Audio signal processing method and device, equipment and medium

Abstract

The invention provides an audio signal processing method and device, equipment and a medium, and the method comprises the steps: determining a target acoustic transmission feature between a digital signal processor and audio collection equipment based on a first audio signal outputted by the digital signal processor and a second audio signal collected by the audio collection equipment, after the first audio signal is output to the audio playing device through the digital signal processor, the audio playing device plays the first audio signal and acquires the first audio signal through the audio acquisition device to obtain a second audio signal, and then target tuning information of the digital signal processor is determined based on the target acoustic transmission characteristics, so that the digital signal processor performs tuning on the second audio signal based on the target tuning information. And tuning the received audio signal. Therefore, the audio quality can be improved.

Description

Technical Field

[0001] This disclosure relates to audio processing technology, and in particular to an audio signal processing method, apparatus, device, and medium. Background Technology

[0002] In related technologies, audio playback systems such as headphones and speakers often integrate multiple components. However, these components frequently experience changes in their physical characteristics due to environmental changes, aging, and other issues, resulting in poor audio quality. For example, in a vehicle cabin environment, there are various types of noise both inside and outside the vehicle, creating a complex acoustic environment. The signal received by the microphone not only includes the speaker's response but also incorporates interference from cabin multipath reflections and background noise. Furthermore, components such as the diaphragm, voice coil, and cavity of a vehicle speaker may experience changes in their physical characteristics due to long-term use, temperature and humidity changes, or oxidation and aging, leading to changes in frequency response and increased distortion. Summary of the Invention

[0003] To address the aforementioned technical problems, this disclosure provides an audio signal processing method, apparatus, device, and medium.

[0004] A first aspect of this disclosure provides an audio signal processing method, comprising:

[0005] Based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device, the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device are determined. The first audio signal is output to the audio playback device by the digital signal processor, played by the audio playback device, and the second audio signal is acquired by the audio acquisition device.

[0006] Based on the target acoustic transmission characteristics, the target tuning information of the digital signal processor is determined, so that the digital signal processor can perform tuning processing on the received audio signal based on the target tuning information.

[0007] A second aspect of this disclosure provides an audio signal processing apparatus, comprising:

[0008] The first determining unit is configured to determine the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device. The first audio signal is output to the audio playback device by the digital signal processor, played by the audio playback device, and the second audio signal is acquired by the audio acquisition device.

[0009] The second determining unit is configured to determine the target tuning information of the digital signal processor based on the target acoustic transmission characteristics, so that the digital signal processor can perform tuning processing on the received audio signal based on the target tuning information.

[0010] A third aspect of this disclosure provides an electronic device comprising:

[0011] Memory, used to store computer programs;

[0012] A processor is configured to execute a computer program stored in a memory, wherein, when the computer program is executed, it implements the method of any embodiment of the audio signal processing method of the first aspect of this disclosure.

[0013] A fourth aspect of this disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method of any embodiment of the audio signal processing method of the first aspect described above.

[0014] A fifth aspect of this disclosure provides a computer program including computer-readable code, which, when executed by a processor, implements the method of any embodiment of the audio signal processing method of the first aspect described above.

[0015] Based on the embodiments of this disclosure, the target acoustic transmission characteristics between the digital signal processor (DSP) and the audio acquisition device can be determined based on a first audio signal output by the DSP and a second audio signal acquired by the audio acquisition device. The first audio signal is output by the DSP to the audio playback device, played by the playback device, and the second audio signal is acquired by the audio acquisition device. Then, based on the target acoustic transmission characteristics, target tuning information for the DSP is determined, allowing the DSP to perform tuning processing on the received audio signal based on this information. Therefore, by determining the acoustic transmission characteristics between the DSP and the audio acquisition device using the first audio signal output by the DSP and the second audio signal acquired by the audio acquisition device, the influence of the audio playback device and the environment on the audio signal can be more accurately quantified. Thus, the target tuning information determined based on these acoustic transmission characteristics can more effectively compensate for deviations in the audio signal during transmission and playback. Consequently, after the DSP performs tuning processing on the received audio signal based on the target tuning information, audio quality can be improved, helping to solve problems such as frequency response changes and increased distortion caused by noise interference and alterations in the physical characteristics of vehicle speaker components. Attached Figure Description

[0016] Figure 1 This is the scenario diagram to which this disclosure applies.

[0017] Figure 2 This is a schematic flowchart of an audio signal processing method provided in an exemplary embodiment of this disclosure.

[0018] Figure 3This is a schematic diagram illustrating the connection relationship between a digital signal processor, an audio playback device, and an audio acquisition device in an audio signal processing method provided by an exemplary embodiment of this disclosure.

[0019] Figure 4 This is a schematic flowchart illustrating the process of determining target acoustic transmission characteristics between a digital signal processor and an audio acquisition device, provided by an exemplary embodiment of this disclosure.

[0020] Figure 5 This is a schematic flowchart illustrating the process of determining target tuning information of a digital signal processor in an audio signal processing method provided by an exemplary embodiment of this disclosure.

[0021] Figure 6 This is a schematic flowchart illustrating the process of determining the center frequency, high-frequency cutoff frequency, and low-frequency cutoff frequency of a digital filter running on a digital signal processor in an audio signal processing method provided by an exemplary embodiment of this disclosure.

[0022] Figure 7 This is a schematic diagram of the frequency response curve in an audio signal processing method provided by an exemplary embodiment of the present disclosure.

[0023] Figure 8 This is a schematic flowchart illustrating the process of determining target tuning information of a digital signal processor in an audio signal processing method provided in another exemplary embodiment of this disclosure.

[0024] Figure 9 This is a schematic flowchart illustrating the process of determining target tuning information of a digital signal processor in an audio signal processing method provided in another exemplary embodiment of the present disclosure.

[0025] Figure 10 This is a schematic flowchart illustrating the process of determining target tuning information of a digital signal processor in an audio signal processing method provided in another exemplary embodiment of this disclosure.

[0026] Figure 11 This is a schematic diagram of the structure of an audio signal processing apparatus provided in an exemplary embodiment of the present disclosure.

[0027] Figure 12 This is a schematic diagram of the structure of an audio signal processing apparatus provided in yet another exemplary embodiment of this disclosure.

[0028] Figure 13 This is a schematic diagram of the structure of an audio signal processing system provided in an exemplary embodiment of this disclosure.

[0029] Figure 14 This is a structural diagram of an electronic device provided in an exemplary embodiment of this disclosure. Detailed Implementation

[0030] To explain this disclosure, exemplary embodiments of the disclosure will now be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the disclosure, and not all of them. It should be understood that the disclosure is not limited to exemplary embodiments.

[0031] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of this disclosure.

