WO2021248521A1 - Audio signal adjustment method and apparatus, computer device, and storage medium - Google Patents
Audio signal adjustment method and apparatus, computer device, and storage medium Download PDFInfo
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- WO2021248521A1 WO2021248521A1 PCT/CN2020/096684 CN2020096684W WO2021248521A1 WO 2021248521 A1 WO2021248521 A1 WO 2021248521A1 CN 2020096684 W CN2020096684 W CN 2020096684W WO 2021248521 A1 WO2021248521 A1 WO 2021248521A1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R3/00—Circuits for transducers, loudspeakers or microphones
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R29/00—Monitoring arrangements; Testing arrangements
- H04R29/001—Monitoring arrangements; Testing arrangements for loudspeakers
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R2203/00—Details of circuits for transducers, loudspeakers or microphones covered by H04R3/00 but not provided for in any of its subgroups
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R2430/00—Signal processing covered by H04R, not provided for in its groups
Definitions
- This application relates to the field of computer technology, and in particular to an audio signal adjustment method, device, computer equipment, and storage medium.
- the internal structure of the micro-speaker cavity is complicated and the space is small.
- the airflow turbulence caused by the vibration of the diaphragm can cause "sand” and "hissing" noise at certain frequencies. This situation is particularly serious when playing music under high voltage.
- the commonly used audio signal adjustment method is partially solved by improving the structure of the speaker cavity or the internal material, but this method has a higher process cost, a longer period, and limited versatility.
- the dynamic range compression technology is used to control the excitation voltage to avoid airflow noise under excessively high voltage values. But this method can easily cause the sound to be loud and small, which affects the auditory perception. In view of this, there is an urgent need to provide a new audio signal adjustment method.
- the present application provides an audio signal adjustment method, device, computer equipment, and storage medium, which are used to solve the problems of poor audio signal adjustment effect and low adjustment freedom in the prior art.
- an embodiment of the present application provides an audio signal adjustment method, and a micro speaker includes:
- An equalizer algorithm is used to adjust the excitation signal according to the target adjustment gain to obtain a target audio signal.
- an embodiment of the present application also provides an audio signal adjustment device, the device including:
- An amplitude prediction module for obtaining an excitation signal to be input to the micro speaker, and predicting the vibration amplitude of the diaphragm generated when the excitation signal is input to the micro speaker;
- a judging module for judging whether the amplitude of the diaphragm exceeds a preset amplitude threshold
- a gain determination module configured to determine that the vibration diaphragm amplitude of the excitation signal is reduced to be less than the preset amplitude according to the vibration diaphragm amplitude and the preset amplitude threshold value when the vibration diaphragm amplitude exceeds the preset amplitude threshold value Target adjustment gain at threshold;
- the signal adjustment module is used to adjust the excitation signal according to the target adjustment gain by using an equalizer algorithm to obtain a target audio signal.
- the embodiments of the present application also provide a computer device, including a memory, a processor, and a computer program stored on the memory and running on the processor.
- a computer program stored on the memory and running on the processor.
- an embodiment of the present application also provides a computer-readable storage medium, including computer instructions, which when run on a computer, cause the computer to execute the steps of the audio signal adjustment method described above.
- the excitation signal After adopting the above audio signal adjustment method, device, computer equipment and storage medium, the excitation signal obtains the excitation signal to be input into the micro speaker, and calculates the diaphragm amplitude of the excitation signal; judges whether the diaphragm amplitude exceeds a preset Amplitude threshold; when the amplitude of the diaphragm exceeds the preset amplitude threshold, the excitation signal determines the target adjustment gain of the excitation signal according to the diaphragm amplitude and the preset amplitude threshold; the equalizer algorithm is used according to the target The gain is adjusted to adjust the excitation signal to obtain the target audio signal.
- the adjustment of the audio signal is realized by adopting the dynamic equalizer algorithm, and when adjusting the audio signal, since only the audio signal of the narrow frequency band that will produce airflow noise is processed, the overall volume is limited, so as to avoid sudden loudness to the greatest extent The phenomenon of sudden smallness is subjectively perceived, and at the same time, since the audio signal adjustment is determined according to the preset threshold value, the degree of freedom of audio signal adjustment is improved.
- FIG. 1 is a schematic flowchart of the audio signal adjustment method in an embodiment
- FIG. 2 is a schematic flowchart of the method for predicting the amplitude of the diaphragm in an embodiment
- FIG. 3 is a schematic flowchart of the method for predicting the amplitude of the diaphragm in another embodiment
- FIG. 4 is a schematic flowchart of the method for determining the target adjustment gain in an embodiment
- FIG. 5 is a schematic flowchart of the method for determining the target adjustment gain in another embodiment
- FIG. 6 is a schematic flowchart of the audio signal adjustment method in another embodiment
- FIG. 7 is a schematic diagram of the structure of the audio signal adjusting device in an embodiment
- FIG. 8 is a schematic diagram of the internal structure of a computer device running the above audio signal adjustment method in an embodiment.
- the speaker cavity structure or internal material is improved, or the dynamic range compression technology is used to control the excitation voltage, to avoid airflow noise under excessively high voltage values, and the resulting audio signal is poorly adjusted, and the vertical and horizontal freedom is improved.
- the problem is not high.
- an audio signal adjustment method is specially proposed.
- the realization of the method can rely on a computer program, which can run on a computer system based on the von Neumann system.
- the audio signal adjustment method provided in this embodiment is applied to a micro speaker, and the audio signal adjustment method specifically includes the following steps:
- Step 102 Obtain an excitation signal to be input to the micro speaker, and predict the vibration amplitude of the diaphragm generated by the excitation signal input to the micro speaker.
- the excitation signal refers to the signal excitation source that is the music file (such as a song) played during the test, and the played audio signal is the input signal corresponding to the audio signal recorded by the microphone.
- the signal excitation source can be determined in advance from the server, and the audio signal generated by the analog signal excitation source input into the micro speaker is used as the excitation signal.
- the diaphragm amplitude is the index data used to reflect the intensity of the airflow noise generated by the excitation signal. The larger the vibration diaphragm amplitude, the greater the intensity of the airflow noise generated by the excitation signal.
- the amplitude of the diaphragm generated by the excitation signal input to the micro-speaker can be predicted by the speaker model, or the diaphragm amplitude generated by the input of the excitation signal into the micro-speaker can be predicted by a predictive model based on machine learning.
- Step 104 Determine whether the amplitude of the diaphragm exceeds a preset amplitude threshold.
- the preset amplitude threshold refers to a preset threshold value of the diaphragm amplitude of the excitation signal used to determine whether airflow noise is generated.
- the preset amplitude threshold can be determined by listening test combined with experimental measurement, that is, the lowest diaphragm amplitude of the airflow noise experienced by listening is set to the preset amplitude threshold, or it can pass a large-scale test by referring to the machine learning algorithm , Such as hidden Markov model, neural network, etc., determine the probability of airflow noise at different frequencies and different diaphragm amplitudes, dynamically change the amplitude threshold according to the probability of airflow noise, and set the diaphragm amplitude when the probability exceeds a specific value as the amplitude threshold Exemplarily, the probability value is 75%. When the preset amplitude threshold is set according to the probability, the greater the probability, the greater the risk of airflow noise. When the preset amplitude threshold is set to a smaller value, the airflow can be
- the amplitude threshold can be dynamically changed according to the probability of occurrence of airflow noise, so that subsequent dynamic audio signal adjustments can be dynamically performed, and the accuracy and freedom of audio signal adjustments can be improved.
- Step 106 When the diaphragm amplitude exceeds the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold.
- the target adjustment gain refers to the magnification required for the diaphragm amplitude when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold.
- the target adjustment gain at this time is a/A. It is understandable that when the diaphragm amplitude exceeds the preset amplitude threshold, airflow noise will appear when the excitation signal is input to the micro-speaker.
- the diaphragm amplitude of the excitation signal needs to be reduced to It is less than the preset amplitude threshold. Therefore, it is necessary to determine the corresponding target adjustment gain, so that the diaphragm amplitude of the excitation signal is determined to be accurately adjusted before the micro-speaker plays the excitation signal, so as to avoid the appearance of airflow noise.
- Step 108 Use the equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain the target audio signal.
- the equalizer algorithm is a way to divide the frequency domain into frequency bands (such as dividing into 5, 10, 12, and 15 frequency bands) and apply corresponding gains to different frequency bands to change the frequency domain energy distribution of the original data.
- An audio signal processing method that changes the subjective sense of hearing.
- the target audio signal refers to an audio signal in which air noise is hardly felt in the sense of hearing.
- the equalizer in this embodiment is a parametric equalizer and a time domain equalizer.
- the equalizer is at 20 ⁇ 20K
- the Hz frequency range is divided into 5, 10, 15, 20 or 30 frequency bands, and a gain corresponding to the target adjustment gain is applied to this frequency band to realize the adjustment of the excitation signal, and the adjusted excitation signal is input to the micro speaker, Play the target audio signal through the micro speaker.
