Audio signal processing method and device, storage medium and computer equipment

Abstract

The embodiment of the invention discloses an audio signal processing method and device, a storage medium and computer equipment. The method comprises the following steps: acquiring an audio signal, and backing up the audio signal to obtain a first audio signal of a first branch and a second audio signal of a second branch; performing feature extraction processing on a time domain on sub-band signals of a plurality of different sub-bands in the first audio signal, and determining a masked masking sub-band based on a processing result of the feature extraction processing; on the basis of the masking sub-band, performing signal attenuation processing on a time domain on the second audio signal of the second branch to obtain a target audio signal corresponding to the audio signal; and outputting the target audio signal. According to the embodiment of the invention, the whole processing process is carried out in the time domain, the calculated amount is reduced while the power of the audio signal is reduced, the processing efficiency and speed of the audio signal are improved, and in addition, the original audio signal is processed based on the masking sub-band, so that the accuracy of the target audio signal can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an audio signal processing method, apparatus, computer-readable storage medium, and computer equipment. Background Art

[0002] In order to enhance the loudness of the sound, current technology strives to improve the power amplifier of the audio signal. Therefore, the demand for saving power while ensuring the loudness of the sound has emerged. The existing power saving algorithms are mainly based on psychoacoustic models, which are often used in audio coding algorithms. Audio coding algorithms usually include: inputting audio signals, using frequency domain analysis when offline, attenuating the unperceived signals, and then inversely transforming to the time domain, and outputting the processed signals. This method of processing audio signals based on psychoacoustic models has a large amount of calculation, which reduces the processing efficiency of audio signals. Summary of the invention

[0003] The embodiments of the present application provide an audio signal processing method, an apparatus, a computer-readable storage medium, and a computer device, which can improve the processing efficiency of the audio signal while reducing the power of the audio signal.

[0004] The present application provides an audio signal processing method, including:

[0005] An audio signal is acquired, and the audio signal is backed up to obtain a first audio signal of a first branch and a second audio signal of a second branch; a feature extraction process is performed on subband signals of a plurality of different subbands in the first audio signal in a time domain, and a masked masked subband is determined from the plurality of different subbands based on a processing result of the feature extraction process; based on the masked subband, a signal attenuation process is performed on the second audio signal in the second branch in a time domain to obtain a target audio signal corresponding to the audio signal; and the target audio signal is output.

[0006] The present application also provides an audio signal processing method, including:

[0007] An audio signal and a sound pressure model of an electroacoustic transducer that plays the audio signal are obtained; the audio signal is converted into a voltage signal, and the voltage signal is processed using the sound pressure model to obtain a predicted sound pressure signal; a feature extraction process is performed in the time domain on sub-band signals of a plurality of different sub-bands in the sound pressure signal; and a masked sub-band that is masked in the sound pressure signal is determined from the plurality of different sub-bands based on the processing result of the feature extraction process.

[0008] The present application also provides an audio signal processing device, including:

[0009] A first acquisition module, used to acquire an audio signal;

[0010] A backup module, used for backing up the audio signal to obtain a first audio signal of a first branch and a second audio signal of a second branch;

[0011] a sub-band determination module, configured to perform feature extraction processing on sub-band signals of a plurality of different sub-bands in the first audio signal in a time domain, and determine a masked sub-band to be masked from the plurality of different sub-bands based on a processing result of the feature extraction processing;

[0012] a masking module, configured to perform signal attenuation processing in a time domain on the second audio signal in the second branch based on the masking subband to obtain a target audio signal;

[0013] An output module is used to output the target audio signal.

[0014] The present application also provides an audio signal processing device, including:

[0015] A second acquisition module, used to acquire an audio signal and a sound pressure model of an electroacoustic transducer that plays the audio signal;

[0016] a sound pressure determination module, configured to convert the audio signal into a voltage signal, and process the voltage signal using the sound pressure model to obtain a predicted sound pressure signal;

[0017] A feature processing module, used for performing feature extraction processing in the time domain on sub-band signals of multiple different sub-bands in the sound pressure signal;

[0018] The sub-band determination module is used to determine a masked sub-band in the sound pressure signal from a plurality of different sub-bands based on a processing result of the feature extraction processing.

[0019] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor to execute the steps in the audio signal processing method described in any of the above embodiments.

[0020] An embodiment of the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the steps in the audio signal processing method described in any of the above embodiments by calling the computer program stored in the memory.

[0021] The audio signal processing method, apparatus, computer-readable storage medium and computer equipment provided in the embodiments of the present application back up the audio signal to obtain the first audio signal and the second audio signal, perform feature extraction processing in the time domain on the sub-band signals of multiple different sub-bands in the first audio signal, and determine the masked masked sub-band based on the processing result of the feature extraction processing, and perform signal attenuation processing in the time domain on the second audio signal in the second branch based on the masked sub-band to obtain the target audio signal. In the embodiments of the present application, both the first audio signal and the second audio signal are processed in the time domain, and the audio signal is no longer converted to the frequency domain first, and is processed in the frequency domain and then converted to the time domain, which reduces the amount of calculation for conversion to the frequency domain and improves the efficiency and speed of audio signal processing. At the same time, due to the signal attenuation processing, the signal power can be reduced. In addition, the audio signal is divided into two branches, the first branch is used to determine the masked sub-band. band, and the second branch directly performs signal attenuation processing in the time domain on the second audio signal, that is, the original audio signal, based on the determined masked subband, so as to improve the accuracy of the target audio signal; in addition, in the embodiment of the present application, the sound pressure model of the electroacoustic transducer that plays the audio signal can also be obtained, and the audio signal is processed by using the sound pressure model to obtain a predicted sound pressure signal, and then the sub-band signals of multiple different sub-bands are subjected to feature extraction processing in the time domain based on the sound pressure signal to determine the masked sub-band in the sound pressure signal. Since the sound pressure model of the electroacoustic transducer takes into account the power amplifier characteristics and frequency response characteristics of the electroacoustic transducer itself, the predicted sound pressure signal is obtained by using the sound pressure model of the electroacoustic transducer, and then the processing is performed based on the sound pressure signal. In this embodiment, the audio signal is no longer directly subjected to feature extraction processing, but the sound pressure signal predicted by the audio signal is subjected to feature extraction processing, thereby improving the accuracy of feature processing of the audio signal and the accuracy of determining the masked sub-band. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A flowchart of an audio signal processing method provided in an embodiment of the present application.

[0024] Figure 2 A schematic diagram of data in the sound pressure model provided in an embodiment of the present application.

[0025] Figure 3 A flowchart of an audio signal processing method provided in an embodiment of the present application is provided.

[0026] Figure 4 Another flowchart of the audio signal processing method provided in an embodiment of the present application.

[0027] Figure 5 A flowchart of another method for processing an audio signal provided in an embodiment of the present application is provided.

[0028] Figure 6 A schematic diagram of the structure of an audio signal processing device provided in an embodiment of the present application.

[0029] Figure 7 A schematic diagram of the structure of an audio signal processing device provided in an embodiment of the present application.

[0030] Figure 8 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0032] The embodiments of the present application provide an audio signal processing method, device, computer-readable storage medium and computer equipment. Specifically, the audio signal processing method of the embodiments of the present application can be executed by a computer device, and the audio signal processing device in the embodiments of the present application is integrated in the computer equipment. Among them, the computer equipment can be a terminal or a server or other equipment. The terminal can be a terminal device such as a smart phone, a tablet computer, a laptop computer, a touch screen, a game console, a personal computer (PC, Personal Computer), a smart speaker, a speaker, etc. The server can be an independent physical server, or a server cluster composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services and cloud databases.

