Soft mute control method, device, medium and product for a sound receiving device

Abstract

Embodiments of the present application provide a soft mute control method and device for a radio device, a medium and a product. By extracting the spectral deviation feature and the time domain energy feature of the digital audio signal of the radio device, the spectral deviation feature can reflect the frequency spectrum similarity between the signal and the noise, and the time domain energy feature can reflect the signal strength. Combined with multi-state decision and energy decision, multi-dimensional decision of the signal state is performed to realize accurate identification of the signal state, and then the output gain is dynamically adjusted. Compared with the prior art, not only the signal receiving strength index is relied on for adjustment, but also the problem of large and small sound caused by signal strength fluctuation due to position change is avoided. The spectral deviation feature is used to effectively distinguish between effective signals and noise, improve the accuracy of soft mute decision, and the time domain energy feature is used as auxiliary decision to enhance the reliability of the system in a low energy scene, so that the volume is smooth and continuous, and the user's radio experience is improved as a whole.

Description

Technical Field

[0001] This application relates to the field of audio signal processing technology, and in particular to a soft mute control method, device, medium and product for a radio device. Background Technology

[0002] Mobile phones, car radios, and other terminal devices widely integrate frequency modulation (FM) radio reception, providing users with real-time broadcast reception services. However, because users frequently change their listening location while moving, the FM signal strength fluctuates due to environmental changes. This fluctuation leads to unstable reception signal quality, causing inconsistent playback volume and affecting the user's listening experience.

[0003] In related technologies, the received signal strength indicator (RSSI) is relied upon for FM soft mute control. For example, the volume of the radio playback is adjusted by monitoring the received signal strength of the radio station currently being listened to in real time. When the FM radio station signal strength decreases to a certain level, it triggers the entry into a mute state, and when the FM radio station signal strength increases to a certain level, it triggers the entry into an unmute state.

[0004] However, existing technology is prone to significant fluctuations when the location changes, resulting in inconsistent sound volume and affecting the user's radio reception experience. Summary of the Invention

[0005] This application provides soft mute control, equipment, media, and products for radio equipment, in order to improve the user's radio reception experience.

[0006] In a first aspect, embodiments of this application provide a soft mute control method for a radio device, comprising:

[0007] Acquire digital audio signals from the radio recording device;

[0008] The digital audio signal is subjected to feature extraction processing to obtain spectral deviation features and temporal energy features;

[0009] The first signal state is determined based on the spectral deviation characteristics and the preset multi-state decision logic;

[0010] The second signal state is determined based on the time-domain energy characteristics and the preset energy decision logic;

[0011] The digital audio signal of the radio device is adjusted according to the first signal state and / or the second signal state to achieve soft mute control for the radio device.

[0012] This application provides a soft mute control method for a radio receiver. First, it extracts the spectral deviation and temporal energy characteristics of the digital audio signal from the receiver. The spectral deviation reflects the spectral similarity between the signal and noise, while the temporal energy reflects the signal strength. Using these two characteristics, combined with multi-state and energy-based decision-making, a multi-dimensional decision on the signal state is made, achieving accurate identification of the signal state and dynamically adjusting the output gain. Compared to existing technologies, this method does not rely solely on a single signal reception strength index for adjustment, avoiding the problem of fluctuating sound volume caused by signal strength fluctuations due to location changes. It effectively distinguishes between valid signals and noise using spectral deviation characteristics, improving the accuracy of soft mute decision-making. Furthermore, it combines temporal energy characteristics as an auxiliary decision-making tool, enhancing the system's reliability in low-energy scenarios, ensuring smooth and continuous volume, and improving the overall user's radio reception experience.

[0013] Optionally, the preset multi-state decision logic includes a first threshold, a second threshold, a first state, a second state, and a third state; wherein the first threshold is higher than the second threshold, the first state corresponds to a valid signal state, the second state corresponds to a transitional signal state, and the third state corresponds to a noisy signal state.

[0014] Accordingly, determining the first signal state based on the spectral deviation characteristics and the preset multi-state decision logic includes:

[0015] Obtain the current state of the digital audio signal;

[0016] Based on the comparison results between the spectral deviation characteristics and the first threshold and the second threshold, and in conjunction with the current state, a state transition decision is executed to obtain the first signal state.

[0017] This application provides an accurate multi-state decision method. It introduces three states and dual thresholds into the multi-state decision logic and makes transition decisions based on the current state. By introducing intermediate transition states, it smooths state transitions when signal quality changes, reducing frequent switching. At the same time, the dual threshold mechanism provides a hysteresis effect, enhancing the anti-interference capability against noise. Combined with the introduction of the current state, the decision result is continuous, further reducing sudden changes in volume and improving the user's radio reception experience.

[0018] Optionally, the preset multi-state decision logic further includes multiple counting thresholds;

[0019] Accordingly, the step of performing a state transition decision based on the comparison results of the spectral deviation feature with the first threshold and the second threshold, combined with the current state, to obtain the first signal state includes:

[0020] Based on the comparison results between the spectral deviation characteristics and the first threshold and the second threshold, the counting threshold is used as a transition delay constraint, and combined with the current state, a state transition decision is executed to obtain the first signal state.