- the diaphragm amplitude of the excitation signal whose diaphragm amplitude exceeds the preset amplitude threshold is not adjusted. Adjustment, that is, only process the excitation signal in a narrow frequency band that will produce airflow noise, and has a limited impact on the overall volume. Therefore, it can avoid the subjective perception of the fluctuations of large and small phenomena to the greatest extent. Improve the effect and efficiency of audio signal adjustment.
- the preset diaphragm amplitude in this embodiment is determined dynamically, the adjustment of the excitation signal is also dynamically adjusted through the dynamic equalizer to obtain the target audio signal, thereby increasing the degree of freedom of audio signal adjustment.
- the audio signal adjustment method described above obtains the excitation signal to be input to the micro speaker, and predicts the vibration amplitude of the diaphragm generated by the excitation signal input to the micro speaker; determines whether the diaphragm amplitude exceeds the preset amplitude threshold; when the diaphragm amplitude exceeds the preset amplitude threshold, According to the diaphragm amplitude and the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; use the equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain the target audio signal to avoid In order to avoid airflow noise in the target audio signal, the audio signal is adjusted by adopting a dynamic equalizer algorithm.
- predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes:
- Step 102A Extract audio parameters of the excitation signal
- Step 102B Input the audio parameters into the preset loudspeaker model for prediction, and obtain the diaphragm amplitude.
- the audio parameters refer to signal parameters related to the diaphragm amplitude in the excitation signal, such as frequency, diaphragm velocity, or diaphragm acceleration.
- the audio parameters of the excitation signal can be extracted through a signal source and a signal analysis system. Then, the audio parameters are input into the preset speaker model, and the audio parameters are directly calculated through the preset speaker model, and the diaphragm amplitude is directly calculated. Understandably, by adopting the preset loudspeaker model, the diaphragm amplitude of the excitation signal can be easily and quickly predicted.
- predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes:
- Step 102C Extract audio parameters of the excitation signal
- Step 102D Obtain the diaphragm amplitude according to the preset amplitude prediction model trained based on the machine learning algorithm and according to the audio parameters.
- the audio parameters are consistent with the audio parameters in step 102A, and will not be repeated here.
- the amplitude prediction model is based on preset machine learning algorithms, such as hidden Markov models, neural networks, etc. This algorithm establishes the relationship between the audio parameters and the amplitude of the diaphragm, and uses the audio parameters as the input of the amplitude prediction model.
- the output of the amplitude prediction model is the diaphragm amplitude of the excitation signal.
- determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes:
- Step 106A Determine the target amplitude according to the diaphragm amplitude and the preset amplitude threshold, and the target amplitude is less than the preset amplitude threshold;
- Step 106B Determine the target adjustment gain corresponding to the target amplitude through the built-in gain curve in the preset loudspeaker model.
- the target amplitude refers to the diaphragm amplitude of the excitation signal that can avoid the occurrence of airflow noise, and the target amplitude is less than a preset amplitude threshold.
- the corresponding correction value may be determined in advance according to the diaphragm amplitude of the excitation signal, and then the difference between the preset amplitude threshold and the correction value may be determined as the target amplitude.
- the built-in gain curve in the preset loudspeaker model refers to the preset curve used to describe the change of the relationship between the amplitude of the diaphragm and the gain. In the gain curve, finding the gain corresponding to the target amplitude is the target adjustment gain.
- determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes:
- Step 106C Determine the target amplitude according to the diaphragm amplitude and the preset amplitude threshold, where the target amplitude is less than the preset amplitude threshold;
- Step 106D Obtain the target adjustment gain through a preset gain calculation model based on machine learning and calculation according to the target amplitude.
- the target amplitude in this embodiment is consistent with the target amplitude in step 106A, and will not be repeated here.
- the gain calculation model is based on a preset machine learning algorithm, such as hidden Markov model, neural network, etc. This algorithm establishes the relationship between the gain and the amplitude of the diaphragm, and uses the target amplitude as the input of the gain calculation model.
- the calculated model output is the target adjustment gain.
- using an equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain the target audio signal includes:
- Step 108A Obtain multiple filters and corresponding frequencies and energy included in the equalizer algorithm
- Step 108B Calculate the quality factor of each filter according to the frequency and energy of each filter stage and the target adjustment gain;
- Step 108C Filter the excitation signal according to the quality factor of each filter to obtain the target audio signal.
- the quality factor refers to the ratio of the mode of the gain corresponding to the cut-off frequency to the mode of the pass-band gain, which is used to reflect the shape of the amplitude-frequency characteristics of the low-pass filter at the cut-off frequency.
- the larger the quality factor the narrower the filtering frequency band, and the better the filtering effect within the frequency band.
- the built-in algorithm for dynamically determining Q is an algorithm based on a speaker model or an algorithm based on a statistical model. According to the frequency, energy and gain, the corresponding quality factor can be calculated. According to the quality factor of each filter, the excitation signal is filtered to obtain the target audio signal, which realizes the narrow frequency band that generates airflow noise in the excitation signal. The excitation signal is filtered to realize the adjustment of the audio signal, and has a limited impact on the overall volume. It avoids the subjective perception of the fluctuation of the audio signal to the greatest extent, and improves the effect and efficiency of audio signal adjustment. And because the excitation signal is dynamically filtered according to the quality factor of each filter, the freedom of adjusting the audio signal is improved.
- the filter is an IIR filter or FIR filter.
- the IIR filter is an infinite impulse response filter
- the FIR filter is a finite impulse response filter.
- the excitation signal is processed by the filter as an IIR filter or an FIR filter, and the time domain characteristics of the excitation signal can be obtained, thereby improving the real-time performance of audio signal adjustment.
- the order of the filter in this embodiment does not exceed 6 orders, thereby saving costs on the basis of ensuring the adjustment effect.
- an embodiment of the application provides an audio signal adjustment device 700, as shown in FIG. 7, including: an amplitude prediction module 702, configured to obtain an excitation signal to be input to the micro speaker, and predict the excitation signal Input the diaphragm amplitude generated by the micro-speaker; the determining module 704 is used to determine whether the amplitude of the diaphragm exceeds the preset amplitude threshold; the gain determining module 706 is used to when the amplitude of the diaphragm exceeds the preset amplitude threshold, According to the diaphragm amplitude and the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; the signal adjustment module 708 is configured to use an equalizer algorithm according to The target adjustment gain adjusts the excitation signal to obtain a target audio signal.
- an amplitude prediction module 702 configured to obtain an excitation signal to be input to the micro speaker, and predict the excitation signal Input
- the audio signal adjustment device 700 of this embodiment includes: an amplitude prediction module 702, configured to obtain an excitation signal to be input to the micro speaker, and predict that the excitation signal is input to the micro speaker Generated vibration diaphragm amplitude; judging module 704, used to determine whether the vibration diaphragm amplitude exceeds a preset amplitude threshold; gain determination module 706, when the vibration diaphragm amplitude exceeds the preset amplitude threshold, according to the diaphragm The amplitude and the preset amplitude threshold are used to determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; the signal adjustment module 708 is configured to adjust the gain according to the target by using an equalizer algorithm The excitation signal is adjusted to obtain the target audio signal.
- an amplitude prediction module 702 configured to obtain an excitation signal to be input to the micro speaker, and predict that the excitation signal is input to the micro speaker Generated vibration diaphragm ampli
- Fig. 8 shows an internal structure diagram of a computer device in an embodiment.
- the computer device may specifically be a server or a terminal.
- the computer device 800 includes a processor 810, a memory 820, and a network interface 830 connected through a system bus.
- the memory 820 includes a non-volatile storage medium and an internal memory.
- the non-volatile storage medium of the computer device stores an operating system, and may also store a computer program.
- the processor can implement the audio signal adjustment method.
- a computer program may also be stored in the internal memory, and when the computer program is executed by the processor, the processor can execute the audio signal adjustment method.
- FIG. 8 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied.
- the specific computer device may Including more or fewer components than shown in FIG. 8, or combining certain components, or having a different component arrangement.
- the audio signal adjustment method provided in the present application can be implemented in the form of a computer program, and the computer program can be run on a computer device as shown in FIG. 8.
- the memory of the computer device can store various program modules that make up the audio signal adjustment device. For example, the amplitude prediction module 702, the judgment module 704, the gain determination module 706, and the signal adjustment module 708.
- a computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the following steps: Obtain an excitation signal to be input to the micro speaker , And predict the diaphragm amplitude generated by the excitation signal input to the micro speaker; determine whether the diaphragm amplitude exceeds a preset amplitude threshold; when the diaphragm amplitude exceeds the preset amplitude threshold, according to the diaphragm amplitude And the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; adjust the excitation signal according to the target adjustment gain by using an equalizer algorithm, Obtain the target audio signal.
- predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes: extracting audio parameters of the excitation signal; inputting the audio parameters into a preset speaker model for prediction, and obtaining The amplitude of the diaphragm.
- predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes: extracting the audio parameters of the excitation signal; using a preset amplitude prediction model trained based on a machine learning algorithm and according to the The audio parameter is used to obtain the vibration diaphragm amplitude.
- determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes: according to the vibration The film amplitude and the preset amplitude threshold determine a target amplitude, and the target amplitude is less than the preset amplitude threshold; the target adjustment gain corresponding to the target amplitude is determined through a gain curve built into the preset speaker model.
- determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes: according to the vibration The film amplitude and the preset amplitude threshold determine a target amplitude, and the target amplitude is less than the preset amplitude threshold; the target adjustment gain is calculated by a preset gain calculation model based on machine learning and calculated according to the target amplitude.
- using an equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain a target audio signal includes: obtaining multiple filters included in the equalizer algorithm and corresponding frequencies and energy Calculate the quality factor of each filter according to the frequency and energy of each filter stage and the target adjustment gain; filter the excitation signal according to the quality factor of each filter to obtain the target audio signal.
- the filter is an IIR filter or FIR filter.
- a computer-readable storage medium wherein the computer-readable storage medium stores a computer program, and the computer program is characterized in that, when the computer program is executed by a processor, the following steps are implemented: obtaining an excitation signal to be input to the micro-speaker, and predicting The excitation signal is input to the diaphragm amplitude generated by the micro-speaker; it is determined whether the diaphragm amplitude exceeds a preset amplitude threshold; when the diaphragm amplitude exceeds the preset amplitude threshold, according to the diaphragm amplitude and the The preset amplitude threshold is used to determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; the equalizer algorithm is used to adjust the excitation signal according to the target adjustment gain to obtain the target audio Signal.
- predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes: extracting audio parameters of the excitation signal; inputting the audio parameters into a preset speaker model for prediction, and obtaining The amplitude of the diaphragm.
- predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes: extracting the audio parameters of the excitation signal; using a preset amplitude prediction model trained based on a machine learning algorithm and according to the The audio parameter is used to obtain the vibration diaphragm amplitude.
- determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes: according to the vibration The film amplitude and the preset amplitude threshold determine a target amplitude, and the target amplitude is less than the preset amplitude threshold; the target adjustment gain corresponding to the target amplitude is determined through a gain curve built into the preset speaker model.
- determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes: according to the vibration The film amplitude and the preset amplitude threshold determine a target amplitude, and the target amplitude is less than the preset amplitude threshold; the target adjustment gain is calculated by a preset gain calculation model based on machine learning and calculated according to the target amplitude.
- using an equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain a target audio signal includes: obtaining multiple filters included in the equalizer algorithm and corresponding frequencies and energy Calculate the quality factor of each filter according to the frequency and energy of each filter stage and the target adjustment gain; filter the excitation signal according to the quality factor of each filter to obtain the target audio signal.
- the filter is an IIR filter or FIR filter.
- Non-volatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
- Volatile memory may include random access memory (RAM) or external cache memory.
- RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Channel (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
- SRAM static RAM
- DRAM dynamic RAM
- SDRAM synchronous DRAM
- DDRSDRAM double data rate SDRAM
- ESDRAM enhanced SDRAM
- SLDRAM synchronous chain Channel
- memory bus Radbus direct RAM
- RDRAM direct memory bus dynamic RAM
- RDRAM memory bus dynamic RAM
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Abstract
Disclosed in embodiments of the present application is an audio signal adjustment method, comprising: acquiring an excitation signal to be input to a micro speaker, and predicting a diaphragm amplitude produced when the excitation signal is input to the micro speaker; determining whether the diaphragm amplitude exceeds a preset amplitude threshold; if the diaphragm amplitude exceeds the preset amplitude threshold, determining, according to the diaphragm amplitude and the preset amplitude threshold, a target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; and using an equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain a target audio signal, thereby avoiding airflow noise in the target audio signal, and preventing the subjective perception of fluctuations in loudness, thus increasing the degree of freedom of audio signal adjustment and improving the effect and efficiency of audio signal adjustment. In addition, also provided are an audio signal adjustment apparatus, a computer device, and a storage medium.
Description
本申请涉及计算机技术领域,尤其涉及一种音频信号调整方法、装置、计算机设备及存储介质。This application relates to the field of computer technology, and in particular to an audio signal adjustment method, device, computer equipment, and storage medium.
微型扬声器腔体内部结构复杂、空间狭小,振膜振动造成的气流湍流在某些频率下导致“沙沙”、“嘶嘶”的噪声,这种情况在大电压下播放音乐时显得尤为严重。The internal structure of the micro-speaker cavity is complicated and the space is small. The airflow turbulence caused by the vibration of the diaphragm can cause "sand" and "hissing" noise at certain frequencies. This situation is particularly serious when playing music under high voltage.
目前常用的音频信号调整方法,一方面是通过对扬声器腔体结构或内部材质进行改进部分解决,但这种方法工艺成本较高、周期较长,且通用性受到限制。另一方面是采用动态范围压缩技术来控制激励电压,避免过高电压值下出现气流杂音。但这种方法容易导致声音忽大忽小,影响听觉感受。鉴于此,亟需提供一种新的音频信号调整方法。At present, the commonly used audio signal adjustment method is partially solved by improving the structure of the speaker cavity or the internal material, but this method has a higher process cost, a longer period, and limited versatility. On the other hand, the dynamic range compression technology is used to control the excitation voltage to avoid airflow noise under excessively high voltage values. But this method can easily cause the sound to be loud and small, which affects the auditory perception. In view of this, there is an urgent need to provide a new audio signal adjustment method.
有鉴于此,本申请提供了一种音频信号调整方法、装置、计算机设备及存储介质,用于解决现有技术中音频信号调整效果不佳以及调整自由度不高的问题。In view of this, the present application provides an audio signal adjustment method, device, computer equipment, and storage medium, which are used to solve the problems of poor audio signal adjustment effect and low adjustment freedom in the prior art.
本申请实施例的具体技术方案为:The specific technical solutions of the embodiments of this application are:
第一方面,本申请实施例提供一种音频信号调整方法,微型扬声器,包括:In a first aspect, an embodiment of the present application provides an audio signal adjustment method, and a micro speaker includes:
获取待输入所述微型扬声器的激励信号,并预测所述激励信号输入所述微型扬声器产生的振膜振幅;Acquiring an excitation signal to be input to the micro speaker, and predicting the vibration amplitude of the diaphragm generated when the excitation signal is input to the micro speaker;
判断所述振膜振幅是否超过预设振幅阈值;Judging whether the amplitude of the diaphragm exceeds a preset amplitude threshold;
当所述振膜振幅超过预设振幅阈值时,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益;When the amplitude of the diaphragm exceeds the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold ;
利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。An equalizer algorithm is used to adjust the excitation signal according to the target adjustment gain to obtain a target audio signal.
第二方面,本申请实施例还提供一种音频信号调整装置,所述装置包括:In a second aspect, an embodiment of the present application also provides an audio signal adjustment device, the device including:
振幅预测模块,用于获取待输入所述微型扬声器的激励信号,并预测所述激励信号输入所述微型扬声器产生的振膜振幅;An amplitude prediction module for obtaining an excitation signal to be input to the micro speaker, and predicting the vibration amplitude of the diaphragm generated when the excitation signal is input to the micro speaker;
判断模块,用于判断所述振膜振幅是否超过预设振幅阈值;A judging module for judging whether the amplitude of the diaphragm exceeds a preset amplitude threshold;
增益确定模块,用于当所述振膜振幅超过预设振幅阈值时,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益;A gain determination module, configured to determine that the vibration diaphragm amplitude of the excitation signal is reduced to be less than the preset amplitude according to the vibration diaphragm amplitude and the preset amplitude threshold value when the vibration diaphragm amplitude exceeds the preset amplitude threshold value Target adjustment gain at threshold;
信号调整模块,用于利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。The signal adjustment module is used to adjust the excitation signal according to the target adjustment gain by using an equalizer algorithm to obtain a target audio signal.
第三方面,本申请实施例还提供一种计算机设备,包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序,所述处理器执行所述计算机程序时实现如上所述音频信号调整方法的步骤。In the third aspect, the embodiments of the present application also provide a computer device, including a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, The steps of the audio signal adjustment method described above are implemented.
第四方面,本申请实施例还提供一种计算机可读存储介质,包括计算机指令,当所述计算机指令在计算机上运行时,使得计算机执行如上所述音频信号调整方法的步骤。In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium, including computer instructions, which when run on a computer, cause the computer to execute the steps of the audio signal adjustment method described above.