[0033] The following will respectively describe in detail an audio signal processing method, apparatus, computer-readable storage medium and computer equipment provided in the embodiments of the present application. It should be noted that the serial numbers of the following embodiments are not intended to limit the preferred order of the embodiments.

[0034] See also Figure 1 , Figure 1 is a flow chart of an audio signal processing method provided in an embodiment of the present application. The flow of the audio signal processing method can be as follows.

[0035] 101. Acquire an audio signal, and back up the audio signal to obtain a first audio signal of a first branch and a second audio signal of a second branch.

[0036] The audio signal may be an audio signal in any format, such as .mp3, .wav, .aac, etc. The audio signal is obtained and backed up / copied to obtain two audio signals, namely, the first audio signal of the first branch and the second audio signal of the second branch, wherein the first audio signal and the second audio signal are completely identical, and the first audio signal and the second audio signal are completely identical to the audio signal. After the backup is performed, it is convenient to perform different processing on the first audio signal of the first branch and the second audio signal of the second branch respectively.

[0037] 102 : Perform feature extraction processing on subband signals of a plurality of different subbands in the first audio signal in the time domain, and determine a masked subband to be masked from the plurality of different subbands based on a processing result of the feature extraction processing.

[0038] This step defines the feature extraction processing of the first audio signal in the time domain to determine the masked subband, which is called the masked subband. It should be noted that in related schemes, it is usually necessary to convert the audio signal to the frequency domain for processing, such as using algorithms such as Fast Fourier Transform (FFT), wavelet transform, Discrete Fourier Transform (DFT), Sparse Fourier Transform (SFT) to convert the audio signal to the frequency domain for processing, and then attenuate the masking signal before converting it from the frequency domain to the time domain. Among them, the amount of calculation required for processing in the frequency domain is large, and the mutual conversion between the frequency domain and the time domain also requires calculation, which will also bring certain errors. In the embodiment of the present application, the first audio signal is only processed in the time domain to reduce the amount of calculation and improve accuracy.

[0039] In one embodiment, the method further includes: obtaining a sound pressure model of an electroacoustic transducer that plays an audio signal, the sound pressure model can be pre-constructed and saved, and the sound pressure model is a model of the electroacoustic transducer that converts a voltage signal corresponding to an audio signal into a sound pressure signal. The electroacoustic transducer includes an electrostatic transducer, a piezoelectric transducer, a moving coil transducer, etc., which are not specifically limited. Correspondingly, the above-mentioned step of performing feature extraction processing in the time domain on sub-band signals of multiple different sub-bands in the first audio signal includes: converting the first audio signal into a voltage signal, and processing the voltage signal using the sound pressure model to obtain a predicted sound pressure signal; performing feature extraction processing in the time domain on sub-band signals of multiple different sub-bands in the sound pressure signal.

[0040] In this embodiment, the voltage signal corresponding to the first audio signal is converted and processed using the sound pressure model of the electroacoustic transducer to obtain a predicted sound pressure signal, and then the predicted sound pressure signal is subjected to feature extraction processing. That is, the present application takes into account the pronunciation characteristics of the electroacoustic transducer itself (such as frequency response characteristics, etc.), such as the influence of the overall gain of the electroacoustic transducer on the sound pressure signal, and processes the sound pressure signal heard by simulating the sound pressure model instead of directly processing the audio signal, thereby improving the accuracy of the feature extraction processing and making the result of the feature extraction processing more accurate and closer to the actual situation.

[0041] Before obtaining the sound pressure model of the electroacoustic transducer, it is also necessary to construct the sound pressure model of the electroacoustic transducer. In one embodiment, the step of constructing the sound pressure model of the electroacoustic transducer includes: for each frequency band in the multiple frequency bands corresponding to the existing audio signal, providing a test voltage signal for each frequency band; processing the test voltage signal using the electroacoustic transducer, and measuring the first test sound pressure signal output by the electroacoustic transducer at a preset distance; and constructing the sound pressure model of the electroacoustic transducer at the preset distance based on the test voltage signal and the first test sound signal pressure.

[0042] Among them, the multi-band can be a frequency band in which the corresponding sound signal appears more in the existing audio signal, such as the frequency band of 100Hz-15000Hz, or it can be a full frequency band, such as the frequency band of 20Hz-20000Hz, etc. Among them, the existing audio signal refers to the existing audio signal, rather than the audio signal to be processed in step 101. For each frequency band in the multi-band, a test voltage signal of equal amplitude can be provided for each frequency band. Among them, the test voltage signal for each frequency band can be sent simultaneously or separately in time sequence. The test voltage signal is input into the electroacoustic transducer, and the electroacoustic transducer converts the test voltage signal into a sound pressure signal. The sound pressure signal output by the electroacoustic transducer at a preset distance is measured to obtain a first test sound pressure signal. The first test sound pressure signal can be expressed by a sound pressure level, and a sound pressure model of the electroacoustic transducer at a preset distance is constructed according to the test voltage signal and the first test sound pressure signal. Among them, the sound pressure signal output by the electroacoustic transducer can be collected by a microphone to determine the corresponding first test sound pressure signal.

[0043] like Figure 2 As shown, it is a schematic diagram of the data in the sound pressure model provided in an embodiment of the present application, wherein the horizontal axis represents each different frequency band in the multiple frequency bands of the existing audio signal, and the vertical axis represents the first test sound pressure signal measured for different frequency bands, and the first test sound pressure signal is represented by sound pressure level, and the curve represents the corresponding sound pressure level information under the test voltage signal of equal amplitude in different frequency bands.

[0044] The sound pressure model of the electroacoustic transducer is a sound pressure model at a preset distance, and the preset distance may be a distance at which a sound pressure receiver is usually located, or may be a set fixed distance, such as 2 m.

[0045] In one embodiment, the method further includes: obtaining different distances for receiving the test sound pressure signal; processing the test voltage signal using an electroacoustic transducer, and determining the second test sound pressure signal output by the electroacoustic transducer at different distances, and updating the sound pressure model according to the test voltage signal and the second test sound pressure signal to obtain the sound pressure model of the electroacoustic transducer at different distances. Wherein, the second test sound pressure signal can be calculated according to the first test sound pressure signal at a preset distance, or can be obtained by measuring the signal output by the electroacoustic transducer at different distances. In this embodiment, it is further defined that the sound pressure model is not only related to the self-pronunciation characteristics of the electroacoustic transducer, but also to the different distances of the receiver of the sound pressure from the electroacoustic transducer. It can be understood that the distance from the electroacoustic transducer is different, and the sound heard is different. In this embodiment, not only the pronunciation characteristics of the electroacoustic transducer are considered, but also the distance characteristics are considered, so that the sound pressure signal predicted by the sound pressure model is more accurate and closer to the actual situation.

[0046] In one embodiment, since environmental factors such as temperature and air pressure may also have a certain impact on the sound pressure signal output by the electroacoustic transducer, the sound pressure model of the electroacoustic transducer may also be updated according to the temperature and air pressure.

[0047] After obtaining the sound pressure model of the electroacoustic transducer, the sound pressure model can be used to process the first audio signal to obtain a predicted sound pressure signal. Specifically, the first audio signal of the first branch is converted into a voltage signal, for example, the first audio signal is subjected to digital-to-analog conversion processing to be converted into an analog signal such as an analog voltage signal, and then the analog signal such as the analog voltage signal is subjected to gain processing, such as amplification processing, to obtain an amplified analog signal such as an analog voltage signal, the amplified analog voltage signal is the voltage signal input into the sound pressure model of the electroacoustic transducer, the voltage signal is input into the sound pressure model of the electroacoustic transducer, and the voltage signal is processed using the sound pressure model to obtain a predicted sound pressure signal, specifically, as Figure 3 or Figure 4 It should be noted that the sound pressure signal is predicted by the sound pressure model of the electroacoustic transducer, and is not a real sound pressure signal. Since the sound pressure model of the electroacoustic transducer is obtained based on the sound characteristics and / or distance characteristics of the electroacoustic transducer itself, the predicted sound pressure signal is very close to the real sound pressure signal.