[0032] Application Overview

[0033] In developing this disclosure, the inventors discovered that audio playback systems such as headphones and speakers often integrate multiple components. However, these components frequently experience changes in their physical characteristics due to environmental changes, aging, and other issues, resulting in poor audio quality. For example, in a vehicle cabin environment, there are various types of noise both inside and outside the vehicle, creating a complex acoustic environment. The signal received by the microphone not only includes the speaker's response but also incorporates interference from cabin multipath reflections and background noise. Furthermore, components such as the diaphragm, voice coil, and cavity of a vehicle speaker may experience changes in their physical characteristics due to long-term use, temperature and humidity variations, or oxidation and aging, leading to changes in frequency response and increased distortion, thus resulting in poor audio quality.

[0034] Exemplary System

[0035] When processing audio signals, the acoustic transmission characteristics between the digital signal processor (DSP) and the audio acquisition device can be determined by using the first audio signal output by the DSP and the second audio signal acquired by the audio acquisition device. This allows for a more accurate quantification of the impact of the audio playback device and the environment on the audio signal. In this way, the target tuning information determined based on these acoustic transmission characteristics can more effectively compensate for deviations in the audio signal during transmission and playback. As a result, after the DSP tunes the received audio signal based on the target tuning information, the audio quality can be improved.

[0036] The audio signal processing in this embodiment can be implemented via any device with audio signal processing capabilities, such as headphones, speakers, vehicles, or other devices equipped with audio signal processing devices. The aforementioned audio signal processing device may include a digital signal processor, an audio playback device, and an audio acquisition device; alternatively, the aforementioned audio signal processing device may be communicatively connected to the digital signal processor, the audio playback device, and the audio acquisition device.

[0037] Digital signal processors (DSPs) can be used to process digital audio signals. For example, a DSP can perform audio processing algorithms such as filtering, equalization, and mixing. Furthermore, a DSP can be an audio signal processing chip, such as a System-on-a-Chip (SoC) chip or a Digital Signal Processor (DSP) chip.

[0038] Audio playback devices are used to convert audio signals output by a digital signal processor into sound signals. For example, an audio playback device could be a speaker, headphones, or a loudspeaker.

[0039] Audio acquisition devices can be used to collect sound signals from the surrounding environment. For example, an audio acquisition device could be a microphone, a pickup, etc.

[0040] Please refer to the following. Figure 1 The physical environment constituted by the vehicle is used as the sound transmission environment for converting audio signals into sound signals and transmitting them, in order to exemplify and explain the process of the audio signal processing method. It is understood that the vehicle environment is only used as an example of a specific environment for sound transmission and is not intended to limit the specific scenario of this disclosure.

[0041] In this example, the vehicle may be equipped with a digital signal processor, an audio playback device, and an audio acquisition device; the entire vehicle can be viewed as an audio signal processing system. The electronic devices equipped on the vehicle can act as the actuators of the signal processing, such as intelligent driving chips and intelligent cockpit chips. For example, such as... Figure 1 The vehicle 101 is equipped with a digital signal processor, audio playback equipment and audio acquisition equipment.

[0042] When preset tuning trigger conditions are met, the electronic equipment equipped on the vehicle can perform the audio signal processing described in this disclosure. The tuning trigger conditions may include at least one of the following: the current time is a preset tuning time, and a tuning trigger operation is detected.

[0043] During audio signal processing, the target acoustic transmission characteristics 104 between the digital signal processor and the audio acquisition device can be determined based on the first audio signal 102 output by the digital signal processor and the second audio signal 103 acquired by the audio acquisition device. Specifically, the first audio signal is output to the audio playback device after being processed by the digital signal processor, and then played by the audio playback device and acquired by the audio acquisition device to obtain the second audio signal 103.

[0044] Subsequently, the target tuning information 105 of the digital signal processor can be determined based on the target acoustic transmission characteristics 104, so that the digital signal processor can perform tuning processing on the received audio signal based on the target tuning information 105.

[0045] Here, the target acoustic transmission characteristics reflect the environmental influences on the audio signal during its transmission from playback to acquisition, including factors such as the vehicle's interior space structure, material reflections, and noise interference. Therefore, compensation parameters can be calculated based on the target acoustic transmission characteristics to compensate for subsequent audio signals, thereby improving audio quality.

[0046] The audio signal processing method of this disclosure can be applied to in-vehicle scenarios such as smart cockpits, as well as to any other audio signal processing scenarios, such as home audio systems, conference audio equipment, and mobile terminal players.

[0047] Exemplary methods

[0048] Figure 2 This is a schematic flowchart of an audio signal processing method provided in an exemplary embodiment of this disclosure. This embodiment can be applied to electronic devices (e.g., in-vehicle electronic devices, headphones, speakers, etc.), such as... Figure 2 As shown, it includes the following steps:

[0049] Step 21: Based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device, determine the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device. After the first audio signal is output to the audio playback device by the digital signal processor, it is played by the audio playback device and acquired by the audio acquisition device to obtain the second audio signal.

[0050] A digital signal processor (DSP) can be used for digital signal processing. As an example, a DSP can be a dedicated chip or integrated circuit used to perform encoding, decoding, filtering, or enhancement processing of audio signals. DSPs can be, but are not limited to, installed in devices such as in-vehicle audio systems, speakers, and headphones. A DSP can be an audio signal processing chip, such as a System-on-a-Chip (SoC) chip or a DSP chip.

[0051] The first audio signal can be the raw audio signal (such as a digital audio electrical signal, digital audio optical signal, etc.) output after processing by a digital signal processor. It can serve as a reference signal for calculating the transmission characteristics (i.e., the target acoustic transmission characteristics described later), reflecting the ideal output state of the digital signal processor. As an example, the first audio signal can be audio from a video, broadcast, music, etc.

[0052] In this embodiment, an audio signal can be a signal that carries sound characteristics and is used for processing by electronic devices (e.g., acquisition, transmission, calculation, output, etc.). For example, it can carry sound characteristics such as frequency, amplitude, and phase. A sound signal refers to a wave signal generated by a sound source (e.g., audio playback device, person, etc.), transmitted through an audio signal transmission link, and propagated in physical space. It can carry all the characteristics of the influence of the environment (e.g., diaphragm aging, voice coil temperature drift, changes in cavity sealing of audio playback devices such as speakers) on the sound. The difference between an audio signal and a sound signal is that the former exists inside the electronic device and can be directly read through a data interface, and is usually used for processing by the electronic device; the latter is the sound generated after the audio signal is transmitted through lines, devices, and links, and propagated in space, and affected by reverberation, noise, etc., and is closer to the sound heard by the listener.

[0053] An audio acquisition device can be used to acquire sound signals. As an example, an audio acquisition device may include one or more microphones, pickups, etc. In this embodiment, the audio acquisition device can be used to acquire sound signals played by an audio playback device, which may include ambient noise, thereby obtaining a second audio signal.