实施本申请实施例,将具有如下有益效果:Implementing the embodiments of this application will have the following beneficial effects:
采用了上述音频信号调整方法、装置、计算机设备及存储介质之后,激励信号获取待输入微型扬声器中的激励信号,并计算所述激励信号的振膜振幅;判断所述振膜振幅是否超过预设振幅阈值;当所述振膜振幅超过预设振幅阈值时,激励信号则根据所述振膜振幅和所述预设振幅阈值确定所述激励信号的目标调整增益;利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。通过采用动态均衡器算法实现了对音频信号的调整,并且在调整音频信号时,由于只针对会产生气流噪声的窄频段的音频信号进行处理,对总体音量影响有限,从而最大程度的避免忽大忽小的现象被主观感知到,同时,由于根据预设阈值确定是否进行音频信号调整,提高了音频信号调整的自由度。After adopting the above audio signal adjustment method, device, computer equipment and storage medium, the excitation signal obtains the excitation signal to be input into the micro speaker, and calculates the diaphragm amplitude of the excitation signal; judges whether the diaphragm amplitude exceeds a preset Amplitude threshold; when the amplitude of the diaphragm exceeds the preset amplitude threshold, the excitation signal determines the target adjustment gain of the excitation signal according to the diaphragm amplitude and the preset amplitude threshold; the equalizer algorithm is used according to the target The gain is adjusted to adjust the excitation signal to obtain the target audio signal. The adjustment of the audio signal is realized by adopting the dynamic equalizer algorithm, and when adjusting the audio signal, since only the audio signal of the narrow frequency band that will produce airflow noise is processed, the overall volume is limited, so as to avoid sudden loudness to the greatest extent The phenomenon of sudden smallness is subjectively perceived, and at the same time, since the audio signal adjustment is determined according to the preset threshold value, the degree of freedom of audio signal adjustment is improved.
为了更清楚地说明本申请实施例或现有技术中的技术方案,下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本申请的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。In order to more clearly describe the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.
其中:in:
图1为一个实施例中所述音频信号调整方法的流程示意图;FIG. 1 is a schematic flowchart of the audio signal adjustment method in an embodiment;
图2为一个实施例中所述振膜振幅预测方法的流程示意图;FIG. 2 is a schematic flowchart of the method for predicting the amplitude of the diaphragm in an embodiment;
图3为另一个实施例中所述振膜振幅预测方法的流程示意图;FIG. 3 is a schematic flowchart of the method for predicting the amplitude of the diaphragm in another embodiment;
图4为一个实施例中所述目标调整增益确定方法的流程示意图;FIG. 4 is a schematic flowchart of the method for determining the target adjustment gain in an embodiment;
图5为另一个实施例中所述目标调整增益确定方法的流程示意图;FIG. 5 is a schematic flowchart of the method for determining the target adjustment gain in another embodiment;
图6为另一个实施例中所述音频信号调整方法的流程示意图;FIG. 6 is a schematic flowchart of the audio signal adjustment method in another embodiment;
图7为一个实施例中所述音频信号调整装置的结构示意图;FIG. 7 is a schematic diagram of the structure of the audio signal adjusting device in an embodiment;
图8为一个实施例中运行上述音频信号调整方法的计算机设备的内部结构示意图。FIG. 8 is a schematic diagram of the internal structure of a computer device running the above audio signal adjustment method in an embodiment.
下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本申请一部分实施例,而不是全部的实施例。基于本申请中的实施例,本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例,都属于本申请保护的范围。The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of this application.
为解决传统技术中采用对扬声器腔体结构或内部材质进行改进,或者动态范围压缩技术来控制激励电压,避免过高电压值下出现气流杂音,产生的音频信号调整不佳,且提纵横自由度不高的为问题。In order to solve the traditional technology, the speaker cavity structure or internal material is improved, or the dynamic range compression technology is used to control the excitation voltage, to avoid airflow noise under excessively high voltage values, and the resulting audio signal is poorly adjusted, and the vertical and horizontal freedom is improved. The problem is not high.
基于上述问题,在本实施例中,特提出了一种音频信号调整方法。该方法的实现可依赖于计算机程序,该计算机程序可运行于基于冯诺依曼体系的计算机***之上。Based on the above problems, in this embodiment, an audio signal adjustment method is specially proposed. The realization of the method can rely on a computer program, which can run on a computer system based on the von Neumann system.
如图1所示,本实施例提供的音频信号调整方法,应用于微型扬声器,该音频信号调整方法具体包括以下步骤:As shown in FIG. 1, the audio signal adjustment method provided in this embodiment is applied to a micro speaker, and the audio signal adjustment method specifically includes the following steps:
步骤102:获取待输入微型扬声器的激励信号,并预测激励信号输入微型扬声器产生的振膜振幅。Step 102: Obtain an excitation signal to be input to the micro speaker, and predict the vibration amplitude of the diaphragm generated by the excitation signal input to the micro speaker.
其中,激励信号是指信号激励源即测试时播放的音乐文件(比如歌曲),播放出来的音频信号被麦克风录下来的音频信号对应的输入信号。具体地,可以预先从服务器中确定信号激励源,通过模拟信号激励源输入至微型扬声器中产生的音频信号作为激励信号。振膜振幅是用于反映激励信号产生气流杂音强度的指标数据,振膜振幅越大,则激励信号产生气流杂音强度的越大。具体地,可以通过扬声器模型预测激励信号输入微型扬声器产生的振膜振幅,也可以通过基于机器学习的预测模型预测激励信号输入微型扬声器产生的振膜振幅。Among them, the excitation signal refers to the signal excitation source that is the music file (such as a song) played during the test, and the played audio signal is the input signal corresponding to the audio signal recorded by the microphone. Specifically, the signal excitation source can be determined in advance from the server, and the audio signal generated by the analog signal excitation source input into the micro speaker is used as the excitation signal. The diaphragm amplitude is the index data used to reflect the intensity of the airflow noise generated by the excitation signal. The larger the vibration diaphragm amplitude, the greater the intensity of the airflow noise generated by the excitation signal. Specifically, the amplitude of the diaphragm generated by the excitation signal input to the micro-speaker can be predicted by the speaker model, or the diaphragm amplitude generated by the input of the excitation signal into the micro-speaker can be predicted by a predictive model based on machine learning.
步骤104:判断振膜振幅是否超过预设振幅阈值。Step 104: Determine whether the amplitude of the diaphragm exceeds a preset amplitude threshold.
其中,预设振幅阈值是指预先设定的用于判断是否产生气流杂音的激励信号的振膜振幅的临界值。具体地,该预设振幅阈值可以通过听音测试结合实验测量来确定,即将听音感受到气流噪声的最低振膜振幅设为该预设振幅阈值,也可以通过大规模测试,由指机器学习算法,如隐马尔科夫模型、神经网络等确定不同频率、不同振膜振幅下出现气流噪声概率,根据出现气流噪声的概率动态改变振幅阈值,将概率超过特定值时的振膜振幅设为振幅阈值,示例性地,概率值取75%,按照概率设置预设振幅阈值的情况下,概率越大,出现气流噪声的风险越大,当把预设振幅阈值设的越小,越能提高对气流噪声预测的准确性。Wherein, the preset amplitude threshold refers to a preset threshold value of the diaphragm amplitude of the excitation signal used to determine whether airflow noise is generated. Specifically, the preset amplitude threshold can be determined by listening test combined with experimental measurement, that is, the lowest diaphragm amplitude of the airflow noise experienced by listening is set to the preset amplitude threshold, or it can pass a large-scale test by referring to the machine learning algorithm , Such as hidden Markov model, neural network, etc., determine the probability of airflow noise at different frequencies and different diaphragm amplitudes, dynamically change the amplitude threshold according to the probability of airflow noise, and set the diaphragm amplitude when the probability exceeds a specific value as the amplitude threshold Exemplarily, the probability value is 75%. When the preset amplitude threshold is set according to the probability, the greater the probability, the greater the risk of airflow noise. When the preset amplitude threshold is set to a smaller value, the airflow can be improved. The accuracy of noise prediction.
值得说明的是,作为本实施例中的优选,可以根据出现气流噪声的概率动态改变振幅阈值,从而能够动态地进行后续动态音频信号地调整,提高音频信号调整的准确性和自由度。It is worth noting that, as a preference in this embodiment, the amplitude threshold can be dynamically changed according to the probability of occurrence of airflow noise, so that subsequent dynamic audio signal adjustments can be dynamically performed, and the accuracy and freedom of audio signal adjustments can be improved.
步骤106:当振膜振幅超过预设振幅阈值时,根据振膜振幅和预设振幅阈值,确定激励信号的振膜振幅降低至小于预设振幅阈值时的目标调整增益。Step 106: When the diaphragm amplitude exceeds the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold.
