Charging state adaptive recording noise reduction method and device, equipment and storage medium

Abstract

The application discloses a charging state adaptive recording noise reduction method and device, equipment and a storage medium, and relates to the technical field of charging circuits and audio signal processing. The method comprises the following steps: acquiring charging state information of a recording device and electromagnetic noise information generated during charging; extracting noise spectrum features in the electromagnetic noise information; determining a candidate noise reduction parameter group from a preset parameter library according to the charging state information, and matching or correcting the candidate noise reduction parameter group based on the noise spectrum features to obtain a target noise reduction parameter group; and performing a noise reduction operation on the recording device according to the target noise reduction parameter group. In the foregoing manner, adaptive noise reduction processing is completed on the recording device that is being charged in combination with the charging state information and the electromagnetic noise information, noise that may be generated due to audio mutation caused by changes in the state of the device during charging is solved, and the adaptive noise reduction demand of the recording device is met.

Description

Technical Field

[0001] This application relates to the fields of charging circuits and audio signal processing technology, and in particular to a charging state adaptive recording noise reduction method, apparatus, device and storage medium. Background Technology

[0002] With the increasing popularity of AI-powered recording power banks and magnetic portable power banks, users often wirelessly charge their phones while recording audio using the power bank or mobile device in scenarios such as meetings, interviews, training sessions, and mobile office work. When the wireless charging module is operating, it generates periodic electromagnetic fields, power modulation waveforms, and switching noise. This noise can easily enter the microphone front end, analog amplifier, ADC, or digital audio link through power coupling, spatial magnetic field induction, ground wire return current, and PCB crosstalk, leading to increased recording noise floor, decreased speech clarity, and even affecting the accuracy of subsequent ASR transcription.

[0003] Existing solutions typically address noise reduction in ordinary recordings or use fixed filtering circuits. Fixed-parameter filters struggle to simultaneously achieve both noise suppression and vocal fidelity.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this application is to provide a charging state adaptive recording noise reduction method, apparatus, device, and storage medium, which aims to solve the problem that the sound quality noise reduction effect obtained by conventional fixed noise reduction methods during the recording process is poor due to changes in the charging state and electromagnetic noise generated during the charging process when traditional recording devices are charging and recording simultaneously.

[0006] To achieve the above objectives, this application proposes a charging state adaptive recording noise reduction method, which includes: acquiring the charging state information of the recording device and the electromagnetic noise information generated during charging; extracting the noise spectrum features from the electromagnetic noise information; matching the charging state information and the noise spectrum features with noise reduction parameters in a preset parameter library to obtain a target noise reduction parameter set; and performing noise reduction operation on the recording device according to the target noise reduction parameter set.

[0007] Furthermore, to achieve the above objectives, this application also proposes a recording noise reduction device, which includes: a detection module for acquiring charging status information of the recording device and electromagnetic noise information generated during charging; an analysis and matching module for extracting noise spectrum features from the electromagnetic noise information; matching the charging status information and noise spectrum features with noise reduction parameters in a preset parameter library to obtain a target noise reduction parameter set; and a noise reduction processing module for performing noise reduction operations on the recording device according to the target noise reduction parameter set.

[0008] In addition, to achieve the above objectives, this application also proposes a recording noise reduction device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the charging state adaptive recording noise reduction method as described above.

[0009] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the charging state adaptive recording noise reduction method described above.

[0010] This application proposes an adaptive noise reduction method for recording during charging. The method includes: acquiring charging status information of the recording device and electromagnetic noise information generated during charging; extracting noise spectrum features from the electromagnetic noise information; matching the charging status information and noise spectrum features with noise reduction parameters in a preset parameter library to obtain a target noise reduction parameter set; and performing noise reduction operation on the recording device according to the target noise reduction parameter set. By addressing the problem that conventional noise reduction methods produce poor sound quality during recording when the recording device is simultaneously charging and recording, due to changes in the charging status and electromagnetic noise generated during charging, this application uses different noise reduction combinations based on the charging status information and noise spectrum features to adaptively set noise reduction parameters for the recording device during charging, thereby achieving high-quality noise reduction. Attached Figure Description

[0011] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating the steps of an embodiment of the charging state adaptive recording noise reduction method provided in this application.