[0054] An audio playback device can be used to convert audio signals into sound signals. In this embodiment, it can play audio signals processed by a digital signal processor. As an example, the audio playback device may include a multi-channel speaker array, a door-mounted speaker, etc.

[0055] The second audio signal can be an audio signal acquired by an audio acquisition device (such as an analog audio signal, a digital audio signal, etc.). It can reflect the actual audio output effect, such as the sound heard by the listener. In some cases, the second audio signal may include the sound signal played by the audio playback device, interference signals such as cabin ambient noise, etc.

[0056] The target acoustic transfer characteristic (also known as the transfer function) characterizes the transmission pattern of sound signals between a digital signal processor and an audio acquisition device. In some cases, the target acoustic transfer characteristic can represent the transmission response characteristics of the transmission link from the first audio signal to the second audio signal under interference from other factors in the current acoustic environment. In other cases, the target acoustic transfer characteristic can quantify the state of the audio playback device (such as its aging level) and the influence of the cabin environment on the audio signal.

[0057] In some alternative implementations, the cross-spectral ratio method can be used to determine the target acoustic transmission characteristics by calculating the self-power spectral density of the first audio signal and the cross-power spectral density of the first and second audio signals; or, the least squares method can be used to fit the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device based on the time-domain waveform data of the first and second audio signals.

[0058] In some alternative implementations, noise and interference signals can be removed from the first and second audio signals first, and then the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device can be determined by the first and second audio signals after removing noise and interference. This provides a cleaner signal for determining the target acoustic transmission characteristics while ensuring computational stability.

[0059] Step 22: Based on the target acoustic transmission characteristics, determine the target tuning information of the digital signal processor, so that the digital signal processor can perform tuning processing on the received audio signal based on the target tuning information.

[0060] The target tuning information may include one or more parameters used to adjust the audio signal. For example, the target tuning information may include at least one of the following: center frequency, quality factor, numerator coefficient, denominator coefficient, etc.

[0061] In some alternative implementations, the target tuning information of the digital signal processor can be determined by comparing the deviation between the target acoustic transmission characteristics and the preset acoustic transmission characteristics using an error compensation algorithm. Alternatively, an objective function for optimizing the tuning information can be constructed based on the target acoustic transmission characteristics, and then the target tuning information can be determined based on the objective function. The objective function can aim to minimize the error between the actual acoustic response (e.g., the second audio signal) and the ideal target response (e.g., the first audio signal).

[0062] In some alternative implementations, the connection between the digital signal processor, the audio playback device, and the audio acquisition device can be as follows: Figure 3 As shown. In Figure 3In this system, the audio playback device 302 is connected to both the digital signal processor 301 and the audio acquisition device 303. The digital signal processor 301 is also connected to the audio acquisition device 303. Thus, after the first audio signal is output from the digital signal processor 301 to the audio playback device 302, it is played by the audio playback device 302 and acquired by the audio acquisition device 303, thereby obtaining the second audio signal. Specifically, the digital signal processor 301 can perform digital signal processing on the input audio signal, including filtering, equalization (EQ), dynamic compression, reverberation, and other operations. It is the core signal conditioning unit of the system, providing optimization processing for the final played sound. The audio playback device 302 (e.g., including a speaker array) can play the audio signal processed by the digital signal processor 301. It is the output of the system, actually producing audible sound. The physical state of components (e.g., speakers) in the audio playback device 302 (e.g., aging, cavity deformation) directly affects the playback effect; therefore, the method of this disclosure is required for compensation through closed-loop feedback. The audio acquisition device 303 may include, for example, a microphone array, which can be used to acquire the played sound in real time and record ambient noise and acoustic characteristics, thereby providing feedback signals for closed-loop tuning. Therefore, based on the actual sound acquired by the audio acquisition device 303 (i.e., the second audio signal) and the signal output by the digital signal processor 301 (i.e., the first audio signal), the target acoustic transfer characteristics (i.e., transfer function) of the acoustic channel within the vehicle electronic device can be dynamically calculated. The impact of factors such as the audio playback device 302 and the in-vehicle environment on the sound is quantified through the target acoustic transfer characteristics, providing a mathematical basis for parameter optimization (i.e., determining the target tuning information).

[0063] Based on this embodiment, the target acoustic transmission characteristics between the digital signal processor (DSP) and the audio acquisition device can be determined based on the first audio signal output by the DSP and the second audio signal acquired by the audio acquisition device. The first audio signal is output by the DSP to the audio playback device, played by the playback device, and the second audio signal is acquired by the audio acquisition device. Then, based on the target acoustic transmission characteristics, the target tuning information of the DSP is determined, allowing the DSP to perform tuning processing on the received audio signal based on this information. Therefore, by determining the acoustic transmission characteristics between the DSP and the audio acquisition device using the first audio signal output by the DSP and the second audio signal acquired by the audio acquisition device, the influence of the audio playback device and the environment on the audio signal can be more accurately quantified. Thus, the target tuning information determined based on these acoustic transmission characteristics can more effectively compensate for deviations in the audio signal during transmission and playback, thereby improving audio quality after the DSP performs tuning processing on the received audio signal based on the target tuning information.

[0064] In some alternative embodiments, such as Figure 4 As shown above, in the above Figure 2 Based on the illustrated embodiment, step 21 may include the following steps:

[0065] Step 211: Determine the auto-power spectral density of the first audio signal output by the digital signal processor.

[0066] The power spectral density (PSD) can be a function of the power distribution of the first audio signal itself with respect to frequency. It can reflect the frequency and power characteristics of the first audio signal itself.

[0067] In some alternative implementations, a Fast Fourier Transform (FFT) can be performed on the first audio signal X(t) to obtain the frequency domain result X(f), the square of the amplitude of X(f) can be calculated, and then the mean can be calculated to obtain the power spectral density S. xx (f). For example, the auto-power spectral density of the first audio signal output by the digital signal processor can be determined using the following formula (1):

[0068] S xx (f)=E[|X(f)| 2 ]

[0069] Formula (1)

[0070] In formula (1), E[|X(f)| 2 ] represents |X(f)| 2 The mean of the first audio signal X(t) is given by X(f), which represents the result of the Fast Fourier Transform of the first audio signal X(t). xx (f) represents the self-power spectral density.

[0071] Step 212: Determine the cross-power spectral density between the first audio signal and the second audio signal.

[0072] The cross-power spectral density (CPSD) can be a function of the power distribution between the first and second audio signals as a function of frequency. It can reflect the correlation and phase relationship between the two signals.