其中,目标调整增益是指将激励信号的振膜振幅降低至小于预设振幅阈值时,振膜振幅需要的放大倍数,例如,当激励信号的振膜振幅为A,将激励信号对应的理想振膜振幅为a,则此时的目标调整增益为a/A。可以理解地,由于在振膜振幅超过预设振幅阈值时,将该激励信号输入至微型扬声器时,会出现气流杂音,因此,为了避免气流杂音的出现,需要将激励信号的振膜振幅降低至小于预设振幅阈值,因此,需要确定对应的目标调整增益,以便在微型扬声器播放该激励信号之前,确定激励信号的振膜振幅进行准确的调整,进而避免气流杂音出现。Among them, the target adjustment gain refers to the magnification required for the diaphragm amplitude when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold. For example, when the diaphragm amplitude of the excitation signal is A, the ideal vibration corresponding to the excitation signal The film amplitude is a, and the target adjustment gain at this time is a/A. It is understandable that when the diaphragm amplitude exceeds the preset amplitude threshold, airflow noise will appear when the excitation signal is input to the micro-speaker. Therefore, in order to avoid the occurrence of airflow noise, the diaphragm amplitude of the excitation signal needs to be reduced to It is less than the preset amplitude threshold. Therefore, it is necessary to determine the corresponding target adjustment gain, so that the diaphragm amplitude of the excitation signal is determined to be accurately adjusted before the micro-speaker plays the excitation signal, so as to avoid the appearance of airflow noise.
步骤108:利用均衡器算法按照目标调整增益对激励信号进行调整,得到目标音频信号。Step 108: Use the equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain the target audio signal.
其中,均衡器(Equalizer)算法是一种通过对频域进行频带划分(如划分为5,10,12,15个频带)并对不同的频带施加相应的增益,从而改变原始数据频域能量分布,达到改变主观听感的作用的音频信号处理方法。目标音频信号是指在听感上几乎感受不到气流杂音的音频信号。考虑到实时处理特性,避免FFT(快速傅立叶变换的算法)切换到频域处理,采用时域滤波的方式,因此,本实施例中的均衡器为参数均衡器和时域均衡器。具体地,均衡器在20~20K
Hz频率范围内分割为5, 10, 15, 20或30个频带,并对该频带施加与目标调整增益对应大小的增益,实现对激励信号得调整,将调整后的激励信号输入至微型扬声器,通过微型扬声器播放目标音频信号。Among them, the equalizer algorithm is a way to divide the frequency domain into frequency bands (such as dividing into 5, 10, 12, and 15 frequency bands) and apply corresponding gains to different frequency bands to change the frequency domain energy distribution of the original data. , An audio signal processing method that changes the subjective sense of hearing. The target audio signal refers to an audio signal in which air noise is hardly felt in the sense of hearing. Considering the characteristics of real-time processing, avoiding FFT (Fast Fourier Transform algorithm) switching to frequency domain processing and adopting time domain filtering, therefore, the equalizer in this embodiment is a parametric equalizer and a time domain equalizer. Specifically, the equalizer is at 20~20K
The Hz frequency range is divided into 5, 10, 15, 20 or 30 frequency bands, and a gain corresponding to the target adjustment gain is applied to this frequency band to realize the adjustment of the excitation signal, and the adjusted excitation signal is input to the micro speaker, Play the target audio signal through the micro speaker.
进一步地,本实施例中,由于只对振膜振幅超过预设振幅阈值的激励信号的振膜振幅进行调整,对于小于或者等于振膜振幅超过预设振幅阈值的激励信号的振膜振幅不做调整,即只针对会产生气流噪声的窄频段的激励信号进行处理,对总体音量影响有限,因此,可以最大程度的避免忽大忽小的现象被主观感知到。提高了音频信号调整效果和效率。并且由于本实施例中的预设振膜振幅是动态确定的,进而对激励信号的调整也是通过动态均衡器进行动态调整,得到目标音频信号,从而提高了音频信号调整的自由度。Further, in this embodiment, since only the diaphragm amplitude of the excitation signal whose diaphragm amplitude exceeds the preset amplitude threshold is adjusted, the diaphragm amplitude of the excitation signal whose diaphragm amplitude exceeds the preset amplitude threshold is not adjusted. Adjustment, that is, only process the excitation signal in a narrow frequency band that will produce airflow noise, and has a limited impact on the overall volume. Therefore, it can avoid the subjective perception of the fluctuations of large and small phenomena to the greatest extent. Improve the effect and efficiency of audio signal adjustment. Moreover, since the preset diaphragm amplitude in this embodiment is determined dynamically, the adjustment of the excitation signal is also dynamically adjusted through the dynamic equalizer to obtain the target audio signal, thereby increasing the degree of freedom of audio signal adjustment.
上述音频信号调整方法,获取待输入微型扬声器的激励信号,并预测激励信号输入微型扬声器产生的振膜振幅;判断振膜振幅是否超过预设振幅阈值;当振膜振幅超过预设振幅阈值时,根据振膜振幅和预设振幅阈值,确定激励信号的振膜振幅降低至小于预设振幅阈值时的目标调整增益;利用均衡器算法按照目标调整增益对激励信号进行调整,得到目标音频信号,避免了目标音频信号中出现气流杂音,通过采用动态均衡器算法实现了对音频信号的调整,并且在调整音频信号时,由于只针对会产生气流噪声的窄频段的音频信号进行处理,对总体音量影响有限,从而最大程度的避免忽大忽小的现象被主观感知到,同时,由于根据预设阈值确定是否进行音频信号调整,提高了音频信号调整的自由度和音频信号调整效果及效率。The audio signal adjustment method described above obtains the excitation signal to be input to the micro speaker, and predicts the vibration amplitude of the diaphragm generated by the excitation signal input to the micro speaker; determines whether the diaphragm amplitude exceeds the preset amplitude threshold; when the diaphragm amplitude exceeds the preset amplitude threshold, According to the diaphragm amplitude and the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; use the equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain the target audio signal to avoid In order to avoid airflow noise in the target audio signal, the audio signal is adjusted by adopting a dynamic equalizer algorithm. When adjusting the audio signal, since only the audio signal of a narrow frequency band that generates airflow noise is processed, it affects the overall volume. Limited, so as to avoid the phenomenon of fluctuations in large and small being subjectively perceived to the greatest extent, and at the same time, since the audio signal adjustment is determined according to the preset threshold, the freedom of audio signal adjustment and the effect and efficiency of audio signal adjustment are improved.
如图2所示,在一个实施例中,预测激励信号输入微型扬声器产生的振膜振幅,包括:As shown in Fig. 2, in one embodiment, predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes:
步骤102A:提取激励信号的音频参数;Step 102A: Extract audio parameters of the excitation signal;
步骤102B:将音频参数输入到预设的扬声器模型中进行预测,得到振膜振幅。Step 102B: Input the audio parameters into the preset loudspeaker model for prediction, and obtain the diaphragm amplitude.
其中,音频参数是指激励信号中与振膜振幅相关的信号参数,如频率、振膜速度或者振膜加速度等,具体地,可以通过信号源及信号分析***提取激励信号的音频参数。然后,将音频参数输入到预设的扬声器模型中,通过预设的扬声器模型对音频参数直接计算,振膜振幅。可以理解地,通过采用预设的扬声器模型,方便快速地预测了激励信号的振膜振幅。Among them, the audio parameters refer to signal parameters related to the diaphragm amplitude in the excitation signal, such as frequency, diaphragm velocity, or diaphragm acceleration. Specifically, the audio parameters of the excitation signal can be extracted through a signal source and a signal analysis system. Then, the audio parameters are input into the preset speaker model, and the audio parameters are directly calculated through the preset speaker model, and the diaphragm amplitude is directly calculated. Understandably, by adopting the preset loudspeaker model, the diaphragm amplitude of the excitation signal can be easily and quickly predicted.
如图3所示,在一个实施例中,预测激励信号输入微型扬声器产生的振膜振幅,包括:As shown in Figure 3, in one embodiment, predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes:
步骤102C:提取激励信号的音频参数;Step 102C: Extract audio parameters of the excitation signal;
步骤102D:通过预设的基于机器学习算法训练得到的振幅预测模型并根据音频参数,得到振膜振幅。Step 102D: Obtain the diaphragm amplitude according to the preset amplitude prediction model trained based on the machine learning algorithm and according to the audio parameters.
在这个实施例中,音频参数与步骤102A中的音频参数一致,此处还不再赘述。振幅预测模型是基于预置的机器学习算法,如隐马尔科夫模型、神经网络等,该算法建立了音频参数与振膜振幅大小之间的关系,将音频参数作为振幅预测模型的输入,该振幅预测模型输出即为激励信号的振膜振幅。In this embodiment, the audio parameters are consistent with the audio parameters in step 102A, and will not be repeated here. The amplitude prediction model is based on preset machine learning algorithms, such as hidden Markov models, neural networks, etc. This algorithm establishes the relationship between the audio parameters and the amplitude of the diaphragm, and uses the audio parameters as the input of the amplitude prediction model. The output of the amplitude prediction model is the diaphragm amplitude of the excitation signal.
如图4所示,在一个实施例中,根据振膜振幅和预设振幅阈值,确定激励信号的振膜振幅降低至小于预设振幅阈值时的目标调整增益,包括:As shown in FIG. 4, in one embodiment, determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes:
步骤106A:根据振膜振幅和预设振幅阈值确定目标振幅,目标振幅小于预设振幅阈值;Step 106A: Determine the target amplitude according to the diaphragm amplitude and the preset amplitude threshold, and the target amplitude is less than the preset amplitude threshold;
步骤106B:通过预设的扬声器模型中内置的增益曲线确定与目标振幅对应的目标调整增益。Step 106B: Determine the target adjustment gain corresponding to the target amplitude through the built-in gain curve in the preset loudspeaker model.