[0021] In this embodiment, multiple counting thresholds are introduced into the preset multi-state decision logic. These thresholds serve as delay constraints for state transitions. This setting ensures that state transitions not only depend on the feature values ​​of the current frame but also meet the continuous counting condition. This effectively suppresses erroneous state transitions caused by instantaneous noise or feature fluctuations. Through delay constraints, state transitions are ensured to be based on statistical results over a period of time, avoiding the auditory discomfort of fluctuating sound volume. Furthermore, setting independent counting thresholds for different state transitions achieves a refined control strategy. By setting multiple counting thresholds, sound jumps can be effectively reduced.

[0022] Optionally, the step of using the counting threshold as a transition delay constraint based on the comparison result between the spectral deviation feature and the first threshold and the second threshold, and combining it with the current state to perform a state transition decision to obtain the first signal state, includes:

[0023] When the current state is the third state, if the spectral deviation feature is not less than the first threshold, then the first signal state is switched to the first state; if the spectral deviation feature is between the second threshold and the first threshold, then based on the comparison result of the first count value and the first count threshold, it is determined whether to switch the first signal state to the second state or maintain the third state; if the spectral deviation feature is not greater than the second threshold, then the first signal state is maintained as the third state and the first count value is updated.

[0024] When the current state is the second state, if the spectral deviation feature is not less than the first threshold, the first signal state is switched to the first state; if the spectral deviation feature is not greater than the second threshold, the first signal state is switched to the third state or maintained in the second state is determined based on the comparison result of the second count value and the second count threshold; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is maintained in the second state.

[0025] When the current state is the first state, if the spectral deviation feature is not greater than the second threshold, the first signal state is switched to the second state; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is switched to the second state or maintained in the first state is determined according to the comparison result of the third count value and the third count threshold; if the spectral deviation feature is not less than the first threshold, the first signal state is maintained in the first state.

[0026] Here, this application embodiment provides specific state transition logic for different current states. Starting from three different current states, the transition logic differs under different threshold intervals, and the constraints of the counting threshold are clearly defined. Through detailed multi-scenario logic branches, comprehensive coverage of various signal change scenarios is achieved, enabling efficient and accurate dynamic state judgment, thereby solving the sound jump problem, improving reception stability, and further enhancing the user's reception experience.

[0027] Optionally, adjusting the digital audio signal of the radio receiver according to the first signal state and / or the second signal state includes:

[0028] Based on the first signal state and / or the second signal state, a corresponding gain adjustment mode is determined; wherein, the gain adjustment mode includes a mute mode and a non-mute mode;

[0029] The target signal gain is determined according to the gain adjustment mode; wherein the gain adjustment mode includes a first signal gain corresponding to the mute mode and a second signal gain corresponding to the non-mute mode;

[0030] According to the target signal gain, the digital audio signal is subjected to smooth gain adjustment; wherein, the smooth gain adjustment includes: when switching from non-mute mode to mute mode, gradually reducing the gain to the first signal gain; when switching from mute mode to non-mute mode, gradually increasing the gain to the second signal gain.

[0031] Here, the embodiments of this application can determine the target signal gain according to the signal state. Specifically, for the gain adjustment in the silent mode, the gain is gradually reduced, and for the adjustment in the non-silent mode, the gain is gradually increased. By gradually adjusting different gain adjustment modes, smooth sound adjustment is achieved. By adopting a smooth gain adjustment strategy, the gain is gradually adjusted to the target value when switching modes to avoid sudden gain changes. This can effectively reduce the occurrence of sudden changes in volume and improve the user's radio reception experience.

[0032] Optionally, the feature extraction process on the digital audio signal to obtain spectral deviation features and temporal energy features includes:

[0033] The digital audio signal is preprocessed to obtain a preprocessed digital audio signal; wherein the preprocessing includes at least one of the following: transsampling processing, signal overlap framing processing, pre-emphasis processing, and windowing processing.

[0034] The preprocessed digital audio signal is subjected to spectral deviation feature extraction processing to obtain spectral deviation features;

[0035] The preprocessed digital audio signal is subjected to time-domain energy feature extraction processing to obtain time-domain energy features.

[0036] In this embodiment, when extracting features of spectral deviation and temporal energy, the digital audio signal is first preprocessed using at least one of the following methods: transsampling, signal overlap framing, pre-emphasis, and windowing. Transsampling reduces computational complexity and adapts to the computing power of different platforms; overlap framing ensures inter-frame continuity and avoids frame boundary effects; pre-emphasis enhances high-frequency components and improves the distinguishability of spectral features; and windowing reduces spectral leakage and improves the accuracy of spectral analysis. Through these preprocessing steps, the accuracy of feature processing is improved, making feature extraction more stable and reliable, laying the foundation for subsequent decision-making, and thus improving the sound reception effect.

[0037] Optionally, the step of performing spectral deviation feature extraction processing on the preprocessed digital audio signal to obtain spectral deviation features includes:

[0038] The preprocessed digital audio signal is subjected to a short-time Fourier transform to obtain the spectrum;

[0039] Calculate the amplitude spectrum based on the given spectrum;

[0040] The spectral deviation characteristics are calculated based on the amplitude spectrum and the preset frequency modulation noise spectrum template.

[0041] This application embodiment utilizes frequency domain analysis to capture the difference between signal and noise, performs short-time Fourier transform on the preprocessed signal to obtain the spectrum, then calculates the amplitude spectrum, and compares it with a preset frequency modulation noise spectrum template to obtain spectral deviation features, thereby achieving accurate extraction of spectral deviation features.