[0048] After the predicted sound pressure signal is obtained, feature extraction processing in the time domain is performed on sub-band signals of multiple different sub-bands in the sound pressure signal.

[0049] Specifically, the predicted sound pressure signal is subjected to time domain filtering through multiple first filtering units. For example, according to the frequency decomposition characteristics of the cochlea, the predicted sound pressure signal is subjected to time domain filtering to divide the sound pressure signal into multiple sub-band signals of different sub-bands, so as to realize the frequency division of the predicted sound pressure signal into multiple different sub-bands. Among them, the frequency range of each sub-band is different. Since the predicted sound pressure signal is very close to the sound pressure signal actually heard, the sound pressure signal is subjected to time domain filtering to make the frequency division of the sound pressure signal more accurate; wherein each sub-band corresponds to a first filtering unit, each first filtering unit includes one or more filters, and the filter coefficients of each first filtering unit are different and fixed; performing time domain filtering can be understood as the input sound pressure signal being a signal in a time series, and the output multiple sub-band signals are also signals in a time series, and the intermediate processing process is not converted to the frequency domain for processing. Finally, the multiple sub-band signals are subjected to feature extraction processing respectively, such as sound energy processing, to estimate the sound energy of the sub-band signal corresponding to each sub-band, such as Figure 3 or Figure 4 In this embodiment, since the frequency division is more accurate, the sound energy corresponding to each sub-band signal after processing is also more accurate, thereby improving the accuracy of determining the sound energy.

[0050] The feature extraction process includes acoustic energy processing / acoustic energy estimation processing, wherein the acoustic energy processing / acoustic energy estimation processing can be performed in real time or offline. The processing result of the feature extraction process includes acoustic energy of multiple different sub-bands, and the acoustic energy can be represented by sound pressure level, acoustic power or sound intensity level, etc. Correspondingly, the step of determining the masked masked sub-band based on the processing result of the feature extraction process includes: determining the masked masked sub-band based on the psychoacoustic model and the acoustic energy of multiple different sub-bands. For example, the sub-bands with lower acoustic energy and / or that cannot be heard by the human ear among the multiple different sub-bands are determined as masked masked sub-bands, and the other sub-bands of the multiple different sub-bands except the masked sub-bands are used as non-masked sub-bands. Wherein, each sub-band corresponds to a sub-band identifier, such as a sub-band number, etc., and the masked sub-band includes a masked sub-band identifier, and the determined masked sub-band can be represented by the masked sub-band identifier, and the masked sub-band identifier can be a masked sub-band number, etc., which is not specifically limited. In this embodiment, since the frequency division is more accurate, the accuracy of determining the acoustic energy is improved. When the masked sub-band is determined based on the acoustic energy, the accuracy of determining the masked sub-band is further improved.

[0051] In one embodiment, the above-mentioned step of determining a masked masked subband from multiple different subbands based on a psychoacoustic model and the sound energy of multiple different subbands includes: obtaining a masking model of one of the multiple different subbands, the masking model including a masking threshold for the subband to mask other subbands; comparing the sound energy of each subband in the other subbands with the corresponding masking threshold; if there is another subband whose sound energy is lower than the corresponding masking threshold, determining the other subband as a masked masked subband.

[0052] Among them, the masking model is a kind of psychoacoustic model. When two sub-bands or different sub-bands mask each other, there is a corresponding masking model. The masking model of one of the sub-bands is taken. The masking model includes the masking range of the sub-band and the masking degree of other sub-bands, such as the masking threshold corresponding to the sub-band to other sub-bands. The acoustic energy of each sub-band in other sub-bands is compared with the masking threshold corresponding to each sub-band, and the other sub-bands whose acoustic energy is lower than the corresponding masking threshold are determined as masked masked sub-bands. Among them, any other sub-bands whose acoustic energy is lower than the corresponding masking threshold are determined as masked masked sub-bands.

[0053] For example, the multiple subbands include A subband, B subband and C subband, and the masking model of A subband is obtained, which includes the masking range of A subband, the masking threshold of A subband to B subband, the masking threshold of A subband to C subband, etc. The acoustic energy of B subband is compared with the masking threshold of B subband. If the acoustic energy of B subband is lower than the masking threshold of B subband, the B subband is determined to be a masked masked subband. If the acoustic energy of B subband is not lower than the masking threshold of B subband, it means that B subband does not need to be masked, that is, B subband is a non-masked subband. Similarly, the acoustic energy of C subband is compared with the masking threshold of C subband. If the acoustic energy of C subband is lower than the masking threshold of C subband, the C subband is determined to be a masked masked subband. If the acoustic energy of C subband is not lower than the masking threshold of C subband, it means that C subband does not need to be masked, that is, C subband is a non-masked subband.

[0054] In one embodiment, the above-mentioned step of determining the masked masked subband from multiple different subbands based on the psychoacoustic model and the sound energy of multiple different subbands includes: comparing the sound energy of any two subbands among the multiple different subbands to obtain an energy ratio; when the energy ratio exceeds a preset threshold, the subband corresponding to the denominator is determined as the masked masked subband.

[0055] The energy ratio of any two subbands refers to log(acoustic energy of one subband / acoustic energy of another subband). For example, any two subbands may be subband A and subband B, and the energy ratio of subband A and subband B is log(acoustic energy of subband A / acoustic energy of subband B). If the energy ratio is greater than a preset threshold, it means that the acoustic energy of subband B is smaller, and subband B is determined to be a masked masked subband. That is, if the energy ratio exceeds the preset threshold, the subband corresponding to the denominator is determined to be a masked masked subband. In this way, all masked masked subbands in multiple different subbands are determined.

[0056] In one embodiment, the step of determining the masked sub-band from the plurality of different sub-bands based on the acoustic energy of the plurality of different sub-bands comprises: comparing the acoustic energy of each sub-band in the plurality of different sub-bands with the absolute hearing threshold; if there is a sub-band whose acoustic energy is lower than the absolute hearing threshold, then the sub-band is determined to be the masked sub-band, that is, all sub-bands whose acoustic energy is lower than the absolute hearing threshold are determined to be the masked sub-band. The absolute hearing threshold refers to the threshold for estimating the minimum sound that can be heard by the human ear. If the acoustic energy of the sub-band is lower than the absolute hearing threshold, it is considered that it is almost inaudible, and then the sub-band is determined to be the masked sub-band.

[0057] In some embodiments, the masked subband to be masked may be determined by other means, for example, the masked subband to be masked may be determined based on non-simultaneous masking, wherein the non-simultaneous masking is a part of the psychoacoustic model.

[0058] The above-mentioned multiple methods can also be combined, for example, the absolute hearing threshold method and non-simultaneous masking are used together to determine the masked masked sub-band. It should be noted that no matter which method is used to determine the masked masked sub-band, it is determined based on the psychoacoustic model.

[0059] The above embodiments provide a method for easily and accurately identifying a masked sub-band signal that is masked in an audio signal, thereby improving the accuracy and efficiency of determining the masked sub-band signal.

[0060] After the first branch determines the acoustic energy of each different subband and the masked masked subband, the determined acoustic energy of each subband and the masked subband identifier of the masked subband are sent to the second branch, so that the second branch processes the second audio signal.

[0061] 103 . Perform signal attenuation processing in the time domain on the second audio signal of the second branch based on the masking subband to obtain a target audio signal of the audio signal.