其中,目标振幅是指能够避免气流杂音出现的激励信号的振膜振幅,且该目标振幅小于预设振幅阈值。具体地,可以预先根据激励信号的振膜振幅确定对应的修正值,然后将预设振幅阈值与该修正值的差值确定为目标振幅。预设的扬声器模型中内置的增益曲线是指预先设置的用于描述振膜振幅与增益之间关系变化的曲线。在该增益曲线中,查找目标振幅对应的增益即为目标调整增益。Wherein, the target amplitude refers to the diaphragm amplitude of the excitation signal that can avoid the occurrence of airflow noise, and the target amplitude is less than a preset amplitude threshold. Specifically, the corresponding correction value may be determined in advance according to the diaphragm amplitude of the excitation signal, and then the difference between the preset amplitude threshold and the correction value may be determined as the target amplitude. The built-in gain curve in the preset loudspeaker model refers to the preset curve used to describe the change of the relationship between the amplitude of the diaphragm and the gain. In the gain curve, finding the gain corresponding to the target amplitude is the target adjustment gain.
如图5所示,在一个实施例中,根据振膜振幅和预设振幅阈值,确定激励信号的振膜振幅降低至小于预设振幅阈值时的目标调整增益,包括:As shown in FIG. 5, in one embodiment, determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes:
步骤106C:根据振膜振幅和预设振幅阈值确定目标振幅,目标振幅小于预设振幅阈值;Step 106C: Determine the target amplitude according to the diaphragm amplitude and the preset amplitude threshold, where the target amplitude is less than the preset amplitude threshold;
步骤106D:通过预设的基于机器学习的增益计算模型并根据目标振幅计算得到目标调整增益。Step 106D: Obtain the target adjustment gain through a preset gain calculation model based on machine learning and calculation according to the target amplitude.
本实施例中的目标振幅与步骤106A步骤中目标振幅一致,此处不再赘述。增益计算模型是基于预置的机器学习算法,如隐马尔科夫模型、神经网络等,该算法建立了增益与振膜振幅大小之间的关系,将目标振幅作为增益计算模型的输入,该增益计算模型输出即为目标调整增益。The target amplitude in this embodiment is consistent with the target amplitude in step 106A, and will not be repeated here. The gain calculation model is based on a preset machine learning algorithm, such as hidden Markov model, neural network, etc. This algorithm establishes the relationship between the gain and the amplitude of the diaphragm, and uses the target amplitude as the input of the gain calculation model. The calculated model output is the target adjustment gain.
如图6所示,在一个实施例中,利用均衡器算法按照目标调整增益对激励信号进行调整,得到目标音频信号,包括:As shown in FIG. 6, in one embodiment, using an equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain the target audio signal includes:
步骤108A:获取均衡器算法中包含的多个滤波器及相应的频率和能量;Step 108A: Obtain multiple filters and corresponding frequencies and energy included in the equalizer algorithm;
步骤108B:根据每个滤波器级频率和能量,以及目标调整增益,计算每个滤波器的品质因数;Step 108B: Calculate the quality factor of each filter according to the frequency and energy of each filter stage and the target adjustment gain;
步骤108C:根据每个滤波器的品质因数,对激励信号进行滤波处理,得到目标音频信。Step 108C: Filter the excitation signal according to the quality factor of each filter to obtain the target audio signal.
其中,品质因数是指截止频率对应处的增益的模与通带增益的模的比值,用于反映低通滤波器在截止频率处幅频特性的形状。品质因数越大,滤波频带越窄,在频带内的滤波效果就越好。具体地,根据每个滤波器级频率和能量,以及目标调整增益,计算每个滤波器的品质因数,其计算过程可以通过内置算法,形式如Q =
f(频率,能量、增益)的函数,其中,Q表示品质因数,f为内置算算法的函数名,该动态确定Q的内置算法是基于扬声器模型的算法或基于统计模型的算法。根据频率、能量和增益,可以计算出对应的品质因数,根据每个滤波器的品质因数,对激励信号进行滤波处理,得到目标音频信,实现了对激励信号中会产生气流噪声的窄频段的激励信号进行滤波处理,进而实现音频信号的调整,且对总体音量影响有限,最大程度的避免音频信号忽大忽小的现象被主观感知到,提高了音频信号调整的效果和效率。且由于根据每个滤波器的品质因数,对激励信号进行了动态滤波处理,提高了对音频信号调整的自由度。Among them, the quality factor refers to the ratio of the mode of the gain corresponding to the cut-off frequency to the mode of the pass-band gain, which is used to reflect the shape of the amplitude-frequency characteristics of the low-pass filter at the cut-off frequency. The larger the quality factor, the narrower the filtering frequency band, and the better the filtering effect within the frequency band. Specifically, according to the frequency and energy of each filter stage, and the target adjustment gain, the quality factor of each filter is calculated. The calculation process can be through a built-in algorithm in the form of Q =
A function of f (frequency, energy, gain), where Q represents the quality factor, and f is the function name of the built-in algorithm. The built-in algorithm for dynamically determining Q is an algorithm based on a speaker model or an algorithm based on a statistical model. According to the frequency, energy and gain, the corresponding quality factor can be calculated. According to the quality factor of each filter, the excitation signal is filtered to obtain the target audio signal, which realizes the narrow frequency band that generates airflow noise in the excitation signal. The excitation signal is filtered to realize the adjustment of the audio signal, and has a limited impact on the overall volume. It avoids the subjective perception of the fluctuation of the audio signal to the greatest extent, and improves the effect and efficiency of audio signal adjustment. And because the excitation signal is dynamically filtered according to the quality factor of each filter, the freedom of adjusting the audio signal is improved.
在一个实施例中,滤波器为IIR滤波器或FIR滤波器。In one embodiment, the filter is an IIR filter or FIR filter.
其中,IIR滤波器为无限冲激响应滤波器,FIR滤波器为有限冲激响应滤波器。通过滤波器为IIR滤波器或FIR滤波器对激励信号进行处理,可以得到激励信号的时域特征,从而提高了对音频信号调整的实时性。Among them, the IIR filter is an infinite impulse response filter, and the FIR filter is a finite impulse response filter. The excitation signal is processed by the filter as an IIR filter or an FIR filter, and the time domain characteristics of the excitation signal can be obtained, thereby improving the real-time performance of audio signal adjustment.
值得说明的是,本实施例中的滤波器阶数不超过6阶,从而在保证调节效果的基础上节省成本。It is worth noting that the order of the filter in this embodiment does not exceed 6 orders, thereby saving costs on the basis of ensuring the adjustment effect.
基于同一申请构思,本申请实施例提供一种音频信号调整装置700,如图7所示,包括:振幅预测模块702,用于获取待输入所述微型扬声器的激励信号,并预测所述激励信号输入所述微型扬声器产生的振膜振幅;判断模块704,用于判断所述振膜振幅是否超过预设振幅阈值;增益确定模块706,用于当所述振膜振幅超过预设振幅阈值时,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益;信号调整模块708,用于利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。Based on the same application concept, an embodiment of the application provides an audio signal adjustment device 700, as shown in FIG. 7, including: an amplitude prediction module 702, configured to obtain an excitation signal to be input to the micro speaker, and predict the excitation signal Input the diaphragm amplitude generated by the micro-speaker; the determining module 704 is used to determine whether the amplitude of the diaphragm exceeds the preset amplitude threshold; the gain determining module 706 is used to when the amplitude of the diaphragm exceeds the preset amplitude threshold, According to the diaphragm amplitude and the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; the signal adjustment module 708 is configured to use an equalizer algorithm according to The target adjustment gain adjusts the excitation signal to obtain a target audio signal.
具体地,本实施例的音频信号调整装置700,如图7所示,包括:振幅预测模块702,用于获取待输入所述微型扬声器的激励信号,并预测所述激励信号输入所述微型扬声器产生的振膜振幅;判断模块704,用于判断所述振膜振幅是否超过预设振幅阈值;增益确定模块706,用于当所述振膜振幅超过预设振幅阈值时,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益;信号调整模块708,用于利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。由于只针对会产生气流噪声的窄频段的音频信号进行处理,对总体音量影响有限,从而最大程度的避免忽大忽小的现象被主观感知到,同时,由于根据预设阈值确定是否进行音频信号调整,提高了音频信号调整的自由度和音频信号调整效果及效率。Specifically, the audio signal adjustment device 700 of this embodiment, as shown in FIG. 7, includes: an amplitude prediction module 702, configured to obtain an excitation signal to be input to the micro speaker, and predict that the excitation signal is input to the micro speaker Generated vibration diaphragm amplitude; judging module 704, used to determine whether the vibration diaphragm amplitude exceeds a preset amplitude threshold; gain determination module 706, when the vibration diaphragm amplitude exceeds the preset amplitude threshold, according to the diaphragm The amplitude and the preset amplitude threshold are used to determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; the signal adjustment module 708 is configured to adjust the gain according to the target by using an equalizer algorithm The excitation signal is adjusted to obtain the target audio signal. Since it only processes audio signals in a narrow frequency band that will produce airflow noise, it has limited impact on the overall volume, so as to avoid the subjective perception of fluctuations in large and small phenomena. At the same time, it is determined whether to perform audio signals according to a preset threshold. Adjustment improves the freedom of audio signal adjustment and the effect and efficiency of audio signal adjustment.