[0014] Figure 2 yes Figure 1 A flowchart illustrating the sub-steps of step S3; step S3 also includes the following sub-steps.

[0015] Figure 3 This is a schematic diagram of an embodiment of the audio recording noise reduction device provided in this application.

[0016] Figure 4 This is a schematic diagram of an embodiment of the audio recording noise reduction device provided in this application.

[0017] Figure 5 This is a system architecture diagram of the adaptive recording noise reduction method for charging state provided in this application.

[0018] Figure 6 This is a schematic diagram illustrating the smooth transition of parameters in an embodiment of the charging state adaptive recording noise reduction method provided in this application.

[0019] Figure 7 This is a schematic diagram of noise spectrum feature extraction from an embodiment of the charging state adaptive recording noise reduction method provided in this application.

[0020] Figure 8 This is a flowchart of the noise reduction parameter scheduling and matching process of an embodiment of the charging state adaptive recording noise reduction method provided in this application.

[0021] Figure 9 This is a schematic diagram of a recording and charging linkage protection strategy according to an embodiment of the charging state adaptive recording noise reduction method provided in this application.

[0022] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0024] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0025] The existing technology has the following drawbacks: (i) Fixed noise reduction parameters cannot adapt to various levels of wireless charging noise. The fundamental frequency, harmonics and modulation noise generated at different power levels and protocol stages are significantly different, and fixed low-pass, fixed notch or fixed gain cannot cover all states.

[0026] (ii) Low-frequency modulation components in charging noise overlap with human voice frequency bands. Qi standard wireless charging carries power communication packets during the charging process. For example, charging power communication or modulation processes may generate low-frequency envelopes or modulation noise, which, after coupling, may fall into or affect human voice-related frequency bands. Charging handshakes, power negotiations, and dynamic current limiting generate low-frequency envelopes and modulation noise, which, if relying solely on ordinary low-pass filtering, can easily remain in the human voice frequency band.

[0027] (iii) Traditional microphone noise reduction does not detect the charging circuit status. Most existing audio noise reduction methods are based solely on microphone input signals or software algorithms, without reading information such as the power, protocol, temperature, and charging stage of the wireless charging receiver chip, and therefore cannot select appropriate filtering strategies in advance.

[0028] (iv) Audio abrupt changes may occur when switching charging states. When wireless charging switches from handshake to steady state, from 7.5W to 15W, or when resuming from charging interruption, if the filter parameters change abruptly, it may cause abrupt changes in recording loudness, transient noise, or short-term distortion.

[0029] (v) Relying solely on backend APP software processing will increase latency and computational burden. In low-power mobile power supply devices, if all charging noise is handled by the backend AI noise reduction model, it may lead to additional power consumption, heat generation, and real-time issues.

[0030] (vi) Lack of coordinated control between charging safety and recording quality. Existing technologies typically handle wireless charging and recording separately, failing to coordinate charging power and noise reduction intensity under conditions such as abnormal temperature, low battery recording, and the instant recording starts.

[0031] Therefore, this application provides a method, apparatus, device, and storage medium for adaptive recording noise reduction during charging to solve the above-mentioned problems. This enables the recording device to perform adaptive noise reduction processing during charging, resulting in higher quality audio recording files.

[0032] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or recording device capable of performing the above functions. The following description uses a recording device as an example to illustrate this embodiment and the subsequent embodiments.

[0033] This application provides a charging state-adaptive recording noise reduction method, see below. Figure 1 As shown, Figure 1 This is a schematic flowchart illustrating the steps of an embodiment of the charging state adaptive recording noise reduction method provided in this application; the charging state adaptive recording noise reduction method includes the following steps: Step S1: Obtain the charging status information of the recording device and the electromagnetic noise information generated during charging.