[0073] In some alternative implementations, FFT can be performed on the first audio signal X(t) and the second audio signal Y(t) to obtain X(f) and Y(f) respectively. The product of the complex conjugate of X(f) and Y(f) can be calculated, and then the mean can be calculated to obtain the cross-power spectral density S. xy (f). For example, the cross-power spectral density between the first audio signal and the second audio signal can be determined using the following formula (2):

[0074] S xy (f)=E[X * (f)·Y(f)]

[0075] Formula (2)

[0076] In formula (2), S xy (f) represents the cross-power spectral density, E[X] * [(f)·Y(f)] represents X * The mean of (f)·Y(f), X * (f) denotes the complex conjugate of X(f), X(f) denotes the result of the Fast Fourier Transform of the first audio signal X(t), Y(f) denotes the result of the Fast Fourier Transform of the second audio signal Y(t), and · denotes the dot product operation.

[0077] Step 213: Based on the self-power spectral density and cross-power spectral density, determine the target acoustic transfer characteristics between the digital signal processor and the audio acquisition device.

[0078] In some alternative implementations, the ratio of cross-power spectral density to self-power spectral density can be used as the target acoustic transfer characteristic. Alternatively, the cross-power spectral density and self-power spectral density can be smoothed first, and then the ratio of the smoothed cross-power spectral density to self-power spectral density can be calculated to obtain the target acoustic transfer characteristic.

[0079] As an example, the following formula (3) can be used to determine the target acoustic transfer characteristics between the digital signal processor and the audio acquisition device based on the self-power spectral density and the cross-power spectral density:

[0080]

[0081] In formula (3), H measured (f) represents the acoustic transmission characteristics of the target, S xy (f) represents the cross-power spectral density, S xx (f) represents the self-power spectral density.

[0082] Based on the embodiments of this disclosure, the auto-power spectral density of the first audio signal can reflect the frequency power distribution of the first audio signal itself, eliminating interference from signal fluctuations. The cross-power spectral density between the first audio signal and the second audio signal can reflect the correlation and phase relationship between the first audio signal and the second audio signal in the frequency domain, reflecting the signal correlation characteristics in the acoustic transmission process. Therefore, based on the auto-power spectral density and the cross-power spectral density, the target acoustic transmission characteristics can be determined by the cross-spectral ratio method, which can ensure that the tuning processing of the digital signal processor can more effectively compensate for the distortion in the acoustic transmission process, thereby improving the audio quality.

[0083] In some alternative embodiments, in the above... Figure 2 Based on the embodiment shown, step 21 may include the following steps: in response to the meeting of the tuning trigger condition and the vehicle being in a preset state, determining the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device.

[0084] The tuning trigger condition includes at least one of the following: the current time is a preset tuning time, and a tuning trigger operation is detected. The tuning trigger condition is the basis for triggering the audio signal processing in the embodiments of this disclosure.

[0085] The preset state includes at least one of the following: the vehicle is stationary, the vehicle is in neutral, the doors are closed, the vehicle seats are in preset positions, and the audio acquisition equipment in the vehicle is not obstructed.

[0086] The tuning trigger can be a user-initiated action to start tuning. As an example, the tuning trigger could be the voice command "Start automatic tuning", or it could be touching the "Tuning" button.

[0087] Based on this embodiment, the target acoustic transmission characteristics are determined only when the tuning triggering conditions are met and the vehicle is in a preset state. This ensures that the tuning operation is initiated at the appropriate time, avoiding frequent tuning that consumes computing resources or is initiated when tuning is not needed. It also enables seamless and automated tuning throughout the entire life cycle of the vehicle, suppressing distortion introduced by diaphragm aging and cavity deformation of audio playback devices such as speakers in in-vehicle electronic devices, thereby improving audio quality.

[0088] Optionally, the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device can be determined according to a preset period based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device.

[0089] In some alternative embodiments, such as Figure 5 As shown above, in the above Figure 2 Based on the illustrated embodiment, step 22 may include the following steps:

[0090] Step 221: Determine the frequency response deviation information of the target acoustic transmission characteristics relative to the preset acoustic transmission characteristics.

[0091] The preset acoustic transmission characteristics can be preset ideal acoustic transmission characteristics. These can serve as a reference standard for judging whether the current acoustic transmission is distorted. For example, the preset acoustic transmission characteristics can be the acoustic transmission characteristics of electronic devices (such as automotive electronic devices, headphones, speakers, etc.) at the time of manufacture.

[0092] Frequency response deviation information represents the difference between the frequency response of the target acoustic transmission characteristic and the frequency response of the preset acoustic transmission characteristic. It can be used to determine the frequency band and degree of frequency response distortion.

[0093] In some alternative implementations, the frequency response curves of the target acoustic transmission feature and the preset acoustic transmission feature can be determined, and the amplitude difference between the two frequency response curves at each frequency point can be calculated to obtain the frequency response deviation information of the target acoustic transmission feature relative to the preset acoustic transmission feature. Alternatively, spectral subtraction can be used to subtract the frequency domain data of the preset acoustic transmission feature from the frequency domain data of the target acoustic transmission feature to obtain the frequency response deviation information.

[0094] In some alternative implementations, the following formula (4) can be used to determine the frequency response deviation information of the target acoustic transmission characteristics relative to the preset acoustic transmission characteristics:

[0095] E(f)=H target (f)-H measured (f)

[0096] Formula (4)

[0097] In formula (4), E(f) represents the frequency response deviation information, and H target (f) represents the preset acoustic transmission characteristics, H measured (f) represents the acoustic transmission characteristics of the target.

[0098] Step 222: Based on the frequency response deviation information, determine the center frequency, high-frequency cutoff frequency, and low-frequency cutoff frequency of the digital filter running on the digital signal processor.

[0099] The digital filter can be a signal processing module running in a digital signal processor, which can adjust specific frequency components through parameter configuration. For example, a digital filter can include a bandpass IIR filter or a peak-mode EQ filter.

[0100] The center frequency can be the peak frequency corresponding to the most distorted frequency band in the frequency response deviation curve. It can be used to determine the core frequency band that needs correction.

[0101] The high-frequency cutoff frequency can be the upper limit of the frequency band that needs to be corrected in the frequency response deviation curve. For example, the high-frequency cutoff frequency can be the high-frequency end frequency corresponding to the peak amplitude of the frequency response deviation curve dropping to a preset gain (e.g., -3dB).

[0102] The low-frequency cutoff frequency can be the lower limit of the frequency band that needs to be corrected in the frequency response deviation curve. As an example, the low-frequency cutoff frequency can be the low-frequency end frequency at which the peak amplitude drops to a preset gain (e.g., -3dB).

[0103] In some alternative implementations, peak detection can be performed on the frequency response deviation curve to determine the frequency corresponding to the maximum amplitude as the center frequency. Then, frequencies with amplitudes equal to a preset gain (e.g., -3dB, or other gain values) can be found along the frequency response deviation curve in both high and low frequency directions, and these are determined as the high-frequency cutoff frequency and low-frequency cutoff frequency, respectively. Alternatively, a curve fitting algorithm can be used to fit the frequency response deviation information, extract the peak position of the fitted curve as the center frequency, and then determine the high-frequency and low-frequency cutoff frequencies corresponding to the preset gain through threshold judgment.