[0042] Secondly, embodiments of this application provide a soft mute control device for a radio device, including: a memory and a processor;

[0043] The memory stores computer-executed instructions;

[0044] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0045] Thirdly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0046] Fourthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0047] The soft mute control method, electronic device, medium, and product for a radio recording device provided in this application extract the spectral deviation features and time-domain energy features of the digital audio signal from the radio recording device. The spectral deviation features reflect the spectral similarity between the signal and noise, while the time-domain energy features reflect the signal strength. By combining these two features with multi-state decision and energy decision, a multi-dimensional decision on the signal state is made, achieving accurate identification of the signal state and dynamically adjusting the output gain. Compared with existing technologies, this method does not rely solely on a single signal reception strength index for adjustment, avoiding the problem of fluctuating sound volume caused by signal strength fluctuations due to location changes. It effectively distinguishes between valid signals and noise using spectral deviation features, improving the accuracy of soft mute decision. Furthermore, by combining time-domain energy features as an auxiliary decision, it enhances the reliability of the system in low-energy scenarios, ensuring smooth and continuous volume and improving the overall user's radio recording experience. Attached Figure Description

[0048] 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.

[0049] Figure 1 This application provides a schematic diagram of a soft mute control system architecture for a radio device.

[0050] Figure 2 Flowchart of the soft mute control method for the radio device provided in this application Figure 1 ;

[0051] Figure 3 A schematic diagram illustrating a digital audio signal processing procedure provided in an embodiment of this application;

[0052] Figure 4 A schematic diagram of a state transition process with three states and two thresholds provided in this application embodiment;

[0053] Figure 5 A schematic diagram of the soft mute control device for a radio device provided in this application embodiment. Figure 1 ;

[0054] Figure 6 A schematic diagram of the structure of a soft mute control device for a radio device provided in this application embodiment. Figure 2 ;

[0055] Figure 7 This is a schematic diagram of the structure of a soft mute control device for a radio device provided in an embodiment of this application.

[0056] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0057] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0058] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0059] Mobile phones, car radios, and other terminal devices widely integrate FM radio functionality, providing users with real-time broadcast reception services. Conventional FM soft mute methods adjust the playback volume by monitoring the signal strength of the currently received radio station. Mute is triggered when the FM signal strength decreases to a certain level, and unmute is triggered when the signal strength increases to a certain level. However, this method relies on the RSSI index, which is prone to significant fluctuations when the location changes, leading to inconsistent volume and negatively impacting the user's listening experience.

[0060] One common soft mute control method involves acquiring the current AM radio station signal quality, determining the usage scenario, and adjusting the signal modulation parameters accordingly to reduce noise and improve playback quality. Another method compares the radio station signal quality to a preset threshold; if the conditions are met, the sound output volume is attenuated to reduce the impact of environmental changes and safety hazards. Yet another method assesses signal strength and whether the audio signal is noise. If the signal is weak or indistinguishable but noise is present, the car audio system is turned off, improving noise detection accuracy and user experience. All of these methods rely solely on RSSI (Radio Frequency Indicator) for soft mute control, which is prone to significant fluctuations when location changes, resulting in inconsistent volume and negatively impacting the user's listening experience.

[0061] To address the aforementioned technical problems, embodiments of this application provide a soft mute control method, device, medium, and product for a radio receiver. The method extracts the spectral deviation characteristics and temporal energy characteristics of the digital audio signal from the radio receiver. By combining these two characteristics with multi-state decision and energy decision, a multi-dimensional decision on the signal state is made, thereby achieving accurate identification of the signal state and dynamically adjusting the output gain.

[0062] In this embodiment, FM soft mute control is performed through audio signal processing methods, without relying on the RSSI index of the radio, thereby avoiding the problem of fluctuating volume caused by relying on the RSSI index and improving the user's radio reception experience.

[0063] Optionally, in this application embodiment, the spectral deviation and time-domain energy characteristics of the FM input digital signal are mainly extracted through audio signal processing, and the FM gain is dynamically adjusted by combining three-state dual-threshold decision and time-domain energy decision methods to improve the robustness of FM soft mute.

[0064] The embodiments of this application can be applied to various devices equipped with radio functions, including mobile phone radios, car radios, and other product forms. The technical solution remains the same when applied to different types of products.

[0065] This application provides a soft mute control method for a radio device, which is applied to a terminal device / base station, or a chip or chip module in a terminal device / base station. This application does not impose specific limitations on this method.

[0066] Optional, Figure 1 This is a schematic diagram of a soft mute control system architecture for a radio device provided in an embodiment of this application. The soft mute control system for this radio device can be a computer device. Figure 1 In the above architecture, at least one of data acquisition device 101, processing device 102 and display device 103 is included.

[0067] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the architecture of the soft mute control system for a radio device. In other feasible embodiments of this application, the above architecture may include more or fewer components than illustrated, or combine some components, or divide some components, or arrange different components, which can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown can be implemented in hardware, software, or a combination of both.

[0068] In the specific implementation process, the data acquisition device 101 may include an input / output interface or a communication interface, and the data acquisition device 101 can be connected to the processing device through the input / output interface or the communication interface.

[0069] The processing device 102 can extract the spectral deviation characteristics and temporal energy characteristics of the digital audio signal from the radio receiver. By combining these two characteristics with multi-state decision and energy decision, it can make multi-dimensional decisions on the signal state, achieve accurate identification of the signal state, and then dynamically adjust the output gain.

[0070] The display device 103 can also be a touch screen or the screen of a terminal device, used to receive user commands while displaying the above-mentioned content, so as to realize interaction with the user.

