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used. The bus 502 may be an ISA bus, a PCI bus, or an EISA bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0141] The processor 500 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits or software instructions in the processor 500. The processor 500 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present disclosure may be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory 501 , and the processor 500 reads the information in the memory 501 and completes the method steps of the aforementioned embodiment in combination with its hardware.

[0142] The present invention further provides an electronic device, wherein the computer device includes a memory and a processor, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor performs the steps of the audio device parameter configuration method described in each of the above embodiments. The present invention further provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions. When the instructions are executed on a computer, the computer performs the steps of the audio device parameter configuration method.

[0143] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0144] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0145] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A parameter configuration method for an audio device, characterized in that: The parameter configuration method of the audio device includes: Get the type and audio format information of the current input signal source; Based on the type of the input signal source and the audio format information, identifying the audio content type and determining the optimal playback mode; adjusting the speaker combination and channel configuration of the audio device based on the optimal playback mode; Matching the volume level according to the audio content type and performing adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis; The method of matching the volume level according to the audio content type and performing adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis includes: obtaining an initial volume parameter matching the audio content type from a preset volume level library; obtaining a user's historical volume adjustment record in user historical preference data; using an environmental sensor to collect a noise intensity value, spatial echo parameter, and ambient light intensity data of the current environment to generate an environmental feature vector; using the user's historical volume adjustment record to calculate an average volume adjustment offset of the user under the same audio content type and in a similar environment; inputting a preset volume compensation regression model based on the environmental feature vector, and outputting a corresponding environmental volume compensation coefficient by analyzing the synergistic influence relationship between noise intensity, spatial echo, and light intensity; determining an adjusted volume parameter based on the average volume adjustment offset, the environmental volume compensation coefficient, and the initial volume parameter, and applying the adjusted volume parameter to the audio device; Sets the first weight for the average volume adjustment offset , the environmental volume compensation coefficient sets the second weight , + =1, the comprehensive adjustment coefficient is calculated based on the initial volume parameter, average volume adjustment offset, ambient volume compensation coefficient, first weight and second weight , and calculate the adjusted volume parameter according to the comprehensive adjustment coefficient and the initial volume parameter; Comprehensive adjustment parameters The calculation formula is: Adjusted volume parameter = initial volume parameter × ; The method of adjusting the speaker combination and channel configuration of the audio device based on the optimal playback mode includes: extracting the frequency response range, dynamic range, sound field width, and surround sound effect intensity from the optimal playback mode to obtain sound effect characteristic parameters, determining the sound effect requirement indicators covering multiple dimensions such as low-frequency impact, mid-frequency clarity, high-frequency delicacy, and sound field uniformity based on the sound effect characteristic parameters, collecting detailed performance parameters of each speaker in the audio device, the detailed performance parameters including frequency response curve, power output capacity, distortion and directivity characteristics, so as to obtain a speaker performance parameter set, using a similarity calculation model and a matching evaluation algorithm to compare and quantify the detailed performance parameters of each speaker with the sound effect requirement indicators one by one, evaluate the matching degree between them, set a reasonable matching threshold, eliminate speakers with a matching degree lower than the threshold, and obtain speaker screening results that meet the sound effect requirements, and use acoustic measurement equipment and acoustic analysis software to obtain room acoustic characteristic parameters. Specifically, by arranging multiple measurement points in the room, using a sound level meter and a microphone array device to collect sound signals, and analyzing the room size, shape, and sound quality. The room acoustic characteristic parameters are obtained by analyzing the shape, reverberation time, reflection path, sound absorption coefficient and sound field distribution. The reverberation time is accurately calculated by analyzing the sound attenuation process in the room using the impulse response measurement method. The reflection path is determined by simulating the sound propagation trajectory in the room using a sound ray tracing algorithm. The sound absorption coefficient is obtained by measuring the sound absorption properties of different materials using the standing wave tube method or the reverberation chamber method. Based on the speaker screening results and the room acoustic characteristic parameters, a multi-objective optimization algorithm is used to generate an optimized speaker layout plan. Specifically, with the highest sound field uniformity, the most accurate sound localization, and the minimum low-frequency standing wave interference as objective functions, while considering the physical size of the speakers, installation location restrictions, and wiring rationality constraints, a genetic algorithm or a particle swarm optimization algorithm is used to iteratively search in the multidimensional solution space, continuously adjusting the position, angle, and spatial distribution of the speakers to find the optimal speaker layout combination, and ultimately obtaining the optimized speaker layout plan. The relative position, angle, and spatial distribution of the speakers in the audio device are adjusted according to the optimized speaker layout plan, and channel configuration is performed based on the adjusted speaker layout and the optimal playback mode.

2. The method for configuring parameters of an audio device according to claim 1, wherein: The obtaining of the type and audio format information of the current input signal source includes: Detecting a type of a currently connected input signal source through an interface of the audio device, where the type of the input signal source includes at least one of Bluetooth, Wi-Fi, and a wired interface; Parsing the audio format of the input signal source, where the audio format includes at least one of MP3, WAV, FLAC, and AAC; Identify the sampling rate and bit depth of the input signal source to obtain complete audio format information.

3. The method for configuring parameters of an audio device according to claim 1, wherein: The step of identifying the audio content type and determining the optimal playback mode based on the type of the input signal source and the audio format information includes: Based on the type of the input signal source and the audio format information, querying the database for the corresponding audio content type; Calculate the suitability score of each playback mode for the current audio content type based on the audio device's hardware performance, current environmental conditions, and user historical preferences. The playback mode with the highest fitness score is selected as the optimal playback mode.