[0104] Step 223: Determine the bandwidth of the digital filter based on the high-frequency cutoff frequency and the low-frequency cutoff frequency.

[0105] Among them, bandwidth can be used to define the width of the frequency band that needs to be corrected, which can reflect the range of influence of frequency response distortion.

[0106] In some alternative implementations, the difference between the high-frequency cutoff frequency and the low-frequency cutoff frequency can be used as the bandwidth of the digital filter. Alternatively, the high-frequency and low-frequency cutoff frequencies can be smoothed, and the difference between them can be calculated to obtain the bandwidth of the digital filter.

[0107] Step 224: Determine the target tuning information for the digital signal processor based on the center frequency and bandwidth.

[0108] In some alternative implementations, the center frequency and bandwidth can be determined as the target tuning information for the digital signal processor. Alternatively, the target tuning information for the digital signal processor can be obtained by optimizing the center frequency and bandwidth.

[0109] Based on this embodiment, the frequency response deviation information of the target acoustic transmission characteristics relative to the preset acoustic transmission characteristics can more accurately reflect the frequency band and degree of frequency response distortion. Then, based on this frequency response deviation information, the center frequency, high-frequency cutoff frequency, and low-frequency cutoff frequency of the digital filter running on the digital signal processor are determined, which can achieve more accurate positioning of the distortion frequency band. Subsequently, based on the high-frequency cutoff frequency and low-frequency cutoff frequency, the bandwidth of the digital filter is determined, which can clarify the frequency band range that needs to be tuned. Finally, based on the center frequency and bandwidth, the target tuning information of the digital signal processor is determined, which can make the target tuning information more accurately match the actual situation of frequency response distortion, making the tuning processing of the digital signal processor more targeted, thereby more accurately compensating for the frequency response deviation caused by the aging of audio playback equipment and changes in the audio playback environment, thereby further improving audio quality.

[0110] In some alternative embodiments, such as Figure 6 As shown above, in the above Figure 5 Based on the illustrated embodiment, step 222 may include the following steps:

[0111] Step 2221: Based on the peak of the frequency response curve represented by the frequency response deviation information, determine the center frequency of the digital filter. The frequency response curve characterizes the correspondence between the frequency and gain of the audio signal to be processed by the digital filter.

[0112] The frequency response curve characterizes the relationship between the frequency and gain of an audio signal. It reflects the gain characteristics of the audio signal at different frequency points.

[0113] The preset gain can be a reference gain value used to determine the bandwidth of the digital filter. As an example, the preset gain could be -3dB, -4dB, etc.

[0114] In some alternative implementations, a peak detection algorithm can be used to scan the frequency response curve represented by the frequency response deviation information, thereby identifying the position of the peak with the largest amplitude in the frequency response curve, and determining the frequency corresponding to the peak position as the center frequency of the digital filter. Alternatively, Fourier transform analysis can be performed on the frequency response curve to extract the frequency corresponding to the peak and obtain the center frequency.

[0115] Step 2222: Determine the high-frequency cutoff frequency and low-frequency cutoff frequency of the digital filter based on the frequencies in the frequency response curve that correspond to the preset gain.

[0116] In some alternative implementations, the frequency response curve can be iterated from its peak towards higher frequencies. When the amplitude drops to a preset gain, the corresponding frequency is identified as the high-frequency cutoff frequency. Similarly, it can be iterated towards lower frequencies, and when the amplitude drops to a preset gain, the corresponding frequency is identified as the low-frequency cutoff frequency. Alternatively, a threshold comparison method can be used to filter all frequency points in the frequency response curve whose amplitude equals the preset gain. The frequency points located to the right of the peak are identified as the high-frequency cutoff frequencies, and those located to the left of the peak are identified as the low-frequency cutoff frequencies.

[0117] As an example, see Figure 7 , Figure 7 This is a schematic diagram of the frequency response curve in an audio signal processing method provided by an exemplary embodiment of this disclosure. Figure 7 In the frequency response curve, the frequency f corresponding to the peak value can be represented by the frequency response deviation information. c The center frequency is determined, and the frequency f corresponding to a 3dB decrease in amplitude relative to the peak value at the rising and falling edges of the frequency response curve is identified. low and f high These are respectively determined as the low-frequency cutoff frequency and the high-frequency cutoff frequency.

[0118] Based on the embodiments of this disclosure, the center frequency can be determined based on the peak of the frequency response curve represented by the frequency response deviation information. Since this peak corresponds to the frequency band with the most severe frequency response distortion, it can ensure that the center frequency can be more accurately located in the core area that needs to be focused on correction. At the same time, the frequency response curve characterizes the correspondence between the frequency and gain of the audio signal to be processed by the digital filter. Therefore, by determining the high-frequency cutoff frequency and low-frequency cutoff frequency based on the frequencies in the frequency response curve that correspond to the preset gain, the influence range of the distortion frequency band can be more accurately defined. In this way, by more accurately determining the center frequency and clearly defining the boundary of the correction frequency band, the design of subsequent digital filters can more comprehensively cover the distortion frequency band, avoiding the correction range being too large or too small, thereby improving the accuracy and targeting of the tuning processing, effectively compensating for frequency response distortion, and further improving audio quality.

[0119] In some alternative embodiments, such as Figure 8 As shown above, in the above Figure 5 Based on the illustrated embodiment, step 22 may include the following steps:

[0120] Step 225: Determine the quality factor of the digital filter based on the center frequency and bandwidth.

[0121] Among them, the quality factor is one of the parameters of a digital filter. It can reflect the frequency selection characteristics of the digital filter. The larger the Q value, the sharper the frequency selection of the digital filter in the frequency band near the center frequency, and the more accurate the correction.

[0122] In some alternative implementations, the center frequency and bandwidth values ​​can be substituted into a preset formula to obtain the quality factor of the digital filter. Here, Q represents the quality factor, and f... c BW represents the center frequency, and BW represents the bandwidth. Alternatively, the quality factor can be obtained by using a preset Q-value mapping table based on the numerical range of the center frequency and bandwidth.

[0123] As an example, the above preset formula could be the following formula (5):

[0124]

[0125] In formula (5), Q represents the quality factor, f c BW represents the center frequency, and BW represents the bandwidth.

[0126] Step 226: Determine the target tuning information for the digital signal processor based on the quality factor.

[0127] In some alternative implementations, the quality factor can be input into a preset digital filter parameter optimization model, combined with the center frequency and bandwidth, to output the target tuning information for the digital signal processor. Alternatively, the target tuning information for the digital signal processor can be obtained by querying a preset tuning parameter table for the digital signal processor based on the quality factor.