[0034] It should be noted that charging status information refers to various operating status parameters of the recording device during the wireless charging process. In one embodiment, the charging status information includes one or more of the following: charging power level, charging protocol type, charging stage, charging temperature, charging interruption status, charging power change rate, or charging power fluctuation status.

[0035] Specifically, the charging power levels may include different power levels such as 5W, 7.5W, 10W, and 15W; the charging protocol type may include Qi, BPP (Baseline Power Profile), EPP (Extended Power Profile), or proprietary fast charging protocols; and the charging stages may include the handshake stage, steady-state charging stage, fast charging stage, power adjustment stage, standby stage, or charging interruption stage.

[0036] Charging status information can be obtained by communicating with the wireless charging receiver chip via I2C, SPI, GPIO interrupts, or register reads. The wireless charging receiver chip can provide information such as power level, protocol type, rectified voltage, output current, coil temperature, chip temperature, and power negotiation status.

[0037] Additionally, it should be noted that electromagnetic noise information refers to the electromagnetic noise signal generated when the wireless charging module is operating. This electromagnetic noise information can be obtained through a noise sensing branch. The noise sensing branch may include a PCB induction coil, noise sensing traces, a miniature coil, a magnetic field sensor, an auxiliary coil adjacent to the wireless charging coil, or noise characteristics obtained from power supply ripple sampling points. The noise sensing branch may also include a differential amplifier, which is used to perform common-mode suppression and amplification of the sensed electromagnetic noise signal.

[0038] Understandably, different charging protocol types correspond to different operating frequency ranges, power negotiation methods, and modulation characteristics. For example, the Qi / BPP protocol corresponds to lower power levels and a more stable base frequency, while EPP or proprietary fast charging protocols correspond to higher power, more harmonics, and a more pronounced modulation envelope. Therefore, obtaining the charging protocol type helps to accurately match the noise pattern in subsequent steps. Simultaneously, actively collecting electromagnetic noise through an independent noise sensing branch can generate quantifiable noise characteristic inputs, avoiding reliance solely on charging status information for open-loop control.

[0039] Step S2: Extract the noise spectrum features from the electromagnetic noise information.

[0040] It should be noted that noise spectrum characteristics refer to various feature parameters extracted after performing spectrum analysis on the electromagnetic noise signal collected by the noise-inducing branch. Spectrum analysis can be performed using FFT (Fast Fourier Transform), Goertzel algorithm, multi-channel filter banks, energy threshold detection, or noise fingerprint matching algorithms.

[0041] Specifically, noise spectrum characteristics may include one or more of the following: fundamental frequency, harmonic components, peak noise level, modulation envelope, and noise energy distribution. Spectrum analysis can cover the energy detection or peak extraction of fundamental frequency and harmonics within the 100 kHz to 5 MHz frequency band.

[0042] For example, when a wireless charging module is operating, the electromagnetic frequency generated by Qi standard wireless charging is typically between 100kHz and 210kHz. At different power levels, the energy distribution of the fundamental frequency and its harmonics (such as 256kHz, 384kHz, 512kHz, 600kHz, 800kHz, etc.) varies. Furthermore, the power communication packet carried during wireless charging operates within the audible frequency range of 12Hz, generating a low-frequency modulation envelope. Extracting these characteristics through spectrum analysis can provide a quantitative basis for the precise matching of subsequent noise reduction parameters.

[0043] Step S3: Determine the candidate noise reduction parameter group from the preset parameter library based on the charging status information, and match or correct the candidate noise reduction parameter group based on the noise spectrum characteristics to obtain the target noise reduction parameter group.

[0044] It should be noted that the preset parameter library refers to a pre-stored noise characteristic fingerprint library, which stores noise spectrum patterns and recommended noise reduction parameters corresponding to different charging levels, protocol types, and charging stages. The preset parameter library can be generated during the factory calibration stage, or it can be updated during user use based on recording quality feedback, noise measurement results, or device aging.