[0071] It should be understood that the aforementioned processing device can be implemented by a processor reading instructions from memory and executing those instructions, or it can be implemented by a chip circuit.

[0072] Furthermore, the network architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0073] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0074] Figure 2 Flowchart of the soft mute control method for the radio device provided in this application Figure 1 ,like Figure 2 As shown, the method includes:

[0075] S201: Acquire digital audio signals from the radio equipment.

[0076] Optionally, the recording device can be monitored in real time to obtain digital audio signals.

[0077] S202: Perform feature extraction processing on the digital audio signal to obtain spectral deviation features and time-domain energy features.

[0078] Optionally, the feature extraction processing of the digital audio signal to obtain spectral deviation features and temporal energy features includes: preprocessing the digital audio signal to obtain a preprocessed digital audio signal; wherein the preprocessing includes at least one of transsampling processing, signal overlap framing processing, pre-emphasis processing, and windowing processing; performing spectral deviation feature extraction processing on the preprocessed digital audio signal to obtain spectral deviation features; and performing temporal energy feature extraction processing on the preprocessed digital audio signal to obtain temporal energy features.

[0079] In this embodiment, when extracting features of spectral deviation and temporal energy, the digital audio signal is first preprocessed using at least one of the following methods: transsampling, signal overlap framing, pre-emphasis, and windowing. Transsampling reduces computational complexity and adapts to the computing power of different platforms; overlap framing ensures inter-frame continuity and avoids frame boundary effects; pre-emphasis enhances high-frequency components and improves the distinguishability of spectral features; and windowing reduces spectral leakage and improves the accuracy of spectral analysis. Through these preprocessing steps, the accuracy of feature processing is improved, making feature extraction more stable and reliable, laying the foundation for subsequent decision-making, and thus improving the sound reception effect.

[0080] Optionally, the spectral deviation feature extraction process is performed on the preprocessed digital audio signal to obtain the spectral deviation feature, including: performing a short-time Fourier transform on the preprocessed digital audio signal to obtain the spectrum; calculating the amplitude spectrum based on the spectrum; and calculating the spectral deviation feature based on the amplitude spectrum and a preset frequency modulation noise spectrum template.

[0081] This application embodiment utilizes frequency domain analysis to capture the difference between signal and noise, performs short-time Fourier transform on the preprocessed signal to obtain the spectrum, then calculates the amplitude spectrum, and compares it with a preset frequency modulation noise spectrum template to obtain spectral deviation features, thereby achieving accurate extraction of spectral deviation features.

[0082] Optionally, before feature extraction, embodiments of this application may also perform feature smoothing processing to improve the accuracy of digital audio signal feature extraction.

[0083] Optionally, sliding window smoothing or exponential weighted smoothing can be used, with the output spectral bias smoothing feature serving as the input feature of the three-state dual-threshold decision submodule; the output temporal energy smoothing feature serves as the input feature of the temporal energy decision submodule.

[0084] S203: Determine the first signal state based on the spectral deviation characteristics and the preset multi-state decision logic.

[0085] S204: Determine the second signal state based on the time-domain energy characteristics and the preset energy decision logic.

[0086] S205: Adjust the digital audio signal of the radio device according to the first signal state and / or the second signal state to achieve soft mute control for the radio device.

[0087] This application provides a soft mute control method for a radio receiver. First, it extracts the spectral deviation and temporal energy characteristics of the digital audio signal from the receiver. The spectral deviation reflects the spectral similarity between the signal and noise, while the temporal energy reflects the signal strength. Using these two characteristics, combined with multi-state and energy-based decision-making, a multi-dimensional decision on the signal state is made, achieving accurate identification of the signal state and dynamically adjusting the output gain. Compared to existing technologies, this method does not rely solely on a single signal strength index for adjustment, avoiding the problem of fluctuating volume caused by signal strength fluctuations due to location changes. It effectively distinguishes between valid signals and noise using spectral deviation characteristics, improving the accuracy of soft mute decision-making. Furthermore, combining temporal energy characteristics as an auxiliary decision enhances the system's reliability in low-energy scenarios, ensuring smooth and continuous volume and improving the overall user's radio reception experience.

[0088] Optionally, the digital audio signal of the radio receiver is adjusted according to the first signal state and / or the second signal state, including:

[0089] Based on the first signal state and / or the second signal state, a corresponding gain adjustment mode is determined; wherein the gain adjustment mode includes a mute mode and a non-mute mode; based on the gain adjustment mode, a target signal gain is determined; wherein the gain adjustment mode includes a first signal gain corresponding to the mute mode and a second signal gain corresponding to the non-mute mode; based on the target signal gain, a smooth gain adjustment is performed on the digital audio signal; wherein the smooth gain adjustment includes: when switching from a non-mute mode to a mute mode, gradually decreasing the gain to the first signal gain; when switching from a mute mode to a non-mute mode, gradually increasing the gain to the second signal gain.

[0090] Here, the embodiments of this application can determine the target signal gain according to the signal state. Specifically, for the gain adjustment in the silent mode, the gain is gradually reduced, and for the adjustment in the non-silent mode, the gain is gradually increased. By gradually adjusting different gain adjustment modes, smooth sound adjustment is achieved. By adopting a smooth gain adjustment strategy, the gain is gradually adjusted to the target value when switching modes to avoid sudden gain changes. This can effectively reduce the occurrence of sudden changes in volume and improve the user's radio reception experience.