[0062] For the second audio signal of the second branch, based on the masking subband, the second audio signal, that is, the original audio signal, is directly subjected to signal attenuation processing in the time domain. It should be noted that the signal attenuation processing is performed in the time domain, and is not converted to the frequency domain for processing.

[0063] In one embodiment, a signal attenuator is set for each of the multiple different sub-bands, and the method further includes: determining characteristic parameters of the signal attenuator corresponding to each sub-band. The characteristic parameters of the signal attenuator of each sub-band can be determined according to the sub-band signal of each sub-band, so that different sub-bands have different characteristic parameters according to the differences in the corresponding sub-band signals, wherein the characteristic parameters of the signal attenuator refer to the parameters of the signal attenuator itself.

[0064] In one embodiment, the step of determining the characteristic parameters of the signal attenuator corresponding to each sub-band includes: obtaining the center frequency and bandwidth of the critical sub-band of each sub-band; and determining the characteristic parameters of the signal attenuator corresponding to each sub-band according to the center frequency and bandwidth. Each sub-band corresponds to a critical sub-band, which can also be called a critical frequency band.

[0065] Among them, when noise masks a pure tone, what takes effect is the noise frequency within a certain frequency bandwidth with the pure tone frequency as the center frequency. If the noise power within this frequency bandwidth is equal to the power of the pure tone that can just be heard in the noise, then this frequency band is called the auditory critical frequency band, which is also the critical sub-band in this application.

[0066] In this embodiment, the characteristic parameters of the signal attenuator are designed according to the center frequency and bandwidth of the critical sub-band of psychoacoustics, that is, the characteristic parameters of the signal attenuator are designed according to the sound frequency perception ability of the human body, so that the determination of the characteristic parameters of the signal attenuator is closely related to the sound frequency perception ability of the human body, and the characteristic parameters are dynamically determined by the sound frequency perception ability of the human body, thereby improving the real-time and accuracy of the determination of the characteristic parameters of the signal attenuator.

[0067] In one embodiment, for a signal attenuator corresponding to each sub-band in a plurality of different sub-bands, the method further comprises: determining an attenuation parameter of the signal attenuator corresponding to each sub-band. If the signal attenuator is a second filter unit, the attenuation parameter of the second filter unit includes a gain parameter of the second filter unit; if the signal attenuator is a multi-band dynamic range control, the attenuation parameter of the multi-band dynamic range control includes a compression ratio and / or a compression threshold. Each second filter unit includes at least one filter.

[0068] Among them, since the determined masked subband is represented by a masked subband identifier, and each subband corresponds to a signal attenuator, the above-mentioned step of performing signal attenuation processing in the time domain on the second audio signal of the second branch based on the masked subband to obtain the target audio signal corresponding to the audio signal includes: when the masked subband identifier is obtained, updating the attenuation parameter of the signal attenuator corresponding to the masked subband, and when the masked subband identifier is not obtained, keeping the attenuation parameter of the signal attenuator corresponding to the subband unchanged; using the corresponding signal attenuator to perform signal attenuation processing in the time domain on the second audio signal of the second branch to obtain the target audio signal corresponding to the audio signal. In this embodiment, the second audio signal is subjected to signal attenuation processing by the signal attenuators corresponding to different subbands to attenuate the second audio signal, that is, to attenuate the original audio signal, thereby saving power consumption, and the human ear cannot perceive the attenuation of the second audio signal.

[0069] Among them, after determining the masked sub-band, the first branch sends the masked sub-band identifier and the sound energy corresponding to each sub-band to the second branch. Since each sub-band corresponds to a signal attenuator, when the second branch obtains the masked sub-band identifier, the signal attenuator of the masked sub-band corresponding to the masked sub-band identifier is turned on to update the attenuation parameter of the signal attenuator corresponding to the masked sub-band. If the second branch does not obtain the masked sub-band identifier, the signal attenuator of the sub-band is kept closed, that is, the attenuation parameter of the signal attenuator corresponding to the sub-band is not updated, and the attenuation parameter of the original signal attenuator is kept unchanged.

[0070] Among them, turning on the signal attenuator of the masked subband means that the attenuation parameter in the signal attenuator can be dynamically adjusted. For example, when the signal attenuator is the second filtering unit, dynamically adjusting the attenuation parameter in the signal attenuator can be understood as dynamically adjusting the gain parameter in the second filtering unit, wherein the frequency band range of the second filtering unit remains unchanged, and only the gain parameter of the second filtering unit is adjusted to adjust the attenuation size.

[0071] The second audio signal is subjected to a signal attenuation process in the time domain by a dynamically adjusted signal attenuator to obtain the second audio signal, that is, the target audio signal corresponding to the original audio signal. The second audio signal is subjected to signal attenuation process by using a dynamically adjusted signal attenuator to determine the attenuation parameter of the signal attenuator in real time according to a specific sub-band (such as a masked sub-band), without using a fixed offline signal attenuator (with a fixed attenuation parameter) to perform signal attenuation process, thereby improving the accuracy of signal attenuation process.

[0072] When the signal attenuator is a second filter unit, the second filter unit can also be understood as a dynamic filter unit, and the attenuation parameter of each second filter unit is initially set to the initial gain of the second filter unit. The initial gain of each second filter unit can be set to a fixed value, such as 0dB, so as not to affect other sub-bands. Correspondingly, the above-mentioned step of updating the attenuation parameter of the signal attenuator corresponding to the masked sub-band includes: reducing the initial gain of the second filter unit corresponding to the masked sub-band to a target gain, which is a preset gain or gain data determined according to the sound energy of the masked sub-band, wherein the preset gain has an effect on the gain of other sub-bands that does not exceed a preset decibel, such as 1dB. Among them, reducing the initial gain to the target gain is a dynamically changing process, and the gain change amplitude is not limited; correspondingly, the step of using the corresponding signal attenuator to perform signal attenuation processing in the time domain on the second audio signal of the second branch includes: using the second filter unit corresponding to the masked subband and the second filter unit corresponding to the unmasked subband to perform first signal filtering processing in the time domain on the second audio signal to attenuate the corresponding amplitude in the second audio signal, wherein the attenuation parameter of the second filter unit corresponding to the masked subband is the target gain, and the attenuation parameter of the second filter unit corresponding to the unmasked subband is the initial gain.

[0073] Among them, the preset gain in the target gain can be a fixed gain data, that is, the initial gain of the second filter unit is reduced to a fixed gain data; the target gain can also be a gain data determined according to the acoustic energy of the masked subband, for example, the target gain can be set as a function of the energy ratio, so that the target gain can be dynamically determined, that is, the range of change of the gain parameter of the second filter unit can be dynamically determined. Among them, it should be noted that the initial gain of the second filter unit is first dynamically determined, and then the target gain of the second filter unit is dynamically determined. For the second filter unit of each masked subband, two dynamic adjustments are achieved. Among them, there is no restriction on the gain change speed of reducing the initial gain of the second filter unit to the target gain, which can be a variable gain change speed or a fixed gain change speed. Since the gain change rate is not limited, the gain parameter of the second filter unit is gradually changed, and the change of the gain parameter will last for some time. In the stage of gain parameter change, the second filter unit with a change in gain parameter is still used to perform the first signal filtering process.

[0074] For all second filtering units within a time window (a period of time), when the corresponding second filtering unit receives the masked subband identifier sent by the first branch, the corresponding second filtering unit is turned on, and the gain parameter of the second filtering unit is updated, such as updating the initial gain to the target gain. When the corresponding second filtering unit does not receive the masked subband identifier sent by the first branch, the second filtering unit is kept closed, the gain parameter is kept as the initial gain, and the next time window is processed in the same way.