[0045] The core of this step lies in employing a two-tiered determination mechanism that combines "pre-selected parameter sets based on charging state information with measured correction of noise spectrum characteristics." The target noise reduction parameter set should not be directly determined by a single charging state, but rather by both pre-selected charging states and noise characteristic correction.

[0046] Step S4: Perform noise reduction operation on the recording device according to the target noise reduction parameter set.

[0047] It should be noted that performing noise reduction refers to adjusting various adjustable parameters of the microphone signal link in the recording equipment according to the target noise reduction parameter set. Specifically, real-time noise reduction processing of the microphone signal can be performed through programmable audio noise reduction circuits such as adjustable low-pass filters, programmable notch filters, variable gain amplifiers, noise gates, or audio DSPs.

[0048] In one embodiment, confirming the candidate noise reduction mode and candidate noise reduction parameter group in the preset parameter library based on the charging status information includes: increasing the candidate noise reduction mode level in response to the charging temperature exceeding a first temperature threshold; and / or, confirming the candidate noise reduction mode as the default noise reduction mode and the candidate noise reduction parameter group as the default noise reduction parameter group in response to the recording device being in a charging interruption state; and / or, confirming the candidate noise reduction mode as a deep noise reduction mode and the candidate noise reduction parameter group as a deep noise reduction parameter group in response to the charging handshake phase starting or the charging power level fluctuating, and switching to the noise reduction mode corresponding to the charging power level after the handshake is completed.

[0049] In one embodiment, determining candidate noise reduction parameter groups from a preset parameter library based on charging status information includes: using charging protocol type, charging power level, and charging stage as combined indexes to determine candidate noise patterns and candidate noise reduction parameter groups from a noise feature fingerprint library.

[0050] In response to the problem that the sound quality noise reduction effect obtained by conventional noise reduction methods is poor during the recording process due to changes in the charging state and electromagnetic noise generated during the charging process, this application adopts different noise reduction combinations based on charging state information and noise spectrum characteristics to achieve adaptive noise reduction parameter settings for the recording device during the charging process, so as to achieve a high-quality noise reduction effect.

[0051] In one embodiment, such as Figure 2 As shown, Figure 2 yes Figure 1 A flowchart illustrating the sub-steps of step S3; step S3 also includes the following sub-steps: Step A31: Based on the charging status information, confirm the candidate noise reduction modes and candidate noise reduction parameter groups in the preset parameter library.

[0052] Specifically, the charging protocol type, charging power level, and charging stage are used as combined indices to select candidate noise patterns and corresponding candidate noise reduction parameter sets from the noise feature fingerprint database. For example, when the charging protocol type is detected as Qi / BPP, the power level is 5W, and the charging stage is steady-state charging, the corresponding candidate noise patterns and candidate noise reduction parameter sets are indexed from the fingerprint database.

[0053] Step A32: Match the noise reduction modes with the candidate noise reduction modes based on the noise spectrum characteristics.

[0054] Specifically, the real-time extracted noise fundamental frequency, harmonic components, peak noise level, modulation envelope, and noise energy distribution are matched with candidate noise patterns. The degree of matching between the measured noise characteristics and the candidate patterns is calculated.

[0055] Step A33: In response to a successful match, confirm the candidate noise reduction parameter group as the target noise reduction parameter group; or in response to a failure to match the noise reduction parameters, call the default noise reduction parameters and retain the original recording signal.

[0056] Understandably, when the matching degree reaches a preset threshold, the corresponding candidate noise reduction parameter group is determined as the target noise reduction parameter group. When the measured noise energy is higher than the candidate mode, the notch depth is increased, the noise gate threshold is raised, or the pre-gain is reduced; when the measured noise energy is lower than the candidate mode, the notch depth is reduced or the default gain is restored; when a match cannot be found, the safe default noise reduction parameters are called and the original recording signal is preserved.