[0091] Optionally, Figure 3 This is a schematic diagram illustrating a digital audio signal processing procedure provided in an embodiment of this application, as shown below. Figure 3 As shown, in conjunction with the soft mute control method of the above-mentioned radio equipment, the embodiment of this application first inputs a digital audio signal, which can be an FM digital signal. After transsampling, signal preprocessing, feature extraction, feature smoothing, three-state dual-threshold decision and time-domain energy decision, gain control is finally executed, and the controlled digital audio signal is finally output. The controlled digital audio signal can meet the user's radio reception needs.

[0092] Optionally, the input FM digital signal is sampled at a common audio sampling rate (e.g., 48kHz), and then framed (without overlap) according to the FM soft mute decision logic (e.g., Figure 3 The FM soft mute flag (FM_Softmute_flag) obtained (shown by the dashed line in the middle) is used for FM gain control. The FM soft mute decision logic consists of 6 sub-modules corresponding to transsampling, signal preprocessing, feature extraction, feature smoothing, three-state dual-threshold decision, and time-domain energy decision.

[0093] In one possible implementation, the submodule corresponding to the transsampling is responsible for processing the input FM digital signal. Switch to sampling rate signal For example, sampling rate It is 8kHz.

[0094] In one possible implementation, the submodule corresponding to signal preprocessing can be used for signal overlap framing, pre-emphasis, and windowing processing, wherein:

[0095] The signal output by the submodule corresponding to the reverse sampling Overlapping frames are performed to obtain the overlapped frame signal. Frame length is The frame shift is less than the frame length.

[0096] Overlapping frame signals For pre-emphasis, a first-order high-pass filter can be used:

[0097]

[0098] Then use window functions. Add a window:

[0099]

[0100] The signal preprocessing output signal, i.e., the preprocessed digital audio signal described above, is defined as follows: , This is the pre-emphasized signal. It is a time series sequence number. This is the frame index. Here, n and m are any positive integers.

[0101] Optionally, the submodule corresponding to feature extraction is used to extract spectral bias features and temporal energy features, specifically as follows:

[0102] First of all The time-domain energy is calculated as follows:

[0103]

[0104] in, This represents the temporal energy of the m-th frame.

[0105] Then, the signal is preprocessed and output as a signal. The spectrum is obtained by performing a Short-Time Fourier Transform (STFT). , The frequency index representing the STFT domain, selecting the index for a specific frequency range. The formula for calculating spectral deviation is defined as follows (for convenience, the frame index m is omitted):

[0106] Amplitude spectrum:

[0107] Amplitude-averaged spectrum:

[0108] Amplitude spectrum variance:

[0109] Amplitude spectral covariance:

[0110] Spectral deviation

[0111] in, The spectral template representing FM noise within the specific frequency range mentioned above can be obtained by fitting the measured FM noise spectrum. .

[0112] Corresponding amplitude average spectrum .

[0113] Corresponding amplitude spectrum variance .

[0114] in, The normalization coefficient representing the spectral bias.

[0115] Optionally, the sub-module corresponding to feature smoothing in this embodiment can use any smoothing method such as sliding window smoothing or exponential weighted smoothing, and this embodiment does not impose any specific restrictions on it.

[0116] The following is combined with Figure 3 The following is a detailed explanation of step S203 in the above embodiments:

[0117] Optionally, the preset multi-state decision logic includes a first threshold, a second threshold, a first state, a second state, and a third state; wherein the first threshold is higher than the second threshold, the first state corresponds to the signal valid state, the second state corresponds to the signal transition state, and the third state corresponds to the signal noise state; accordingly, based on the spectral deviation characteristics and the preset multi-state decision logic, the first signal state is determined, including:

[0118] Obtain the current state of the digital audio signal; based on the comparison results of the spectral deviation characteristics with the first threshold and the second threshold, and combined with the current state, perform a state transition decision to obtain the first signal state.

[0119] This application provides an accurate multi-state decision method. It introduces three states and dual thresholds into the multi-state decision logic and makes transition decisions based on the current state. By introducing intermediate transition states, it smooths state transitions when signal quality changes, reducing frequent switching. At the same time, the dual threshold mechanism provides a hysteresis effect, enhancing the anti-interference capability against noise. Combined with the introduction of the current state, the decision result is continuous, further reducing sudden changes in volume and improving the user's radio reception experience.

[0120] Optionally, the preset multi-state decision logic also includes multiple counting thresholds; correspondingly, based on the comparison results of the spectral deviation features with the first threshold and the second threshold, and combined with the current state, a state transition decision is executed to obtain the first signal state, including: based on the comparison results of the spectral deviation features with the first threshold and the second threshold, using the counting threshold as a transition delay constraint, and combined with the current state, executing a state transition decision to obtain the first signal state.

[0121] In this embodiment, multiple counting thresholds are introduced into the preset multi-state decision logic. These thresholds serve as delay constraints for state transitions. This setting ensures that state transitions not only depend on the feature values ​​of the current frame but also meet the continuous counting condition. This effectively suppresses erroneous state transitions caused by instantaneous noise or feature fluctuations. Through delay constraints, state transitions are ensured to be based on statistical results over a period of time, avoiding the auditory discomfort of fluctuating sound volume. Furthermore, setting independent counting thresholds for different state transitions achieves a refined control strategy. By setting multiple counting thresholds, sound jumps can be effectively reduced.