[0075] It is assumed that n second filtering units are provided in a computer device, such as Figure 3 As shown, the n second filtering units may be second filtering unit 1, second filtering unit 2, ..., second filtering unit n, respectively, and the n second filtering units correspond to n different sub-bands. The n second filtering units may perform a first signal filtering process on a second audio signal within a period of time in the time domain, such as 1-2 ms, and then perform a first signal filtering process on the second audio signal within a next period of time, such as 2-3 ms, until the second audio signal is processed.

[0076] Among them, taking a period of 1 ms as an example, if the masked subband identifier is received / obtained, the second filter unit of the masked subband corresponding to the masked subband identifier is turned on, and the initial gain of the second filter unit is reduced to the target gain (such as Figure 3 The second filter unit parameter changes in the mask subband), and the second filter unit with the changed gain parameter performs the first signal filtering processing on the second audio signal of 1-2ms; if the mask subband identifier is not received / not obtained / not present, the corresponding second filter unit is kept closed, that is, the gain parameter is not changed, and the first signal filtering processing is performed on the second audio signal of 1-2ms using the corresponding second filter unit (the gain parameter in the second filter unit is the initial gain); if only a part of the mask subband identifier is received, the second filter unit parameter of the mask subband corresponding to the mask subband identifier is changed, and the parameters of the second filter unit corresponding to other subbands such as the non-masked subband remain unchanged, and the first signal filtering processing is performed on the second audio signal of 1-2ms using n second filter units. Then, the first signal filtering processing is performed once on the second audio signal of 2-3ms in the time domain, and it is processed in the same way as the second audio signal of 1-2ms. In this way, the processing of the entire second audio signal is completed to obtain the target audio signal.

[0077] When the signal attenuator is a multi-band dynamic range control (MBDRC), the MBDRC is used to perform signal attenuation processing on the second audio signal of the second branch. The signal attenuator may include multiple MBDRCs, and each sub-band corresponds to one MBDRC. When the multi-band dynamic range control is used, each sub-band uses one MBDRC to perform signal attenuation processing. For the audio signal in each sub-band, the corresponding amplitude is also different. Therefore, multiple dynamic range controls (DRCs, Dynamic Range Control) in each MBDRC are used to process audio signals with different amplitudes in the corresponding sub-band.

[0078] Each MBDRC corresponds to a compression threshold and / or a compression ratio, and the initial compression threshold and / or initial compression ratio in each MBDRC is determined as the initial control threshold of the corresponding MBDRC, that is, the attenuation parameters of different signal attenuators are the initial control threshold of each MBDRC in different MBDRCs, including the initial compression threshold and / or the initial compression ratio, wherein the initial compression threshold and the initial compression ratio can be a certain compression threshold such as 1 and a certain compression ratio such as 1, respectively.

[0079] Taking the initial control threshold of each MBDRC including the initial compression threshold and the initial compression ratio as an example for explanation, correspondingly, the step of updating the attenuation parameter of the signal attenuator corresponding to the masked subband includes: adjusting the control threshold of the MBDRC corresponding to the masked subband from the initial control threshold to the target control threshold, where the target control threshold is a preset control threshold or a control threshold determined according to the sound energy of the masked subband, specifically including: adjusting the initial compression threshold of the MBDRC corresponding to the masked subband to the target compression threshold, and at the same time, adjusting the initial compression ratio of the MBDRC corresponding to the masked subband to the target compression ratio; correspondingly, the step of performing signal attenuation processing in the time domain on the second audio signal of the second branch using the corresponding signal attenuator includes: performing second signal filtering processing in the time domain on the second audio signal using the target control threshold of the MBDRC of the masked subband, such as the target compression threshold and the target compression ratio, and the initial control threshold of the MBDRC of the non-masked subband, such as the initial compression threshold and the initial compression ratio, i.e., performing signal compression processing in the time domain on the second audio signal using the target control threshold of the masked subband and the initial control threshold of the non-masked subband.

[0080] Among them, for each MBDRC, input signals of different energies in different frequency bands will correspond to outputs of different energies. For example, when the input signal of a certain frequency band, such as the input signal corresponding to the masked subband, is higher than a corresponding control threshold, the input signal is compressed according to the target control threshold and the target compression ratio. For example, if it is higher than -10db, it is always output as a fixed value, and compressed using the target compression ratio. When the masked subband identifier is obtained, the corresponding MBDRC is turned on to adjust the control threshold corresponding to the MBDRC, such as adjusting from the initial compression threshold to the target compression threshold, and adjusting the initial compression ratio to the target compression ratio. When the masked subband identifier is not obtained, the control threshold corresponding to the corresponding MBDRC is kept unchanged, and the initial control threshold is still used to perform the second signal filtering process.

[0081] It is assumed that a computer device is provided with multiple MBDRCs, for example, n MBDRCs, and the n MBDRCs correspond to n different sub-bands, such as Figure 4As shown, the n MBDRCs may be MBDRC1, MBDRC2, ..., MBDRCn. Each MBDRC includes m DRCs, and the m DRCs may adjust the amplitude of the audio signal in the MBDRC. The n MBDRCs may perform a second signal filtering process on a second audio signal within a period of time in the time domain, such as 1-2 ms, and then perform a second signal filtering process on the second audio signal within the next period of time until the second audio signal is processed.

[0082] Still taking a period of 1 ms as an example, if a masked subband identifier is received / obtained, the multi-segment dynamic range control MBDRC of the masked subband corresponding to the masked signal is turned on, and the control threshold of the MBDRC is changed (such as Figure 4 MBDRC1 parameter changes in the image, etc.), changes to the target control threshold, such as adjusting the initial compression threshold to the target compression threshold, adjusting the initial compression ratio to the target compression ratio, so as to use the target control threshold of the MBDRC with parameter changes to perform second signal filtering processing on the second audio signal in 1-2ms; if the masked subband is not received / not obtained / does not exist, the corresponding MBDRC remains closed, that is, the control threshold is not changed, and the initial control threshold of the corresponding MBDRC is used to perform second signal filtering processing; if only a part of the masked subband identifier is received, the control parameter of the MBDRC corresponding to the masked subband identifier changes, and the control parameters of the MBDRC corresponding to other subbands such as non-masked subbands remain unchanged, and the second signal filtering processing is performed on the second audio signal in 1-2ms using n MBDRCs. Then, the second audio signal in 2-3ms in the time domain is subjected to a second signal filtering processing, so that the entire second audio signal processing is completed to obtain the target audio signal.

[0083] In the above embodiment, a signal attenuator is set for each of the multiple different sub-bands, and the attenuation parameter of the signal attenuator corresponding to each sub-band is determined. In some other embodiments, a signal attenuator is only set for the masked sub-band, and only the attenuation parameter of the signal attenuator corresponding to the masked sub-band is determined. Correspondingly, the second audio signal is attenuated using only the signal attenuator corresponding to the masked sub-band. Among them, determining the attenuation parameter of the signal attenuator corresponding to the masked sub-band is consistent with the above, and the details are not repeated.

[0084] The above step 102 divides the first audio signal of the first branch into multiple sub-band signals and performs feature extraction processing on the multiple sub-band signals to identify which sub-bands are masked. It should be noted that in step 102, the first audio signal is processed in the time domain, and there is no need to fix the frame length like frequency domain analysis, and there is no need to consider the frequency resolution effect of frequency domain processing. Step 103 performs signal attenuation processing on the second audio signal in the second branch according to the masked masked sub-band determined by the first branch to obtain the target audio signal. The processing of the second audio signal in step 103 is also processing in the time domain. It should be noted that in step 103, the second audio signal, that is, the original audio signal, is processed, rather than the processed audio signal. Directly processing the original audio signal can improve the accuracy of the processing.

[0085] 104, output the target audio signal.