4. The method for configuring parameters of an audio device according to claim 1, wherein: The adjusting the relative positions, angles, and spatial distribution of speakers in the audio device according to the speaker layout optimization plan includes: Controlling the electric adjustment structure in the audio device to adjust the relative position and angle of the speakers according to the speaker layout optimization plan; Use angle sensors to determine whether the angles of each speaker are adjusted correctly; Verify whether the adjusted speaker spatial distribution meets the requirements of the speaker layout optimization plan.

5. The method for configuring parameters of an audio device according to claim 1, wherein: The channel configuration based on the adjusted speaker layout and the optimal playback mode includes: Determining a correspondence between each sound element and available sound channels according to the acoustic requirements of the optimal playback mode; Based on the adjusted speaker layout, the sound signals of each channel are distributed to the corresponding speakers.

6. The method for configuring parameters of an audio device according to claim 1, wherein: The collecting of the noise intensity value, spatial echo parameters and ambient light intensity data of the current environment to generate an environmental feature vector includes: Use environmental sensors to collect the current environment's noise intensity value, spatial echo parameters, and ambient light intensity data; The noise intensity value, spatial echo parameters and ambient light intensity data of the current environment are input into a preset environmental analysis model to obtain an environmental feature vector. The environmental analysis model is used in a machine learning model based on multimodal data fusion to output a normalized environmental feature vector by jointly learning the nonlinear mapping relationship between noise intensity, spatial echo and light intensity.

7. A parameter configuration device for an audio device, characterized in that: The parameter configuration device of the audio device includes: The acquisition module is used to obtain the type and audio format information of the current input signal source; an identification module, configured to identify the audio content type and determine an optimal playback mode based on the type of the input signal source and the audio format information; An adjustment module, configured to adjust a speaker combination and a channel configuration of an audio device based on the optimal playback mode; an adjustment module, configured to match the volume level according to the audio content type and perform adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis; The method of matching the volume level according to the audio content type and performing adaptive volume adjustment of the audio device in combination with user preferences and environmental analysis includes: obtaining an initial volume parameter matching the audio content type from a preset volume level library; obtaining a user's historical volume adjustment record in user historical preference data; using an environmental sensor to collect a noise intensity value, spatial echo parameter, and ambient light intensity data of the current environment to generate an environmental feature vector; using the user's historical volume adjustment record to calculate an average volume adjustment offset of the user under the same audio content type and in a similar environment; inputting a preset volume compensation regression model based on the environmental feature vector, and outputting a corresponding environmental volume compensation coefficient by analyzing the synergistic influence relationship between noise intensity, spatial echo, and light intensity; determining an adjusted volume parameter based on the average volume adjustment offset, the environmental volume compensation coefficient, and the initial volume parameter, and applying the adjusted volume parameter to the audio device; Sets the first weight for the average volume adjustment offset , the environmental volume compensation coefficient sets the second weight , + =1, the comprehensive adjustment coefficient is calculated based on the initial volume parameter, average volume adjustment offset, ambient volume compensation coefficient, first weight and second weight , and calculate the adjusted volume parameter according to the comprehensive adjustment coefficient and the initial volume parameter; Comprehensive adjustment parameters The calculation formula is: Adjusted volume parameter = initial volume parameter × ; The adjustment module is specifically used to: extract the frequency response range, dynamic range, sound field width, and surround sound effect intensity from the optimal playback mode to obtain sound effect characteristic parameters, determine the sound effect requirement indicators covering multiple dimensions such as low-frequency impact, mid-frequency clarity, high-frequency delicacy, and sound field uniformity based on the sound effect characteristic parameters, collect detailed performance parameters of each speaker in the audio device, the detailed performance parameters include frequency response curve, power output capacity, distortion and directivity characteristics, so as to obtain a speaker performance parameter set, use a similarity calculation model and a matching evaluation algorithm to compare and quantify the detailed performance parameters of each speaker with the sound effect requirement indicators one by one, evaluate the matching degree between them, set a reasonable matching threshold, and eliminate speakers with a matching degree lower than the threshold to obtain speaker screening results that meet the sound effect requirements, and use acoustic measurement equipment and acoustic analysis software to obtain room acoustic characteristic parameters. Specifically, by arranging multiple measurement points in the room, using a sound level meter and a microphone array device to collect sound signals, and analyzing the room size, shape, reverberation time, reflection path, etc. , sound absorption coefficient and sound field distribution to obtain the room acoustic characteristic parameters. For the reverberation time, the impulse response measurement method is used to accurately calculate it by analyzing the attenuation process of sound in the room. The reflection path is determined by simulating the propagation trajectory of sound in the room through the sound ray tracing algorithm. The sound absorption coefficient is obtained by measuring the sound absorption performance of different materials using the standing wave tube method or the reverberation chamber method. Based on the speaker screening results and the room acoustic characteristic parameters, a multi-objective optimization algorithm is used to generate an optimized speaker layout plan. Specifically, with the highest sound field uniformity, the most accurate sound effect positioning, and the minimum low-frequency standing wave interference as objective functions, while considering the physical size of the speaker, installation location restrictions, and wiring rationality constraints, a genetic algorithm or a particle swarm optimization algorithm is used to iteratively search in the multidimensional solution space, continuously adjusting the position, angle, and spatial distribution of the speakers to find the optimal speaker layout combination, and finally obtaining the speaker layout optimization plan. The relative position, angle, and spatial distribution of the speakers in the audio device are adjusted according to the speaker layout optimization plan, and the channel configuration is performed based on the adjusted speaker layout and the optimal playback mode.

8. An electronic device, characterized in that: The electronic device comprises: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the electronic device to execute the parameter configuration method for an audio device according to any one of claims 1 to 6.

9. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by a processor, the parameter configuration method for an audio device according to any one of claims 1 to 6 is implemented.

Images