[0122] Optionally, based on the comparison results of the spectral deviation characteristics with the first threshold and the second threshold, the counting threshold is used as a transition delay constraint. Combined with the current state, a state transition decision is executed to obtain the first signal state, including:

[0123] When the current state is the third state, if the spectral deviation feature is not less than the first threshold, the first signal state is switched to the first state; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is switched to the second state or maintained in the third state based on the comparison result of the first count value and the first count threshold; if the spectral deviation feature is not greater than the second threshold, the first signal state is maintained in the third state and the first count value is updated.

[0124] When the current state is the second state, if the spectral deviation feature is not less than the first threshold, the first signal state is switched to the first state; if the spectral deviation feature is not greater than the second threshold, the first signal state is switched to the third state or maintained in the second state based on the comparison result of the second count value and the second count threshold; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is maintained in the second state.

[0125] When the current state is the first state, if the spectral deviation feature is not greater than the second threshold, the first signal state is switched to the second state; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is switched to the second state or maintained in the first state is determined according to the comparison result of the third count value and the third count threshold; if the spectral deviation feature is not less than the first threshold, the first signal state is maintained in the first state.

[0126] Here, this application embodiment provides specific state transition logic for different current states. Starting from three different current states, the transition logic differs under different threshold intervals, and the constraints of the counting threshold are clearly defined. Through detailed multi-scenario logic branches, comprehensive coverage of various signal change scenarios is achieved, enabling efficient and accurate dynamic state judgment, thereby solving the sound jump problem, improving reception stability, and further enhancing the user's reception experience.

[0127] Optionally, Figure 4 This is a schematic diagram illustrating a state transition process with a three-state dual-threshold decision mechanism, provided as an embodiment of this application. Figure 4 As shown, the submodule corresponding to the three-state dual-threshold decision uses two high and low thresholds, three states, and four maximum counts constraining the three state transitions to make decisions on the input features and outputs the FM_Softmute_flag signal.

[0128] The two thresholds include a high threshold (high_threshold) used to represent the upper limit threshold of the three-state dual-threshold decision and a low threshold (low_threshold) used to represent the lower limit threshold of the three-state dual-threshold decision.

[0129] The three states are: FM noise state (FM_NOISE), FM transition state (FM_TRANS), and FM signal state (FM_SIG).

[0130] Optionally, the multiple counting thresholds are four maximum counts, including the maximum count for noise hold-up (noise2noise_cnt_max), the maximum count for noise transition (noise2trans_cnt_max), the maximum count for transition to noise (trans2noise_cnt_max), and the maximum count for signal transition (sig2trans_cnt_max).

[0131] It is understood that the above three-state dual-threshold decision logic and the corresponding thresholds are illustrative, and the embodiments of this application do not impose specific limitations in the actual implementation process.

[0132] Reference Figure 4 M1 to M9 represent the conditions and operations for state transitions.

[0133] M1: Transition from FM_NOISE state to FM_SIG state.

[0134] M2: Transition from FM_NOISE state to FM_TRANS state.

[0135] M3: Maintain FM_NOISE state.

[0136] M4: Transition from FM_TRANS state to FM_SIG state.

[0137] M5: Transition from FM_TRANS state to FM_NOISE state.

[0138] M6: Maintain FM_TRANS state.

[0139] M7: Transition from FM_SIG state to FM_TRANS state.

[0140] M8: Transition from FM_SIG state to FM_NOISE state.

[0141] M9: Maintain FM_SIG state.

[0142] In one possible implementation, FM_Softmute_flag can set different working levels according to different state transitions. The simplest way is to set two levels, one level to indicate entering the mute state and the other level to indicate entering the unmute state.

[0143] In some embodiments, a preferred scheme for state transitions applicable to the above-described three-state dual-threshold decision is as follows:

[0144] M1 (transition from FM_NOISE state to FM_SIG state): If the input feature is not less than high_threshold, reset noise2trans_cnt and noise2noise_cnt, and transition to FM_SIG state.

[0145] M2 (transition from FM_NOISE state to FM_TRANS state): If the feature input is between high_threshold and low_threshold, then reset noise2noise_cnt. And if noise2trans_cnt plus 1 is greater than noise2trans_cnt_max, then reset noise2trans_cnt and transition to FM_TRANS state.

[0146] M3 (Maintains FM_NOISE state. Satisfies either condition 1 or condition 2):

[0147] Condition 1: If the feature input is between high_threshold and low_threshold, then reset noise2noise_cnt, and if noise2trans_cnt plus 1 is not greater than noise2trans_cnt_max, maintain the FM_NOISE state.

[0148] Condition 2: If the feature input is less than low_threshold, then reset noise2trans_cnt, maintain the FM_NOISE state, and if noise2noise_cnt plus 1 is greater than noise2noise_cnt_max, then set noise2noise_cnt to noise2noise_cnt_max.

[0149] M4 (Transition from FM_TRANS state to FM_SIG state): If the feature input is not less than high_threshold, reset trans2trans_cnt and transition to FM_SIG state.

[0150] M5 (transition from FM_TRANS state to FM_NOISE state): If the feature input is less than low_threshold and trans2noise_cnt plus 1 is greater than trans2noise_cnt_max, then reset noise2trans_cnt and transition to FM_NOISE state.

[0151] M6 (Maintain FM_TRANS state. Condition 3 or condition 4 is met):

[0152] Condition 3: If the feature input is between high_threshold and low_threshold, then reset trans2noise_cnt and maintain the FM_TRANS state.

[0153] Condition 4: If the feature input is less than low_threshold and trans2noise_cnt plus 1 is not greater than trans2noise_cnt_max, then maintain the FM_TRANS state.