[0086] That is, the target audio signal processed by the second branch for the second audio signal is output.

[0087] The embodiment of the present application provides a method for accurately and easily identifying a masked subband, accurately and easily attenuating the signal corresponding to the masked subband, which can save power consumption and improve efficiency, and the human ear cannot perceive the attenuation of signal energy. In addition, the entire processing process in the embodiment of the present application is processed in the time domain and is not converted to the frequency domain, which reduces the amount of calculation and further improves efficiency.

[0088] It should be noted that the method in the embodiment of the present application can achieve real-time processing, determine the masked subband in the first audio signal in real time, and perform signal attenuation processing on the second audio signal based on the masked subband in real time. Among them, the signal attenuation processing of the second audio signal of the second branch starts almost simultaneously with the processing of the first audio signal of the first branch. In theory, the signal attenuation processing of the second audio signal of the second branch should be slightly delayed than the processing of the first audio signal of the first branch. The delayed time can be the time for identifying the masked subband in the n subbands corresponding to the n signal attenuators as exemplified above, such as the 1ms exemplified above. This time is completely imperceptible to the user. Undoubtedly, the method in the embodiment of the present application can also be applied to offline scenarios.

[0089] In the embodiment of the present application, the audio signal is divided into two branches for processing. While the masking subband is identified in the first branch, the second branch also performs signal attenuation processing. The two branches perform processing in parallel, further improving the efficiency of audio signal processing. In addition, the second branch processes the second audio signal, that is, performs signal attenuation processing on the original audio signal, rather than processing the sound pressure signal. There is little meaning in processing the sound pressure signal, and performing signal attenuation processing on the original audio signal improves the accuracy and authenticity of the signal attenuation processing.

[0090] Figure 5 Detailed description of the invention The present invention provides an audio signal processing method according to an embodiment of the present invention. The method comprises the following steps.

[0091] 201, obtaining an audio signal, and obtaining a sound pressure model of an electroacoustic transducer that plays the audio signal.

[0092] It is necessary to pre-build a sound pressure model of the electroacoustic transducer. For the specific steps of building the sound pressure model of the electroacoustic transducer, please refer to the description of the corresponding steps above, which will not be repeated here.

[0093] 202 , converting the audio signal into a voltage signal, and processing the voltage signal using a sound pressure model to obtain a predicted sound pressure signal.

[0094] The audio signal is converted into a voltage signal, for example, the audio signal is converted into an analog signal such as an analog voltage signal, and then the analog signal such as the analog voltage signal is amplified to obtain an amplified analog voltage signal, and the amplified analog voltage signal is the voltage signal input into the sound pressure model of the electroacoustic transducer, and the voltage signal is input into the sound pressure model of the electroacoustic transducer, and the voltage signal is processed using the sound pressure model to obtain a predicted sound pressure signal.

[0095] 203 : Perform feature extraction processing in the time domain on sub-band signals of multiple different sub-bands in the sound pressure signal.

[0096] Specifically, the sound pressure signal is subjected to time domain filtering by multiple first filtering units to be divided into multiple sub-band signals of different sub-bands, wherein each sub-band corresponds to a first filtering unit; and the multiple sub-band signals are subjected to sound energy processing respectively to estimate the sound energy of each sub-band signal. The sound energy may be a sound pressure level, a sound power, a sound intensity level, etc., which is not specifically limited.

[0097] 204 , determining a masked subband in the sound pressure signal from a plurality of different subbands based on the processing result of the feature extraction processing.

[0098] The feature extraction process includes acoustic energy processing / acoustic energy estimation processing, and the processing result of the feature extraction process includes acoustic energy of multiple different sub-bands, and the acoustic energy can be represented by sound pressure level, acoustic power or sound intensity level, etc. Correspondingly, the step of determining the masked sub-band in the sound pressure signal based on the processing result of the feature extraction process includes: determining the masked sub-band in the sound pressure signal based on the psychoacoustic model and the acoustic energy of multiple different sub-bands.

[0099] In one embodiment, the step of determining the masked masked subband in the sound pressure signal based on the psychoacoustic model and the sound energy of multiple different subbands includes: obtaining a masking model of one of the multiple different subbands, the masking model including a masking threshold for the subband to mask other subbands; comparing the sound energy of each subband in the other subbands with the corresponding masking threshold; if there is another subband whose sound energy is lower than the corresponding masking threshold, determining the other subband as the masked masked subband.

[0100] In one embodiment, the step of determining the masked masked subband in the sound pressure signal based on the psychoacoustic model and the sound energy of multiple different subbands includes: comparing the sound energy of any two subbands among the multiple different subbands to obtain an energy ratio; when the energy ratio exceeds a preset threshold, the subband corresponding to the denominator is determined as the masked masked subband.

[0101] In one embodiment, the step of determining the masked sub-band in the sound pressure signal based on the psychoacoustic model and the sound energy of multiple different sub-bands includes: comparing the sound energy of each sub-band in the multiple different sub-bands with the absolute hearing threshold; if there is a sub-band whose sound energy is lower than the absolute hearing threshold, then determining the sub-band as a masked sub-band, that is, all sub-bands whose sound energy is lower than the absolute hearing threshold are determined as masked sub-bands.

[0102] In some other embodiments, the masked sub-band to be masked may be determined by other methods, for example, the masked sub-band to be masked may be determined based on non-simultaneous masking.

[0103] The above-mentioned multiple methods may also be combined, for example, the absolute hearing threshold method and non-simultaneous masking are used together to determine the masked sub-band to be masked.

[0104] In this embodiment, a sound pressure model of an electroacoustic transducer is used to simulate and obtain a predicted sound pressure signal, and feature extraction processing is performed based on the sound pressure signal, i.e., simulating the heard sound pressure signal, rather than directly performing feature extraction processing on the audio signal. This improves the accuracy of the frequency division processing, and further improves the accuracy of the feature extraction processing, thereby improving the accuracy of determining the masked subband.

[0105] All of the above technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described in detail here.

[0106] In order to better implement the audio signal processing method of the present application embodiment, the present application embodiment also provides an audio signal processing device. Figure 6 , Figure 6 The audio signal processing device 300 may include a first acquisition module 301 , a backup module 302 , a sub-band determination module 303 , a masking module 304 and an output module 305 .

[0107] The first acquisition module 301 is used to acquire an audio signal.

[0108] The backup module 302 is used to back up the audio signal to obtain a first audio signal of a first branch and a second audio signal of a second branch.

[0109] The subband determination module 303 is configured to perform feature extraction processing on subband signals of multiple different subbands in the first audio signal in the time domain, and determine a masked subband to be masked from the multiple different subbands based on the processing result of the feature extraction processing.

[0110] In one embodiment, the subband determination module 303 includes a sound pressure determination module, a feature processing module and a masked subband determination module, wherein the sound pressure determination module is used to convert the audio signal into a voltage signal, and use the sound pressure model to process the voltage signal to obtain a predicted sound pressure signal; the feature processing module is used to perform feature extraction processing in the time domain on the subband signals of multiple different subbands in the sound pressure signal; the masked subband determination module is used to determine the masked subband in the sound pressure signal based on the processing result of the feature extraction processing. The processing result of the feature extraction processing includes the acoustic energy of multiple different subbands; the masked subband determination module is specifically used to determine the masked subband based on the psychoacoustic model and the acoustic energy of multiple different subbands.

[0111] The masking module 304 is configured to perform signal attenuation processing in the time domain on the second audio signal of the second branch based on the masking sub-band to obtain a target audio signal corresponding to the audio signal.