[0057] Specifically, when the charging status is detected abnormally, the noise characteristics cannot be matched, or there is no corresponding item in the parameter library, the system calls the safe default noise reduction parameters and retains the original recording data for backend processing. This ensures that the recording function can still work normally under any abnormal circumstances, and will not be interrupted or fail due to the failure of noise reduction parameter matching.

[0058] The target noise reduction parameter set, in one embodiment, may include, but is not limited to, one or more of the following: filtering parameters, notch filtering parameters, gain parameters, noise gate parameters, ADC sampling control parameters, or DSP noise reduction parameters. Specifically: The low-pass filter cutoff frequency can be set to 10kHz, 15kHz, or 20kHz, or continuously adjustable, to suppress high-frequency harmonics while avoiding excessive reduction in speech clarity.

[0059] The notch center frequency can be set to the noise fundamental frequency and its first or multiple harmonic frequencies (e.g., within the range of 100kHz-500kHz) to suppress the wireless charging fundamental frequency and its harmonics; the notch depth can be selected from -20dB to -40dB based on the peak noise level; the preamp gain can be selected as 0dB, -6dB, or -12dB based on the input noise intensity, or continuously adjustable, to avoid front-end saturation or ADC clipping caused by strong noise; the noise gate threshold can be determined based on the current noise floor level plus a preset margin to suppress charging noise in quiet meeting scenarios; the parameter transition time can be set to 10ms-50ms to avoid sudden changes in recording caused by switching charging states; charging power linkage can include strategies such as maintaining, downgrading, or pausing fast charging to reduce electromagnetic interference in recording-priority scenarios.

[0060] Triggering conditions may include changes in charging power level, changes in protocol type, changes in charging stage, noise peak exceeding the threshold, abnormal modulation envelope, abnormal temperature, or sudden power change.

[0061] In one embodiment, the recording noise reduction method further includes: when the recording device is in recording priority mode and the noise spectrum characteristics indicate that the current charging noise energy exceeds the recording quality threshold, reducing the wireless charging power or limiting fast charging.

[0062] Based on the above embodiments, in another embodiment, the recording noise reduction method further includes: in response to a change in charging state information, determining at least one parameter to be adjusted in the target noise reduction parameter group that differs from the current noise reduction parameter group, and gradually adjusting the at least one parameter to be adjusted from its current value to the target value within a preset transition time.

[0063] Specifically, when the charging state is detected to switch from handshake to steady state, from low power to high power, from charging interruption to resumption of charging, or from fast charging to normal charging, the system does not immediately abruptly change the filtering and gain parameters, but gradually adjusts the parameters in a linear, exponential, or piecewise curve manner within a preset transition window.

[0064] In one feasible implementation, the parameter smooth transition includes: identifying at least one parameter in the target noise reduction parameter set that differs from the current noise reduction parameter set; and, within a transition window of 10ms to 50ms, gradually adjusting the at least one parameter to be adjusted from its current value to the target value in a linear, exponential, or piecewise curve manner; wherein the parameter to be adjusted includes one or more of the following: filtering parameters, notch parameters, gain parameters, noise gate parameters, ADC sampling control parameters, or DSP noise reduction parameters.

[0065] The above-described embodiments can prevent users from hearing abrupt changes in loudness, transient pops, or frequency response changes in recordings.

[0066] In one embodiment, by combining backend AI noise reduction, the proposed solution is further subjected to collaborative noise reduction control, as follows: The recording noise reduction method also includes: after performing noise reduction on the recording device, inputting the processed audio signal into an artificial intelligence noise reduction model for secondary noise reduction.