[0154] M7 (Transitions from FM_SIG state to FM_TRANS state. Condition 5 or 6 is satisfied):

[0155] Condition 5: If the feature input is between high_threshold and low_threshold and sig2trans_cnt plus 1 is greater than sig2trans_cnt_max, then reset sig2trans_cnt and enter the FM_TRANS state.

[0156] Condition 6: If the feature input is less than low_threshold, reset sig2trans_cnt and switch to FM_TRANS state.

[0157] M8 (transition from FM_SIG state to FM_NOISE state): Deprecated.

[0158] M9 (Maintain FM_SIG state): Condition 7 or condition 8 is met.

[0159] Condition 7: If the feature input is not less than high_threshold, then reset sig2trans_cnt and maintain the FM_SIG state.

[0160] Condition 8: If the feature input is between high_threshold and low_threshold and sig2trans_cnt plus 1 is not greater than sig2trans_cnt_max, then maintain the FM_SIG state.

[0161] In some possible implementations, combined with the above three-state dual-threshold decision logic, the decision logic of the sub-module corresponding to the time-domain energy decision is as follows: when the time-domain energy smoothing feature is less than time_energy_threshold, FM_Softmute_flag can be set to indicate entering the unmute state.

[0162] In some possible implementations, combined with the above three-state dual-threshold decision logic, the control logic of the sub-module corresponding to FM gain control is as follows: dynamically adjust the gain applied to the input signal in real time according to the input FM_Softmute_flag signal. Taking FM_Softmute_flag, which corresponds to the mute mode, as an example, when FM_Softmute_flag indicates entering the mute state, the gain is gradually reduced to the set target gain of the mute state. When FM_Softmute_flag indicates entering the unmute state, the gain is gradually increased to the set target gain of the unmute state.

[0163] Optionally, embodiments of this application also provide a soft mute control device for a radio device, correspondingly, Figure 5 A schematic diagram of the soft mute control device for a radio device provided in this application embodiment. Figure 1 ,like Figure 5As shown, the software FM softmute control module runs on the audio co-processor platform. The application processor sends parameters to control the algorithm parameters of the software FM softmute control module on the audio processor. It can work in conjunction with the hardened hardware FM softmute control module to improve the overall effect of FM softmute. Alternatively, it can bypass the hardware FM softmute control module through registers, inputting the FM demodulated digital signal into the software FM softmute control module for processing. This effectively replaces the hardware FM softmute control module with the software FM softmute control module, addressing the shortcomings of the hardware FM softmute control module. Both methods ultimately result in playback via the audio codec. Compared to the alternative method of enabling and disabling the hardware FM soft mute control module, the difference lies in whether or not the audio coprocessor handles the software processing. Alternatively, the software FM soft mute control module can be hardware-based, in which case its output is directly played through the audio codec.

[0164] Figure 6 A schematic diagram of the structure of a soft mute control device for a radio device provided in this application embodiment. Figure 2 ,like Figure 6 As shown, the apparatus provided in this application embodiment includes: an acquisition module 601, an extraction module 602, a first determination module 603, a second determination module 604, and an adjustment module 605. The soft mute control device for the radio equipment here can be the soft mute control system of the radio equipment itself, or a chip or integrated circuit that implements the processing device function in the soft mute control system of the radio equipment. It should be noted that the division of the acquisition module 601, extraction module 602, first determination module 603, second determination module 604, and adjustment module 605 is only a logical functional division; physically, they can be integrated or independent.

[0165] The acquisition module is used to acquire the digital audio signal from the radio receiving device.

[0166] The extraction module is used to perform feature extraction processing on digital audio signals to obtain spectral deviation features and temporal energy features;

[0167] The first determining module is used to determine the first signal state based on the spectral deviation characteristics and the preset multi-state decision logic;

[0168] The second determining module is used to determine the second signal state based on the time-domain energy characteristics and the preset energy decision logic;

[0169] The adjustment module is used to adjust the digital audio signal of the radio device according to the first signal state and / or the second signal state in order to achieve soft mute control for the radio device.

[0170] Optionally, the preset multi-state decision logic includes a first threshold, a second threshold, a first state, a second state, and a third state; wherein, the first threshold is higher than the second threshold, the first state corresponds to the signal valid state, the second state corresponds to the signal transition state, and the third state corresponds to the signal noise state.

[0171] Accordingly, the first determining module is specifically used for:

[0172] Obtain the current state of the digital audio signal;

[0173] Based on the comparison results of the spectral deviation characteristics with the first and second thresholds, and combined with the current state, a state transition decision is executed to obtain the first signal state.

[0174] Optionally, the preset multi-state decision logic also includes multiple counting thresholds;

[0175] Accordingly, the first determining module is specifically used for:

[0176] Based on the comparison results of the spectral deviation characteristics with the first and second thresholds, the counting threshold is used as a transition delay constraint. Combined with the current state, a state transition decision is executed to obtain the first signal state.

[0177] Optionally, the first determining module is specifically used for:

[0178] When the current state is the third state, if the spectral deviation feature is not less than the first threshold, the first signal state is switched to the first state; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is switched to the second state or maintained in the third state is determined according to the comparison result of the first count value and the first count threshold; if the spectral deviation feature is not greater than the second threshold, the first signal state is maintained in the third state and the first count value is updated.