[0112] In one embodiment, the masking module 304 is further used to determine the attenuation parameter of the signal attenuator corresponding to each sub-band; when the masked sub-band identifier is obtained, the attenuation parameter of the signal attenuator corresponding to the masked sub-band is updated; when the masked sub-band identifier is not obtained, the attenuation parameter of the signal attenuator corresponding to the sub-band is kept unchanged; and the second audio signal of the second branch is subjected to signal attenuation processing in the time domain by using the corresponding signal attenuator to obtain a target audio signal corresponding to the audio signal.

[0113] The output module 305 is configured to output the target audio signal.

[0114] In one embodiment, the audio signal processing apparatus 300 may further include a first constructing module 306. The first constructing module 306 is configured to construct a sound pressure model of the electroacoustic transducer.

[0115] In one embodiment, the present application also provides an audio signal processing device. Figure 7 , Figure 7 The audio signal processing device 400 may include a second acquisition module 401 , a sound pressure determination module 402 , a feature processing module 403 , and a masked subband determination module 404 .

[0116] The second acquisition module 401 is used to acquire an audio signal and acquire a sound pressure model of an electroacoustic transducer that plays the audio signal.

[0117] The sound pressure determination module 402 is used to convert the audio signal into a voltage signal, and process the voltage signal using the sound pressure model to obtain a predicted sound pressure signal.

[0118] The feature processing module 403 is used to perform feature extraction processing in the time domain on sub-band signals of multiple different sub-bands in the sound pressure signal.

[0119] The masked subband determining module 404 is configured to determine a masked subband in the sound pressure signal from a plurality of different subbands based on the processing result of the feature extraction process.

[0120] In one embodiment, the audio signal processing device further includes a second construction module 405. The second construction module 405 is the same as the first construction module 306, and the second construction module 405 is used to construct a sound pressure model of the electroacoustic transducer.

[0121] All of the above technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described in detail here.

[0122] Accordingly, the embodiment of the present application also provides a computer device, which may be a terminal or a server. Figure 8 As shown, Figure 8 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. The computer device 500 includes a processor 501 having one or more processing cores, a memory 502 having one or more computer-readable storage media, and a computer program stored in the memory 502 and executable on the processor. The processor 501 is electrically connected to the memory 502. It will be understood by those skilled in the art that the computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0123] The processor 501 is the control center of the computer device 500. It uses various interfaces and lines to connect the various parts of the entire computer device 500, and executes various functions of the computer device 500 and processes data by running or loading software programs (computer programs) and / or modules stored in the memory 502, and calling data stored in the memory 502, thereby monitoring the computer device 500 as a whole.

[0124] In the embodiment of the present application, the processor 501 in the computer device 500 will load instructions corresponding to the processes of one or more application programs into the memory 502 according to the following steps, and the processor 501 will run the application programs stored in the memory 502 to implement various functions:

[0125] Acquire an audio signal and a sound pressure model of an electroacoustic transducer that plays the audio signal; convert the audio signal into a voltage signal, and process the voltage signal using the sound pressure model to obtain a predicted sound pressure signal; perform feature extraction processing on sub-band signals of multiple different sub-bands in the sound pressure signal in the time domain; determine a masked sub-band in the sound pressure signal from the multiple different sub-bands based on the processing result of the feature extraction processing; or,

[0126] An audio signal is acquired, and the audio signal is backed up to obtain a first audio signal of a first branch and a second audio signal of a second branch; a feature extraction process is performed on subband signals of a plurality of different subbands in the first audio signal in a time domain, and a masked masked subband is determined from the plurality of different subbands based on a processing result of the feature extraction process; based on the masked subband, a signal attenuation process is performed on the second audio signal of the second branch in a time domain to obtain a target audio signal corresponding to the audio signal; and the target audio signal is output.

[0127] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0128] Optional, such as Figure 8 As shown, the computer device 500 further includes: a touch screen 503, a radio frequency circuit 504, an audio circuit 505, an input unit 506, and a power supply 507. The processor 501 is electrically connected to the touch screen 503, the radio frequency circuit 504, the audio circuit 505, the input unit 506, and the power supply 507, respectively. Those skilled in the art can understand that Figure 8 The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0129] The touch display screen 503 can be used to display a graphical user interface and receive operation instructions generated by the user acting on the graphical user interface. The touch display screen 503 can include a display panel and a touch panel. Among them, the display panel can be used to display information input by the user or information provided to the user and various graphical user interfaces of the computer device, and these graphical user interfaces can be composed of graphics, text, icons, videos and any combination thereof. Optionally, the display panel can be configured in the form of a liquid crystal display (LCD, Liquid Crystal Display), an organic light-emitting diode (OLED, Organic Light-Emitting Diode) and the like. The touch panel can be used to collect the user's touch operation on or near it (such as the user uses any suitable object or attachment such as a finger, a stylus, etc. on the touch panel or near the touch panel), and generate corresponding operation instructions, and the operation instructions execute corresponding programs. The touch panel can cover the display panel, and when the touch panel detects a touch operation on or near it, it is transmitted to the processor 501 to determine the type of the touch event, and then the processor 501 provides corresponding visual output on the display panel according to the type of the touch event. In the embodiment of the present application, the touch panel and the display panel can be integrated into the touch display screen 503 to realize the input and output functions. However, in some embodiments, the touch panel and the display panel can be used as two independent components to realize the input and output functions. That is, the touch display screen 503 can also be used as a part of the input unit 506 to realize the input function.

[0130] In the embodiment of the present application, the touch display screen 503 is used to present a graphical user interface and receive operation instructions generated by a user acting on the graphical user interface.

[0131] The radio frequency circuit 504 may be used to send and receive radio frequency signals, so as to establish wireless communication with a network device or other computer devices through wireless communication, and to send and receive signals between the network device or other computer devices.

[0132] The audio circuit 505 can be used to provide an audio interface between the user and the computer device through an electroacoustic transducer and a microphone. The audio circuit 505 can transmit the electrical signal converted from the received audio data to the electroacoustic transducer, which is converted into a sound signal for output; on the other hand, the microphone converts the collected sound signal into an electrical signal, which is received by the audio circuit 505 and converted into audio data, and then the audio data is output to the processor 501 for processing, and then sent to another computer device through the radio frequency circuit 504, or the audio data is output to the memory 502 for further processing. The audio circuit 505 may also include an earplug jack to provide communication between an external headset and a computer device. Among them, the audio circuit 505 also includes multiple filters.

[0133] The input unit 506 may be used to receive input numbers, character information or user feature information (such as fingerprint, iris, facial information, etc.), and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0134] The power supply 507 is used to supply power to various components of the computer device 500. Optionally, the power supply 507 can be logically connected to the processor 501 through a power management system, so that the power management system can manage charging, discharging, and power consumption. The power supply 507 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0135] In one embodiment, although Figure 8 Not shown, the computer device 500 may also include a camera, a sensor, a wireless fidelity module, a Bluetooth module, etc., which will not be described in detail here.

[0136] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0137] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0138] To this end, an embodiment of the present application provides a computer-readable storage medium, in which multiple computer programs are stored, and the computer program can be loaded by a processor to execute the steps in any audio signal processing method provided in the embodiment of the present application. For example, the computer program can execute the following steps:

[0139] Acquire an audio signal and a sound pressure model of an electroacoustic transducer that plays the audio signal; convert the audio signal into a voltage signal, and process the voltage signal using the sound pressure model to obtain a predicted sound pressure signal; perform feature extraction processing on sub-band signals of multiple different sub-bands in the sound pressure signal in the time domain; determine a masked sub-band in the sound pressure signal from the multiple different sub-bands based on the processing result of the feature extraction processing; or,

[0140] An audio signal is acquired, and the audio signal is backed up to obtain a first audio signal of a first branch and a second audio signal of a second branch; a feature extraction process is performed on subband signals of a plurality of different subbands in the first audio signal in a time domain, and a masked masked subband is determined from the plurality of different subbands based on a processing result of the feature extraction process; based on the masked subband, a signal attenuation process is performed on the second audio signal of the second branch in a time domain to obtain a target audio signal corresponding to the audio signal; and the target audio signal is output.