需要说明的是,本实施例中音频信号调整的装置的实现与上述音频信号调整的方法的实现思想一致,其实现原理在此不再进行赘述,可具体参阅上述方法中对应内容。It should be noted that the realization of the audio signal adjustment device in this embodiment is consistent with the realization idea of the aforementioned audio signal adjustment method, and its realization principle will not be repeated here. For details, please refer to the corresponding content in the aforementioned method.
图8示出了一个实施例中计算机设备的内部结构图。该计算机设备具体可以是服务器,也可以是终端。如图8所示,该计算机设备800包括通过***总线连接的处理器810、存储器820和网络接口830。其中,存储器820包括非易失性存储介质和内存储器。该计算机设备的非易失性存储介质存储有操作***,还可存储有计算机程序,该计算机程序被处理器执行时,可使得处理器实现音频信号调整的方法。该内存储器中也可储存有计算机程序,该计算机程序被处理器执行时,可使得处理器执行音频信号调整的方法。本领域技术人员可以理解,图8中示出的结构,仅仅是与本申请方案相关的部分结构的框图,并不构成对本申请方案所应用于其上的计算机设备的限定,具体的计算机设备可以包括比图8中所示更多或更少的部件,或者组合某些部件,或者具有不同的部件布置。Fig. 8 shows an internal structure diagram of a computer device in an embodiment. The computer device may specifically be a server or a terminal. As shown in FIG. 8, the computer device 800 includes a processor 810, a memory 820, and a network interface 830 connected through a system bus. Among them, the memory 820 includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system, and may also store a computer program. When the computer program is executed by the processor, the processor can implement the audio signal adjustment method. A computer program may also be stored in the internal memory, and when the computer program is executed by the processor, the processor can execute the audio signal adjustment method. Those skilled in the art can understand that the structure shown in FIG. 8 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may Including more or fewer components than shown in FIG. 8, or combining certain components, or having a different component arrangement.
在一个实施例中,本申请提供的音频信号调整的方法可以实现为一种计算机程序的形式,计算机程序可在如图8所示的计算机设备上运行。计算机设备的存储器中可存储组成所述音频信号调整的装置的各个程序模块。比如,振幅预测模块702,判断模块704,增益确定模块706,信号调整模块708。In an embodiment, the audio signal adjustment method provided in the present application can be implemented in the form of a computer program, and the computer program can be run on a computer device as shown in FIG. 8. The memory of the computer device can store various program modules that make up the audio signal adjustment device. For example, the amplitude prediction module 702, the judgment module 704, the gain determination module 706, and the signal adjustment module 708.
一种计算机设备,包括存储器和处理器,所述存储器存储有计算机程序,所述计算机程序被所述处理器执行时,使得所述处理器执行以下步骤:获取待输入所述微型扬声器的激励信号,并预测所述激励信号输入所述微型扬声器产生的振膜振幅;判断所述振膜振幅是否超过预设振幅阈值;当所述振膜振幅超过预设振幅阈值时,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益;利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。A computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the following steps: Obtain an excitation signal to be input to the micro speaker , And predict the diaphragm amplitude generated by the excitation signal input to the micro speaker; determine whether the diaphragm amplitude exceeds a preset amplitude threshold; when the diaphragm amplitude exceeds the preset amplitude threshold, according to the diaphragm amplitude And the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; adjust the excitation signal according to the target adjustment gain by using an equalizer algorithm, Obtain the target audio signal.
在一个实施例中,预测所述激励信号输入所述微型扬声器产生的振膜振幅,包括:提取所述激励信号的音频参数;将所述音频参数输入到预设的扬声器模型中进行预测,得到所述振膜振幅。In one embodiment, predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes: extracting audio parameters of the excitation signal; inputting the audio parameters into a preset speaker model for prediction, and obtaining The amplitude of the diaphragm.
在一个实施例中,预测所述激励信号输入所述微型扬声器产生的振膜振幅,包括:提取所述激励信号的音频参数;通过预设的基于机器学习算法训练得到的振幅预测模型并根据所述音频参数,得到所述振膜振幅。In one embodiment, predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes: extracting the audio parameters of the excitation signal; using a preset amplitude prediction model trained based on a machine learning algorithm and according to the The audio parameter is used to obtain the vibration diaphragm amplitude.
在一个实施例中,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益,包括:根据所述振膜振幅和所述预设振幅阈值确定目标振幅,所述目标振幅小于所述预设振幅阈值;通过预设的扬声器模型中内置的增益曲线确定与所述目标振幅对应的所述目标调整增益。In one embodiment, determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes: according to the vibration The film amplitude and the preset amplitude threshold determine a target amplitude, and the target amplitude is less than the preset amplitude threshold; the target adjustment gain corresponding to the target amplitude is determined through a gain curve built into the preset speaker model.
在一个实施例中,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益,包括:根据所述振膜振幅和所述预设振幅阈值确定目标振幅,所述目标振幅小于所述预设振幅阈值;通过预设的基于机器学习的增益计算模型并根据所述目标振幅计算得到所述目标调整增益。In one embodiment, determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes: according to the vibration The film amplitude and the preset amplitude threshold determine a target amplitude, and the target amplitude is less than the preset amplitude threshold; the target adjustment gain is calculated by a preset gain calculation model based on machine learning and calculated according to the target amplitude.
在一个实施例中,利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号,包括:获取所述均衡器算法中包含的多个滤波器及相应的频率和能量;根据每个滤波器级频率和能量,以及所述目标调整增益,计算每个滤波器的品质因数;根据每个滤波器的品质因数,对所述激励信号进行滤波处理,得到目标音频信。In one embodiment, using an equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain a target audio signal includes: obtaining multiple filters included in the equalizer algorithm and corresponding frequencies and energy Calculate the quality factor of each filter according to the frequency and energy of each filter stage and the target adjustment gain; filter the excitation signal according to the quality factor of each filter to obtain the target audio signal.
在一个实施例中,滤波器为IIR滤波器或FIR滤波器。In one embodiment, the filter is an IIR filter or FIR filter.
一种计算机可读存储介质,所述计算机可读存储介质存储有计算机程序,其特征在于,所述计算机程序被处理器执行时实现如下步骤:获取待输入所述微型扬声器的激励信号,并预测所述激励信号输入所述微型扬声器产生的振膜振幅;判断所述振膜振幅是否超过预设振幅阈值;当所述振膜振幅超过预设振幅阈值时,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益;利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is characterized in that, when the computer program is executed by a processor, the following steps are implemented: obtaining an excitation signal to be input to the micro-speaker, and predicting The excitation signal is input to the diaphragm amplitude generated by the micro-speaker; it is determined whether the diaphragm amplitude exceeds a preset amplitude threshold; when the diaphragm amplitude exceeds the preset amplitude threshold, according to the diaphragm amplitude and the The preset amplitude threshold is used to determine the target adjustment gain when the diaphragm amplitude of the excitation signal is reduced to less than the preset amplitude threshold; the equalizer algorithm is used to adjust the excitation signal according to the target adjustment gain to obtain the target audio Signal.
在一个实施例中,预测所述激励信号输入所述微型扬声器产生的振膜振幅,包括:提取所述激励信号的音频参数;将所述音频参数输入到预设的扬声器模型中进行预测,得到所述振膜振幅。In one embodiment, predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes: extracting audio parameters of the excitation signal; inputting the audio parameters into a preset speaker model for prediction, and obtaining The amplitude of the diaphragm.
在一个实施例中,预测所述激励信号输入所述微型扬声器产生的振膜振幅,包括:提取所述激励信号的音频参数;通过预设的基于机器学习算法训练得到的振幅预测模型并根据所述音频参数,得到所述振膜振幅。In one embodiment, predicting the amplitude of the diaphragm generated by the excitation signal input to the micro speaker includes: extracting the audio parameters of the excitation signal; using a preset amplitude prediction model trained based on a machine learning algorithm and according to the The audio parameter is used to obtain the vibration diaphragm amplitude.
在一个实施例中,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益,包括:根据所述振膜振幅和所述预设振幅阈值确定目标振幅,所述目标振幅小于所述预设振幅阈值;通过预设的扬声器模型中内置的增益曲线确定与所述目标振幅对应的所述目标调整增益。In one embodiment, determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes: according to the vibration The film amplitude and the preset amplitude threshold determine a target amplitude, and the target amplitude is less than the preset amplitude threshold; the target adjustment gain corresponding to the target amplitude is determined through a gain curve built into the preset speaker model.