[0067] Specifically, after adaptive filtering, notch filtering, and gain control are completed at the hardware front end, the system can send the processed audio signal to the main control DSP or the AI ​​noise reduction model of the mobile APP for secondary processing. The hardware front end mainly suppresses wireless charging coupling noise and strong interference components, preventing noise from entering the ADC or causing front-end saturation; the back-end AI noise reduction model mainly handles acoustic noise such as ambient noise, reverberation, keyboard sounds, and overlapping human voices. The combination of the two can reduce the burden on the back-end model, reduce the probability of accidentally deleting human voices, and form an end-to-end noise suppression link.

[0068] Taking a 15W magnetic AI recording power bank as an example, the device includes a wireless charging receiving coil, a wireless charging receiving chip, a battery management chip, a main control SoC, a microphone, an audio preamplifier, an ADC, a programmable filter bank, a PCB induction coil, and a BLE communication module. The PCB induction coil is placed in an area close to the wireless charging coil but away from the microphone's analog front end to pick up the wireless charging leakage magnetic field; the differential amplifier amplifies the induced signal and suppresses common-mode interference; the main control SoC performs ADC sampling and spectrum analysis on the noise induced signal and determines the current power level and protocol type based on the status of the wireless charging receiving chip.

[0069] When a phone is placed on a power bank and wireless charging handshake is triggered, the system detects the handshake and broadband noise in the 100-300kHz range. It immediately activates the deep noise cancellation mode, adjusting the preamp gain to -12dB, the notch depth to -40dB, and increasing the noise gate threshold. After the handshake is complete and the phone enters steady-state charging at 7.5W or 10W, the system smoothly switches the parameters to the medium noise cancellation mode based on the spectral characteristics. If the user picks up the phone, interrupting charging, the system disables or reduces the notch after confirming the noise has disappeared and restores the preamp gain to its default value.

[0070] Regarding the relationship between charging power levels and noise reduction parameters, in one embodiment, the following table can be used as a reference:

[0071] In one embodiment, in scenarios such as important meeting recording, low-battery recording, or quiet meeting rooms, if the system identifies that the noise energy corresponding to the current charging level continuously exceeds a threshold and still affects the recording quality after dynamic filtering, it can send a power reduction command to the wireless charging control module to temporarily reduce the 15W fast charging to 10W or 7.5W, and then resume high-power charging after the meeting recording ends or the noise returns to normal. This strategy coordinates the optimization of recording quality and charging efficiency.

[0072] In one embodiment, when a wireless charging handshake or power fluctuation is detected within a preset time after the recording task is started, the sampling period for charging status information and noise spectrum characteristics is shortened, and the target noise reduction parameter combination is re-determined based on the real-time extracted noise spectrum characteristics; if the target noise reduction parameter combination is different from the current parameter combination, a smooth parameter transition is performed. This mechanism focuses on protecting the "recording start protection window + fast recognition + smooth transition," and works in conjunction with noise reduction during the handshake phase without duplication.

[0073] This application also provides a recording noise reduction device 100, such as... Figure 3 As shown, Figure 3 This is a schematic diagram of an embodiment of the audio recording noise reduction device provided in this application; the audio recording noise reduction device 100 includes: a detection module 10, used to acquire charging status information of the recording device and electromagnetic noise information generated during charging; an analysis and matching module 20, used to extract noise spectrum features from the electromagnetic noise information; determine candidate noise reduction parameter groups from a preset parameter library based on the charging status information, and match or correct the candidate noise reduction parameter groups based on the noise spectrum features to obtain a target noise reduction parameter group; and a noise reduction processing module 30, used to perform noise reduction operation on the recording device according to the target noise reduction parameter group.

[0074] The recording noise reduction device 100 provided in this application employs the recording noise reduction method based on charging state adaptation in the above embodiments, which can solve the technical problem of reduced recording quality during wireless charging. Compared with the prior art, the beneficial effects of the recording noise reduction device 100 provided in this application are the same as those of the recording noise reduction method based on charging state adaptation provided in the above embodiments, and other technical features in the recording noise reduction device 100 are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0075] This application provides a recording noise reduction device 200, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the recording noise reduction method based on charging state adaptation in the above embodiments.