[0141] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0142] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0143] Since the computer program stored in the storage medium can execute the steps in any audio signal processing method provided in the embodiments of the present application, the beneficial effects that can be achieved by any audio signal processing method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0144] The above is a detailed introduction to an audio signal processing method, device, storage medium and computer device provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An audio signal processing method, characterized in that: include: Acquire an audio signal, and back up the audio signal to obtain a first audio signal of a first branch and a second audio signal of a second branch; performing feature extraction processing in the time domain on subband signals of a plurality of different subbands in the first audio signal, and determining a masked subband to be masked from the plurality of different subbands based on a processing result of the feature extraction processing; Based on the masking subband, performing signal attenuation processing in the time domain on the second audio signal of the second branch to obtain a target audio signal corresponding to the audio signal; The target audio signal is output.

2. The method according to claim 1, characterized in that The method further comprises: Acquiring a sound pressure model of an electroacoustic transducer that plays the audio signal; The step of performing feature extraction processing in the time domain on sub-band signals of a plurality of different sub-bands in the first audio signal comprises: Converting the first audio signal into a voltage signal, and processing the voltage signal using the sound pressure model to obtain a predicted sound pressure signal; A feature extraction process in the time domain is performed on sub-band signals of a plurality of different sub-bands in the sound pressure signal.

3. An audio signal processing method, characterized in that: include: Acquiring an audio signal and acquiring a sound pressure model of an electroacoustic transducer that plays the audio signal; Converting the audio signal into a voltage signal, and processing the voltage signal using the sound pressure model to obtain a predicted sound pressure signal; Performing feature extraction processing in the time domain on sub-band signals of a plurality of different sub-bands in the sound pressure signal; A masked subband in the sound pressure signal is determined from a plurality of different subbands based on a processing result of the feature extraction processing.

4. The method according to claim 2 or 3, characterized in that: The step of performing feature extraction processing in the time domain on sub-band signals of multiple different sub-bands in the sound pressure signal comprises: The sound pressure signal is subjected to time domain filtering by a plurality of first filtering units to obtain a plurality of sub-band signals corresponding to the sound pressure signal; The multiple sub-band signals are respectively subjected to acoustic energy processing.

5. The method according to claim 2 or 3, characterized in that: Before the step of obtaining the sound pressure model of the electroacoustic transducer that plays the audio signal, the method further includes: For each frequency band in the multiple frequency bands corresponding to the existing audio signal, providing a test voltage signal for each frequency band; Processing the test voltage signal using the electroacoustic transducer, and measuring a first test sound pressure signal output by the electroacoustic transducer at a preset distance; A sound pressure model of the electroacoustic transducer at a preset distance is constructed according to the test voltage signal and the first test sound pressure signal.

6. The method according to claim 5, characterized in that Also includes: Obtain different distances for receiving the test sound pressure signal; Processing the test voltage signal using the electroacoustic transducer and determining a second test sound pressure signal output by the electroacoustic transducer at different distances; The sound pressure model is updated according to the test voltage signal and the second test sound pressure signal to obtain the sound pressure models of the electroacoustic transducer at different distances.

7. The method according to claim 1, characterized in that The masked subband includes a masked subband identifier, and each subband in a plurality of different subbands corresponds to a signal attenuator; the method further includes: Determine an attenuation parameter of a signal attenuator corresponding to each sub-band; The step of performing signal attenuation processing in the time domain on the second audio signal of the second branch based on the masked subband to obtain a target audio signal corresponding to the audio signal includes: When the masked sub-band identifier is obtained, the attenuation parameter of the signal attenuator corresponding to the masked sub-band is updated; when the masked sub-band identifier is not obtained, the attenuation parameter of the signal attenuator corresponding to the sub-band is kept unchanged; The second audio signal of the second branch is subjected to signal attenuation processing in the time domain by using a corresponding signal attenuator to obtain a target audio signal corresponding to the audio signal.

8. The method according to claim 7, characterized in that Before the step of determining the attenuation parameter of the signal attenuator corresponding to each sub-band, the method further includes: Obtain the center frequency and bandwidth of the critical sub-band of each sub-band; The characteristic parameters of the signal attenuator corresponding to each sub-band are determined according to the center frequency and the bandwidth.

9. The method according to claim 7, characterized in that: The signal attenuator is a second filtering unit, and the determined attenuation parameter is an initial gain of the second filtering unit; The step of updating the attenuation parameter of the signal attenuator corresponding to the masked subband includes: reducing the initial gain of the second filter unit corresponding to the masked subband to a target gain, wherein the target gain is a preset gain or gain data determined according to the acoustic energy of the masked subband; The step of performing signal attenuation processing in the time domain on the second audio signal of the second branch using the corresponding signal attenuator includes: performing first signal filtering processing in the time domain on the second audio signal using the target gain of the second filtering unit corresponding to the masked subband and the initial gain of the second filtering unit corresponding to the unmasked subband.

10. The method according to claim 7, characterized in that The signal attenuator is a multi-segment dynamic range control, and the determined attenuation parameter is an initial control threshold of the multi-segment dynamic range control; The step of updating the attenuation parameter of the signal attenuator corresponding to the masked subband comprises: Adjusting a control threshold of a multi-segment dynamic range control corresponding to the masked subband from an initial control threshold to a target control threshold, where the target control threshold is a preset control threshold or a control threshold determined according to the acoustic energy of the masked subband; The step of performing signal attenuation processing in the time domain on the second audio signal of the second branch using the corresponding signal attenuator includes: performing second signal filtering processing in the time domain on the second audio signal using the target control threshold of the multi-band dynamic range control of the masked subband and the initial control threshold of the multi-band dynamic range control of the unmasked subband.

11. The method according to claim 1, characterized in that: The processing result of the feature extraction process includes acoustic energy of a plurality of different sub-bands; The step of determining the masked masked subband from the multiple different subbands based on the processing result of the feature extraction processing includes: determining the masked masked subband from the multiple different subbands based on the psychoacoustic model and the acoustic energy of the multiple different subbands.

12. An audio signal processing device, characterized in that: include: A first acquisition module, used to acquire an audio signal; A backup module, used for backing up the audio signal to obtain a first audio signal of a first branch and a second audio signal of a second branch; a sub-band determination module, configured to perform feature extraction processing on sub-band signals of a plurality of different sub-bands in the first audio signal in a time domain, and determine a masked sub-band to be masked from the plurality of different sub-bands based on a processing result of the feature extraction processing; a masking module, configured to perform signal attenuation processing in the time domain on the second audio signal of the second branch based on the masking sub-band, so as to obtain a target audio signal corresponding to the audio signal; An output module is used to output the target audio signal.

13. An audio signal processing device, characterized in that: include: A second acquisition module, used to acquire an audio signal and a sound pressure model of an electroacoustic transducer that plays the audio signal; a sound pressure determination module, configured to convert the audio signal into a voltage signal, and process the voltage signal using the sound pressure model to obtain a predicted sound pressure signal; A feature processing module, used for performing feature extraction processing in the time domain on sub-band signals of multiple different sub-bands in the sound pressure signal; The masked subband determining module is used to determine the masked subband in the sound pressure signal from a plurality of different subbands based on the processing result of the feature extraction processing.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor to execute the steps in the audio signal processing method according to any one of claims 1 to 11.

15. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and the processor executes the steps in the audio signal processing method according to any one of claims 1 to 11 by calling the computer program stored in the memory.

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