[0128] Based on the embodiments of this disclosure, since the quality factor can reflect the sharpness of the frequency selection of the digital filter in the frequency band near the center frequency, determining the target tuning information of the digital signal processor based on the quality factor can make the target tuning information not only include the frequency band range, but also reflect the frequency selection characteristics (such as the fineness of frequency selection and the strength of correction). In this way, the frequency selection characteristics of the digital filter can be matched with the characteristics of the actual distorted frequency band, avoiding unnecessary influence on the undistorted frequency band, while ensuring sufficient correction of the distorted frequency band, thereby improving the accuracy of audio processing.

[0129] In some alternative embodiments, such as Figure 9 As shown above, in the above Figure 2 Based on the illustrated embodiment, step 22 may include the following steps:

[0130] Step 227: Determine the gain deviation information of the target acoustic transmission characteristics relative to the preset acoustic transmission characteristics.

[0131] Gain deviation information represents the difference between the gain of the target acoustic transmission characteristic at each frequency point and the gain of the corresponding frequency point of the preset acoustic transmission characteristic. It can reflect the degree of amplitude distortion of the audio signal in each frequency band.

[0132] In some alternative implementations, the gain value of the target acoustic transmission feature at each frequency point can be calculated, and the gain value of the preset acoustic transmission feature at the corresponding frequency point can be subtracted to obtain the gain deviation at each frequency point. The gain deviations at each frequency point are then summarized to form gain deviation information. Alternatively, the gain value of the target acoustic transmission feature at each frequency point can be calculated, and the gain value of the preset acoustic transmission feature at the corresponding frequency point can be subtracted. Gain value optimization can then be performed to obtain the gain deviation at each frequency point. The gain deviations at each frequency point are then summarized to form gain deviation information.

[0133] In some alternative implementations, the following formula (6) can be used to determine the gain deviation information of the target acoustic transmission characteristics relative to the preset acoustic transmission characteristics:

[0134]

[0135] In formula (6), G represents the gain bias information, and H... target (f) represents the preset acoustic transmission characteristics, H measured (f) represents the acoustic transmission characteristics of the target.

[0136] Step 228: Based on the gain deviation information, determine the target tuning information for the digital signal processor.

[0137] In some alternative implementations, the gain deviation information can be used to determine the target tuning information for the digital signal processor. Alternatively, the gain deviation information can be adjusted to determine the target tuning information for the digital signal processor.

[0138] Based on this embodiment, since the gain deviation information of the target acoustic transmission characteristics relative to the preset acoustic transmission characteristics can reflect the difference between the amplitude of the audio signal in each frequency band and the ideal state, including amplitude distortion caused by factors such as diaphragm aging and voice coil temperature drift of the audio playback device (e.g., speaker), determining the target tuning information of the digital signal processor based on this gain deviation information allows the digital signal processor to adjust the gain of each frequency band in a targeted manner to compensate for amplitude distortion. Therefore, the tuning processing of the digital signal processor can not only correct frequency response deviations but also compensate for gain deviations, ensuring that the amplitude characteristics of the audio signal meet the preset standard (represented by the preset acoustic transmission characteristics), thereby further improving audio quality.

[0139] In some alternative embodiments, such as Figure 10 As shown above, in the above Figure 9 Based on the illustrated embodiment, step 228 may include the following steps:

[0140] Step 2281: Determine the digital angular frequency of the digital filter based on the center frequency and the preset sampling frequency.

[0141] The sampling frequency is the frequency at which the digital signal processor samples the audio signal; it can be a preset fixed frequency value. For example, the sampling frequency could be 48kHz, 96kHz, etc.

[0142] The digital angular frequency can be an angular frequency related to the center frequency and the sampling frequency. It can affect the frequency characteristics of a digital filter.

[0143] In some alternative implementations, the center frequency and the preset sampling frequency can be substituted into the formula. Among them, f c f represents the center frequency. s Let ω0 represent the digital angular frequency of the digital filter, and let ω0 represent the digital angular frequency of the digital filter. Alternatively, the center frequency and a preset sampling frequency can be substituted into the above formula, and the calculation result can be optimized to obtain the digital angular frequency of the digital filter.

[0144] Step 2282: Determine the bandwidth factor of the digital filter based on the digital angular frequency and quality factor.

[0145] The bandwidth factor can be used to calculate the denominator coefficients of a digital filter.

[0146] In some alternative implementations, the digital angular frequency and quality factor can be substituted into the formula for bandwidth factor. Where ω0 represents the digital angular frequency, Q represents the quality factor, and a represents the bandwidth factor, thus obtaining the bandwidth factor. Alternatively, the digital angular frequency and quality factor can be substituted into the above formula, and the calculation result can be optimized to obtain the bandwidth factor.

[0147] Step 2283: Determine the linear gain of the digital filter based on the gain deviation information.

[0148] Among them, linear gain can reflect the magnitude of adjustment required for the audio signal.

[0149] In some alternative implementations, the gain value from the gain deviation information can be substituted into the formula A = 10. G / 20 Where G represents the gain bias, thus obtaining a linear gain. Alternatively, the gain value from the gain bias information can be substituted into the above formula, and the calculation result can be optimized to obtain a linear gain.

[0150] Step 2284: Determine the numerator and denominator coefficients of the digital filter based on the digital angular frequency, bandwidth factor, and linear gain.

[0151] The numerator coefficients can be the coefficients for the forward signal processing of a second-order IIR filter. They can affect the forward filtering effect of the audio signal and determine how the digital filter weights the input signal.

[0152] The denominator coefficients can be the coefficients used in the feedback signal processing of a second-order IIR digital filter. They can affect the feedback filtering effect of the audio signal and determine the stability and frequency selectivity of the digital filter.

[0153] In some alternative implementations, the digital angular frequency, bandwidth factor, and linear gain can be substituted into the coefficient calculation formula of the second-order IIR digital filter to obtain the numerator and denominator coefficients. Alternatively, the digital angular frequency, bandwidth factor, and linear gain can be substituted into the coefficient calculation formula of the second-order IIR digital filter, and the calculation results can be optimized to obtain the numerator and denominator coefficients.

[0154] Step 2285: Determine the target tuning information for the digital signal processor based on the numerator and denominator coefficients.

[0155] In some alternative implementations, the calculated numerator and denominator coefficients can be directly used as the target tuning information for the digital signal processor. Alternatively, the numerator and denominator coefficients can be normalized to obtain the target tuning information.