[0076] The following is for reference. Figure 4 , Figure 4 This is a structural schematic diagram of an embodiment of the audio recording noise reduction device provided in this application; it shows a structural schematic diagram suitable for implementing the audio recording noise reduction device 200 of the embodiments of this application. In some embodiments of this application, the audio recording noise reduction device 200 is mainly aimed at AI recording power banks, magnetic power banks, wireless charging peripherals with recording function, AI conference recording devices, recording earphone cases, etc.

[0077] In other embodiments, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers may be included, but are not limited to. Figure 4 The audio recording noise reduction device 200 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0078] like Figure 4As shown, the recording noise reduction device 200 may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the recording noise reduction device 200. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007, such as touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008, such as liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003, such as magnetic tapes, hard disks, etc.; and communication devices 1009. The communication device 1009 allows the recording noise reduction device 200 to communicate wirelessly or wiredly with other devices to exchange data. Although the recording noise reduction device 200 with various systems is shown in the figure, it should be understood that it is not required to implement or possess all of the systems shown. More or fewer systems may be implemented alternatively.

[0079] It is understandable that, based on the above-described embodiments and solutions, combined with Figure 5-9 As shown, to better understand the scheme of this application. Specifically, among which... Figure 5 This is a system architecture diagram of the adaptive recording noise reduction method for charging state provided in this application. Figure 6 This is a schematic diagram illustrating the smooth transition of parameters in an embodiment of the charging state adaptive recording noise reduction method provided in this application. Figure 7 This is a schematic diagram of noise spectrum feature extraction from an embodiment of the charging state adaptive recording noise reduction method provided in this application. Figure 8 This is a flowchart of the noise reduction parameter scheduling and matching process of an embodiment of the charging state adaptive recording noise reduction method provided in this application. Figure 9 This is a schematic diagram of a recording and charging linkage protection strategy according to an embodiment of the charging state adaptive recording noise reduction method provided in this application.

[0080] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0081] The audio recording noise reduction device 200 provided in this application employs the audio recording noise reduction method based on charging state adaptation in the above embodiments, which can solve the technical problem of decreased recording quality under wireless charging conditions. Compared with the prior art, the beneficial effects of the audio recording noise reduction device 200 provided in this application are the same as the beneficial effects of the audio recording noise reduction method based on charging state adaptation provided in the above embodiments, and other technical features of the audio recording noise reduction device 200 are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0082] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0083] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the recording noise reduction method based on charging state adaptation in the above embodiments.

[0084] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0085] The aforementioned computer-readable storage medium may be included in the recording noise reduction device 200; or it may exist independently and not be assembled into the recording noise reduction device 200.

[0086] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the recording noise reduction device 200, cause the recording noise reduction device 200 to perform the recording noise reduction method based on charging state adaptation in the above embodiments.

[0087] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0088] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0089] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0090] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described recording noise reduction method based on charging state adaptation, which can solve the technical problem of reduced recording quality during wireless charging. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the recording noise reduction method based on charging state adaptation provided in the above embodiments, and will not be repeated here.

[0091] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for adaptive recording noise reduction in charging state, characterized in that, The recording noise reduction method includes: Acquire the charging status information of the recording device and the electromagnetic noise information generated during charging; Extract the noise spectrum features from the electromagnetic noise information; Based on the charging status information, candidate noise reduction parameter groups are determined from a preset parameter library, and the candidate noise reduction parameter groups are matched or corrected based on the noise spectrum characteristics to obtain the target noise reduction parameter group. The recording device performs noise reduction operation according to the target noise reduction parameter set.

2. The charging state adaptive recording noise reduction method as described in claim 1, characterized in that, The step of performing noise reduction operation on the recording device according to the target noise reduction parameter set includes: adjusting one or more of the following parameters in the microphone signal link of the recording device: filtering parameters, notch parameters, gain parameters, noise gate parameters, ADC sampling control parameters, or DSP noise reduction parameters, according to the target noise reduction parameter set, so as to perform noise reduction processing on the microphone signal.