在一个实施例中,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益,包括:根据所述振膜振幅和所述预设振幅阈值确定目标振幅,所述目标振幅小于所述预设振幅阈值;通过预设的基于机器学习的增益计算模型并根据所述目标振幅计算得到所述目标调整增益。In one embodiment, determining the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold includes: according to the vibration The film amplitude and the preset amplitude threshold determine a target amplitude, and the target amplitude is less than the preset amplitude threshold; the target adjustment gain is calculated by a preset gain calculation model based on machine learning and calculated according to the target amplitude.
在一个实施例中,利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号,包括:获取所述均衡器算法中包含的多个滤波器及相应的频率和能量;根据每个滤波器级频率和能量,以及所述目标调整增益,计算每个滤波器的品质因数;根据每个滤波器的品质因数,对所述激励信号进行滤波处理,得到目标音频信。In one embodiment, using an equalizer algorithm to adjust the excitation signal according to the target adjustment gain to obtain a target audio signal includes: obtaining multiple filters included in the equalizer algorithm and corresponding frequencies and energy Calculate the quality factor of each filter according to the frequency and energy of each filter stage and the target adjustment gain; filter the excitation signal according to the quality factor of each filter to obtain the target audio signal.
在一个实施例中,滤波器为IIR滤波器或FIR滤波器。In one embodiment, the filter is an IIR filter or FIR filter.
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程,是可以通过计算机程序来指令相关的硬件来完成,所述的程序可存储于一非易失性计算机可读取存储介质中,该程序在执行时,可包括如上述各方法的实施例的流程。其中,本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用,均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限,RAM以多种形式可得,诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer readable storage medium. Here, when the program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and/or volatile memory. Non-volatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not a limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Channel (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
以上所揭露的仅为本申请较佳实施例而已,当然不能以此来限定本申请之权利范围,因此依本申请权利要求所作的等同变化,仍属本申请所涵盖的范围。The above-disclosed are only the preferred embodiments of the application, and of course the scope of rights of the application cannot be limited by this. Therefore, equivalent changes made in accordance with the claims of the application still fall within the scope of the application.
Claims (10)
- 一种音频信号调整方法,其特征在于,应用于微型扬声器,所述方法包括:An audio signal adjustment method, characterized in that it is applied to a micro speaker, and the method includes:获取待输入所述微型扬声器的激励信号,并预测所述激励信号输入所述微型扬声器产生的振膜振幅;Acquiring an excitation signal to be input to the micro speaker, and predicting the vibration amplitude of the diaphragm generated when the excitation signal is input to the micro speaker;判断所述振膜振幅是否超过预设振幅阈值;Judging whether the amplitude of the diaphragm exceeds a preset amplitude threshold;当所述振膜振幅超过预设振幅阈值时,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益;When the amplitude of the diaphragm exceeds the preset amplitude threshold, determine the target adjustment gain when the diaphragm amplitude of the excitation signal decreases to less than the preset amplitude threshold according to the diaphragm amplitude and the preset amplitude threshold ;利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。An equalizer algorithm is used to adjust the excitation signal according to the target adjustment gain to obtain a target audio signal.
- 如权利要求1所述音频信号调整方法,其特征在于,所述预测所述激励信号输入所述微型扬声器产生的振膜振幅,包括:5. The audio signal adjustment method according to claim 1, wherein said predicting the amplitude of the diaphragm generated by the input of the excitation signal into the micro speaker comprises:提取所述激励信号的音频参数;Extract the audio parameters of the excitation signal;将所述音频参数输入到预设的扬声器模型中进行预测,得到所述振膜振幅。The audio parameters are input into a preset loudspeaker model for prediction, and the diaphragm amplitude is obtained.
- 如权利要求1所述音频信号调整方法,其特征在于,所述预测所述激励信号输入所述微型扬声器产生的振膜振幅,包括:5. The audio signal adjustment method according to claim 1, wherein said predicting the amplitude of the diaphragm generated by the input of the excitation signal into the micro speaker comprises:提取所述激励信号的音频参数;Extract the audio parameters of the excitation signal;通过预设的基于机器学习算法训练得到的振幅预测模型并根据所述音频参数,得到所述振膜振幅。Obtain the diaphragm amplitude according to a preset amplitude prediction model trained based on a machine learning algorithm and according to the audio parameters.
- 如权利要求1所述音频信号调整方法,其特征在于,所述根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益,包括:2. The audio signal adjustment method of claim 1, wherein the vibration amplitude of the excitation signal is determined to be less than the preset amplitude threshold according to the vibration diaphragm amplitude and the preset amplitude threshold. The target adjustment gain includes:根据所述振膜振幅和所述预设振幅阈值确定目标振幅,所述目标振幅小于所述预设振幅阈值;Determining a target amplitude according to the diaphragm amplitude and the preset amplitude threshold, where the target amplitude is less than the preset amplitude threshold;通过预设的扬声器模型中内置的增益曲线确定与所述目标振幅对应的所述目标调整增益。The target adjustment gain corresponding to the target amplitude is determined by a gain curve built into the preset speaker model.
- 如权利要求1所述音频信号调整方法,其特征在于,所述根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益,包括:2. The audio signal adjustment method of claim 1, wherein the vibration amplitude of the excitation signal is determined to be less than the preset amplitude threshold according to the vibration diaphragm amplitude and the preset amplitude threshold. The target adjustment gain includes:根据所述振膜振幅和所述预设振幅阈值确定目标振幅,所述目标振幅小于所述预设振幅阈值;Determining a target amplitude according to the diaphragm amplitude and the preset amplitude threshold, where the target amplitude is less than the preset amplitude threshold;通过预设的基于机器学习的增益计算模型并根据所述目标振幅计算得到所述目标调整增益。The target adjustment gain is obtained through a preset gain calculation model based on machine learning and calculated according to the target amplitude.
- 如权利要求1所述音频信号调整方法,其特征在于,所述利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号,包括:5. The audio signal adjustment method according to claim 1, wherein said using an equalizer algorithm to adjust said excitation signal according to said target adjustment gain to obtain a target audio signal comprises:获取所述均衡器算法中包含的多个滤波器及相应的频率和能量;Acquiring multiple filters and corresponding frequencies and energies included in the equalizer algorithm;根据每个滤波器级频率和能量,以及所述目标调整增益,计算每个滤波器的品质因数;Calculate the quality factor of each filter according to the frequency and energy of each filter stage and the target adjustment gain;根据每个滤波器的品质因数,对所述激励信号进行滤波处理,得到目标音频信。According to the quality factor of each filter, the excitation signal is filtered to obtain the target audio signal.
- 如权利要求6所述音频信号调整方法,其特征在于,所述滤波器为IIR滤波器或FIR滤波器。8. The audio signal adjustment method of claim 6, wherein the filter is an IIR filter or an FIR filter.
- 一种音频信号调整装置,其特征在于,所述装置包括:An audio signal adjustment device, characterized in that the device includes:振幅预测模块,用于获取待输入所述微型扬声器的激励信号,并预测所述激励信号输入所述微型扬声器产生的振膜振幅;An amplitude prediction module for obtaining an excitation signal to be input to the micro speaker, and predicting the vibration amplitude of the diaphragm generated when the excitation signal is input to the micro speaker;判断模块,用于判断所述振膜振幅是否超过预设振幅阈值;A judging module for judging whether the amplitude of the diaphragm exceeds a preset amplitude threshold;增益确定模块,用于当所述振膜振幅超过预设振幅阈值时,根据所述振膜振幅和所述预设振幅阈值,确定所述激励信号的振膜振幅降低至小于所述预设振幅阈值时的目标调整增益;A gain determination module, configured to determine that the vibration diaphragm amplitude of the excitation signal is reduced to be less than the preset amplitude according to the vibration diaphragm amplitude and the preset amplitude threshold value when the vibration diaphragm amplitude exceeds the preset amplitude threshold value Target adjustment gain at threshold;信号调整模块,用于利用均衡器算法按照所述目标调整增益对所述激励信号进行调整,得到目标音频信号。The signal adjustment module is used to adjust the excitation signal according to the target adjustment gain by using an equalizer algorithm to obtain a target audio signal.
- 一种计算机设备,其特征在于,包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序,其特征在于,所述处理器执行所述计算机程序时实现权利要求1至7中任一项所述音频信号调整方法的步骤。A computer device, characterized in that it includes a memory, a processor, and a computer program stored on the memory and capable of running on the processor, wherein the processor implements the rights when the computer program is executed. The steps of the audio signal adjustment method described in any one of 1 to 7 are required.
- 一种计算机可读存储介质,其特征在于,包括计算机指令,当所述计算机指令在计算机上运行时,使得计算机执行如权利要求1至7中任一项所述的音频信号调整方法的步骤。A computer-readable storage medium, characterized by comprising computer instructions, which when run on a computer, causes the computer to execute the steps of the audio signal adjustment method according to any one of claims 1 to 7.
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