[0156] In some alternative implementations, taking a second-order IIR digital filter as an example, the difference equation of the second-order IIR digital filter can be described as:

[0157] y[n]=b0x[n]+b1x[n-1]+b2x[n-2]-a1y[n-1]-a2y[n-2]

[0158] Formula (7)

[0159] In formula (7), y[n] represents the output signal at the nth sampling time, x[n] represents the input signal at the nth sampling time, b0, b1, and b2 represent the numerator coefficients, and a1 and a2 represent the denominator coefficients. Where b0 = 1 + aA; b1 = -2cos(ω0); b2 = 1 - αA μ ; a1 = -2cos(ω0); Digital angular frequency Among them, f c f represents the center frequency. s Indicates the sampling frequency. Linear gain. Where G represents the gain deviation, measured in dB. Bandwidth factor Where ω0 represents the digital angular frequency and Q represents the quality factor.

[0160] Then, normalization operations are performed on b0, b1, b2, a1, and a2 by dividing by a0 to obtain the target tuning information.

[0161] In some alternative implementations, in addition to the second-order digital filter, other orders of digital filters (such as first-order, third-order, etc.) can be used to determine the target tuning information of the digital signal processor. This will not be elaborated further here.

[0162] Based on the embodiments of this disclosure, the numerator and denominator coefficients are determined from three dimensions: frequency characteristics (digital angular frequency), frequency selection characteristics (bandwidth factor), and amplitude characteristics (linear gain). Then, the target tuning information of the digital signal processor is determined based on the numerator and denominator coefficients. This allows the target tuning information to better match the actual frequency response deviation and gain deviation, enabling the digital filter to more accurately filter and compensate for distorted signals, suppressing frequency response distortion and nonlinear distortion, thereby further improving audio quality.

[0163] Any of the audio signal processing methods provided in this disclosure can be executed by any suitable device with data processing capabilities, including but not limited to: in-vehicle electronic devices, terminal devices, and servers. Alternatively, any of the audio signal processing methods provided in this disclosure can be executed by a processor, such as by a processor executing any of the audio signal processing methods mentioned in this disclosure by calling corresponding instructions stored in memory. Further details will not be elaborated below.

[0164] Exemplary device

[0165] Figure 11 This is a schematic diagram of the structure of an audio signal processing apparatus provided in an exemplary embodiment of this disclosure. The audio signal processing apparatus of this disclosure can be used to implement the audio signal processing method of any of the above embodiments. Figure 11 As shown, the audio signal processing device in this embodiment may include:

[0166] The first determining unit 510 is configured to determine the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device. The first audio signal is output to the audio playback device by the digital signal processor, and then played by the audio playback device and acquired by the audio acquisition device to obtain the second audio signal.

[0167] The second determining unit 520 is configured to determine the target tuning information of the digital signal processor based on the target acoustic transmission characteristics, so that the digital signal processor can perform tuning processing on the received audio signal based on the target tuning information.

[0168] Figure 12This is a schematic diagram of the structure of an audio signal processing apparatus provided in yet another exemplary embodiment of this disclosure. (See diagram below.) Figure 12 As shown, in Figure 11 Based on the illustrated embodiment, in some possible implementations, the second determining unit 520 may include:

[0169] The first determining subunit 5210 is configured to determine the frequency response deviation information of the target acoustic transmission feature relative to a preset acoustic transmission feature;

[0170] The second determining subunit 5220 is configured to determine the center frequency, high-frequency cutoff frequency and low-frequency cutoff frequency of the digital filter running on the digital signal processor based on frequency response deviation information.

[0171] The third determining subunit 5230 is configured to determine the bandwidth of the digital filter based on the high-frequency cutoff frequency and the low-frequency cutoff frequency.

[0172] The fourth determining subunit 5240 is configured to determine the target tuning information of the digital signal processor based on the center frequency and bandwidth.

[0173] In some alternative implementations, the second determining subunit 5220 may include:

[0174] The first determining module 5221 is configured to determine the center frequency of the digital filter based on the peak of the frequency response curve represented by the frequency response deviation information, wherein the frequency response curve characterizes the correspondence between the frequency and gain of the audio signal to be processed by the digital filter.

[0175] The second determining module 5222 is configured to determine the high-frequency cutoff frequency and low-frequency cutoff frequency of the digital filter based on the frequencies in the frequency response curve that correspond to the preset gain.

[0176] In some alternative implementations, the fourth determining subunit 5240 may include:

[0177] The third determining module 5241 is configured to determine the quality factor of the digital filter based on the center frequency and bandwidth.

[0178] The fourth determination module 5242 is configured to determine the target tuning information of the digital signal processor based on the quality factor.

[0179] In some alternative implementations, the second determining unit 520 may include:

[0180] The fifth determining subunit 5250 is configured to determine the gain deviation information of the target acoustic transmission characteristics relative to the preset acoustic transmission characteristics;

[0181] The sixth determining subunit 5260 is configured to determine the target tuning information of the digital signal processor based on gain deviation information.

[0182] In some alternative implementations, the sixth determining subunit 5260 may include:

[0183] The fifth determining module 5261 is configured to determine the digital angular frequency of the digital filter based on the center frequency and a preset sampling frequency;

[0184] The sixth determining module 5262 is configured to determine the bandwidth factor of the digital filter based on the digital angular frequency and the quality factor.

[0185] The seventh determining module 5263 is configured to determine the linear gain of the digital filter based on the gain deviation information;

[0186] The eighth determining module 5264 is configured to determine the numerator and denominator coefficients of the digital filter based on the digital angular frequency, bandwidth factor, and linear gain.

[0187] The ninth determining module 5265 is configured to determine the target tuning information of the digital signal processor based on the numerator and denominator coefficients.

[0188] In some alternative implementations, the first determining unit 510 may include:

[0189] The seventh determining subunit 5110 is configured to determine the auto-power spectral density of the first audio signal output by the digital signal processor;

[0190] The eighth determining subunit 5120 is configured to determine the cross power spectral density between the first audio signal and the second audio signal;

[0191] The ninth determining subunit 5130 is configured to determine the target acoustic transfer characteristics between the digital signal processor and the audio acquisition device based on the self-power spectral density and the cross-power spectral density.

[0192] In some alternative implementations, the first determining unit 510 may include:

[0193] The tenth determining subunit 5140 is configured to, in response to the satisfaction of the tuning trigger condition and the vehicle being in a preset state, determine the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device.

[0194] The tuning triggering conditions include at least one of the following: the current time is the preset tuning time, and a tuning triggering operation is detected;

[0195] The preset state includes at least one of the following: the vehicle is stationary, the vehicle is in neutral, the doors are closed, the vehicle seats are in preset positions, and the audio acquisition equipment in the vehicle is not obstructed.

[0196] The exemplary embodiments of this device correspond to the exemplary method section described above in terms of implementation. The corresponding content between the two can be referenced, combined, and cited, and will not be repeated here. The beneficial technical effects corresponding to the exemplary embodiments of this device can be found in the corresponding beneficial technical effects of the exemplary method section described above, and will not be repeated here.