3. The charging state adaptive recording noise reduction method as described in claim 1, characterized in that, The step of determining candidate noise reduction parameter sets from a preset parameter library based on the charging state information, and matching or correcting the candidate noise reduction parameter sets based on the noise spectrum characteristics to obtain the target noise reduction parameter set includes: Based on the charging status information, the candidate noise reduction modes and candidate noise reduction parameter groups in the preset parameter library are confirmed; Based on the noise spectrum characteristics, match the noise reduction mode with the candidate noise reduction mode; In response to a successful match, the candidate denoising parameter set is confirmed as the target denoising parameter set; Alternatively, in response to a failure to match the noise reduction parameters, the default noise reduction parameters can be invoked while preserving the original recording signal.

4. The charging state adaptive recording noise reduction method as described in claim 3, characterized in that, The step of confirming the candidate noise reduction mode and candidate noise reduction parameter group in the preset parameter library based on the charging status information includes: When the charging temperature exceeds a first temperature threshold, the level of the candidate noise reduction mode is increased; And / or, in response to the recording device being in a charging interruption state, confirm that the candidate noise reduction mode is the default noise reduction mode and the candidate noise reduction parameter group is the default noise reduction parameter group; And / or, in response to the charging phase being in the charging handshake phase or the charging power level fluctuating, the candidate noise reduction mode is confirmed to be the deep noise reduction mode, the candidate noise reduction parameter group is the deep noise reduction parameter group, and after the handshake is completed, the noise reduction mode corresponding to the charging power level is switched according to the steady-state charging power level.

5. The charging state adaptive recording noise reduction method as described in claim 2, characterized in that, The charging status information includes one or more of the following: charging power level, charging protocol type, charging stage, charging temperature, charging interruption status, charging power change rate, or charging power fluctuation status.

6. The charging state adaptive recording noise reduction method as described in claim 3, characterized in that, The step of determining candidate noise reduction parameter groups from a preset parameter library based on the charging status information includes: using charging protocol type, charging power level, and charging stage as combined indexes to determine candidate noise patterns and candidate noise reduction parameter groups from a noise feature fingerprint library.

7. The charging state adaptive recording noise reduction method as described in claim 1, characterized in that, The recording noise reduction method further includes: When the recording device is in recording priority mode, and the noise spectrum characteristics indicate that the current charging noise energy exceeds the recording quality threshold, the wireless charging power is reduced or fast charging is limited.

8. The charging state adaptive recording noise reduction method as described in claim 1, characterized in that, The recording noise reduction method further includes: When the charging status information changes, at least one parameter to be adjusted in the target noise reduction parameter group that differs from the current noise reduction parameter group is identified, and the at least one parameter to be adjusted is gradually adjusted from the current value to the target value within a preset transition time.

9. The charging state adaptive recording noise reduction method as described in claim 1, characterized in that, The recording noise reduction method further includes: After performing noise reduction on the recording device, the processed audio signal is input into the artificial intelligence noise reduction model for secondary noise reduction.

10. A recording noise reduction device, characterized in that, The recording noise reduction device includes: The detection module is used to acquire the charging status information of the recording device and the electromagnetic noise information generated during charging; The analysis and matching module is used to extract the noise spectrum features from the electromagnetic noise information; determine the candidate noise reduction parameter group from the preset parameter library according to the charging state information; and match or correct the candidate noise reduction parameter group based on the noise spectrum features to obtain the target noise reduction parameter group. The noise reduction processing module is used to perform noise reduction operation on the recording device according to the target noise reduction parameter set.

11. A recording noise reduction device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the charging state adaptive recording noise reduction method as described in any one of claims 1 to 9.

12. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the charging state adaptive recording noise reduction method as described in any one of claims 1 to 9.

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