[0197] Exemplary System

[0198] Figure 13 This is a schematic diagram of the structure of an audio signal processing system provided in an exemplary embodiment of this disclosure.

[0199] like Figure 13 As shown, the audio signal processing system includes: an audio acquisition device 303, an audio playback device 302, a digital signal processor 301, and an audio signal processing unit 304.

[0200] The audio signal processing device 304 may be the audio signal processing device described in the above exemplary device section.

[0201] The audio acquisition device 303, audio playback device 302, digital signal processor 301, and audio signal processing apparatus 304 in the exemplary embodiment of this system each have the features described in the above exemplary methods and / or apparatus sections. Their contents can be referred to, combined with, and cited in the above exemplary methods and / or apparatus sections, and will not be repeated here. The beneficial technical effects corresponding to the exemplary embodiment of this system can be found in the corresponding beneficial technical effects of the above exemplary methods and / or apparatus sections, and will not be repeated here.

[0202] Exemplary electronic devices

[0203] Figure 14 A structural diagram of an electronic device provided in an embodiment of this disclosure includes at least one processor 111 and a memory 112.

[0204] The processor 111 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0205] The memory 112 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 111 may execute one or more computer program instructions to implement the audio signal processing methods and / or other desired functions of the various embodiments of this disclosure described above.

[0206] In one example, the electronic device may also include an input device 113 and an output device 114, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0207] The input device 113 may also include, for example, a keyboard, a mouse, etc.

[0208] The output device 114 can output various information to the outside, including, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0209] Of course, for the sake of simplicity, Figure 14 Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0210] Exemplary computer program products and computer-readable storage media

[0211] In addition to the methods and apparatus described above, embodiments of this disclosure may also provide a computer program product, including computer program instructions that, when executed by a processor, cause the processor to perform the steps of the audio signal processing methods of the various embodiments of this disclosure described in the "Exemplary Methods" section above.

[0212] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of embodiments of this disclosure. These programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0213] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps in the audio signal processing methods of the various embodiments of this disclosure described in the "Exemplary Methods" section above.

[0214] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, but is not limited to, systems, apparatuses, or devices that are electrical, magnetic, optical, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0215] The basic principles of this disclosure have been described above with reference to specific embodiments. However, the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0216] Various modifications and variations can be made to this disclosure without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, this disclosure is also intended to include such modifications and variations.

Claims

1. An audio signal processing method, the method comprising: Based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device, the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device are determined. The first audio signal is output to the audio playback device by the digital signal processor, and then played by the audio playback device and acquired by the audio acquisition device to obtain the second audio signal. Based on the target acoustic transmission characteristics, the target tuning information of the digital signal processor is determined, so that the digital signal processor can perform tuning processing on the received audio signal based on the target tuning information.

2. The method according to claim 1, wherein, The step of determining the target tuning information of the digital signal processor based on the target acoustic transmission characteristics includes: Determine the frequency response deviation information of the target acoustic transmission characteristics relative to preset acoustic transmission characteristics; Based on the frequency response deviation information, the center frequency, high-frequency cutoff frequency, and low-frequency cutoff frequency of the digital filter running on the digital signal processor are determined. The bandwidth of the digital filter is determined based on the high-frequency cutoff frequency and the low-frequency cutoff frequency. Based on the center frequency and the bandwidth, the target tuning information of the digital signal processor is determined.

3. The method according to claim 2, wherein, The step of determining the center frequency, high-frequency cutoff frequency, and low-frequency cutoff frequency of the digital filter running on the digital signal processor based on the frequency response deviation information includes: Based on the peak of the frequency response curve represented by the frequency response deviation information, the center frequency of the digital filter is determined, wherein the frequency response curve characterizes the correspondence between the frequency and gain of the audio signal to be processed by the digital filter; Based on the frequencies in the frequency response curve that have the corresponding relationship with the preset gain, the high-frequency cutoff frequency and low-frequency cutoff frequency of the digital filter are determined.

4. The method according to claim 2, wherein, Determining the target tuning information of the digital signal processor based on the center frequency and the bandwidth includes: The quality factor of the digital filter is determined based on the center frequency and the bandwidth. Based on the quality factor, the target tuning information of the digital signal processor is determined.

5. The method according to claim 4, wherein, The step of determining the target tuning information of the digital signal processor based on the target acoustic transmission characteristics includes: Determine the gain deviation information of the target acoustic transmission characteristics relative to the preset acoustic transmission characteristics; Based on the gain deviation information, the target tuning information of the digital signal processor is determined.

6. The method according to claim 5, wherein, Determining the target tuning information of the digital signal processor based on the gain deviation information includes: Based on the center frequency and the preset sampling frequency, the digital angular frequency of the digital filter is determined; The bandwidth factor of the digital filter is determined based on the digital angular frequency and the quality factor. Based on the gain deviation information, the linear gain of the digital filter is determined; Based on the digital angular frequency, the bandwidth factor, and the linear gain, the numerator and denominator coefficients of the digital filter are determined. The target tuning information of the digital signal processor is determined based on the numerator coefficient and the denominator coefficient.

7. The method according to any one of claims 1-6, wherein, The determination of the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device includes: Determine the auto-power spectral density of the first audio signal output by the digital signal processor; Determine the cross-power spectral density between the first audio signal and the second audio signal; Based on the self-power spectral density and the cross-power spectral density, the target acoustic transfer characteristics between the digital signal processor and the audio acquisition device are determined.

8. The method according to any one of claims 1-6, wherein, The determination of the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device includes: In response to the satisfaction of the tuning triggering condition and the vehicle being in a preset state, the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device are determined based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device. The tuning triggering condition includes at least one of the following: the current time is a preset tuning time, and a tuning triggering operation is detected; The preset state includes at least one of the following: the vehicle is stationary, the vehicle is in neutral, the doors are closed, the vehicle seats are in preset positions, and the audio acquisition device in the vehicle is not obstructed.

9. An audio signal processing apparatus, comprising: The first determining module is used to determine the target acoustic transmission characteristics between the digital signal processor and the audio acquisition device based on the first audio signal output by the digital signal processor and the second audio signal acquired by the audio acquisition device. The first audio signal is output to the audio playback device by the digital signal processor, played by the audio playback device and acquired by the audio acquisition device to obtain the second audio signal. The second determining module is used to determine the target tuning information of the digital signal processor based on the target acoustic transmission characteristics, so that the digital signal processor can perform tuning processing on the received audio signal based on the target tuning information.

10. An audio playback system, comprising: Audio acquisition device, audio playback device, digital signal processor, and audio signal processing apparatus as described in claim 9.

11. A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the audio signal processing method according to any one of claims 1-8.

12. An electronic device, the electronic device comprising: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the audio signal processing method according to any one of claims 1-8.

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