[0179] When the current state is the second state, if the spectral deviation feature is not less than the first threshold, the first signal state is switched to the first state; if the spectral deviation feature is not greater than the second threshold, the first signal state is switched to the third state or maintained in the second state based on the comparison result between the second count value and the second count threshold; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is maintained in the second state.

[0180] When the current state is the first state, if the spectral deviation feature is not greater than the second threshold, the first signal state is switched to the second state; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is switched to the second state or maintained in the first state is determined according to the comparison result of the third count value and the third count threshold; if the spectral deviation feature is not less than the first threshold, the first signal state is maintained in the first state.

[0181] Optionally, the adjustment module is specifically used for:

[0182] Based on the first signal state and / or the second signal state, the corresponding gain adjustment mode is determined; wherein, the gain adjustment mode includes mute mode and non-mute mode;

[0183] The target signal gain is determined based on the gain adjustment mode; wherein the gain adjustment mode includes a first signal gain corresponding to the mute mode and a second signal gain corresponding to the non-mute mode;

[0184] Based on the target signal gain, the digital audio signal is subjected to smooth gain adjustment; wherein, the smooth gain adjustment includes: when switching from non-mute mode to mute mode, gradually reducing the gain to the first signal gain; when switching from mute mode to non-mute mode, gradually increasing the gain to the second signal gain.

[0185] Optionally, the extraction module is specifically used for:

[0186] The digital audio signal is preprocessed to obtain a preprocessed digital audio signal; wherein the preprocessing includes at least one of the following: transsampling processing, signal overlap framing processing, pre-emphasis processing, and windowing processing.

[0187] The spectral deviation features are extracted from the preprocessed digital audio signal to obtain the spectral deviation features.

[0188] Temporal energy features are extracted from the preprocessed digital audio signal to obtain temporal energy features.

[0189] Optionally, the extraction module is also specifically used for:

[0190] A short-time Fourier transform is performed on the preprocessed digital audio signal to obtain its spectrum;

[0191] Calculate the amplitude spectrum based on the spectrum.

[0192] The spectral deviation characteristics are calculated based on the amplitude spectrum and the preset frequency modulation noise spectrum template.

[0193] refer to Figure 7 The diagram illustrates a structural schematic of a soft mute control device suitable for implementing embodiments of the radio device disclosed herein. This soft mute control device can be a terminal device or a server. The terminal device can include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, personal digital assistants (PDAs), portable Android devices (PADs), portable media players (PMPs), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 7 The soft mute control device of the radio device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0194] like Figure 7 As shown, the soft mute control device of the radio equipment may include a processing unit (such as a central processing unit, graphics processor, etc.) 701, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 702 or a program loaded from storage device 708 into random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the radio equipment's soft mute control device. The processing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0195] Typically, the following devices can be connected to I / O interface 705: input devices 706 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 707 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 708 including, for example, magnetic tapes, hard disks, etc.; and communication devices 709. Communication device 709 allows the soft mute control of the radio device to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7The diagram illustrates a soft mute control device for a radio receiver with various features; however, it should be understood that implementation or possession of all shown features is not required. More or fewer features may be implemented alternatively.

[0196] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure 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 communication device 709, or installed from storage device 708, or installed from ROM 702. When the computer program is executed by processing device 701, it performs the functions defined in the methods of embodiments of this disclosure.

[0197] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0198] The aforementioned computer-readable medium may be included in the soft mute control device of the aforementioned radio device; or it may exist independently and not assembled into the soft mute control device of the radio device.

[0199] The aforementioned computer-readable medium carries one or more programs, which, when executed by the soft mute control device of the radio device, cause the soft mute control device of the radio device to perform the method shown in the above embodiments.

[0200] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and 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).

[0201] 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 disclosure. 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.

[0202] The units described in the embodiments of this disclosure can be implemented in software or in hardware. The name of a unit does not necessarily limit the unit itself; for example, the first acquisition unit can also be described as "a unit that acquires at least two Internet Protocol addresses".

[0203] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0204] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on 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 fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0205] The soft mute control device of the radio device in the embodiments of this application can be used to execute the technical solutions in the above-mentioned method embodiments of this application. Its implementation principle and technical effect are similar, and will not be repeated here.

[0206] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the soft mute control method of the radio device described above.

[0207] This application also provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the soft mute control method for a radio device as described above.

[0208] This application also provides a chip, which includes at least one processor, the processor being configured to execute program instructions to perform the soft mute control method for a radio device as described above.

[0209] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0210] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0211] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0212] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0213] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0214] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0215] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0216] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0217] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, the processor and storage medium can exist as discrete components in an electronic control unit or main control device.

[0218] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0219] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A soft mute control method for a radio device, characterized in that, include: Acquire digital audio signals from the radio recording device; The digital audio signal is subjected to feature extraction processing to obtain spectral deviation features and temporal energy features; The first signal state is determined based on the spectral deviation characteristics and the preset multi-state decision logic; The second signal state is determined based on the time-domain energy characteristics and the preset energy decision logic; The digital audio signal of the radio device is adjusted according to the first signal state and / or the second signal state to achieve soft mute control for the radio device.

2. The method according to claim 1, characterized in that, The preset multi-state decision logic includes a first threshold, a second threshold, a first state, a second state, and a third state; wherein, the first threshold is higher than the second threshold, the first state corresponds to the signal valid state, the second state corresponds to the signal transition state, and the third state corresponds to the signal noise state. Accordingly, determining the first signal state based on the spectral deviation characteristics and the preset multi-state decision logic includes: Obtain the current state of the digital audio signal; Based on the comparison results between the spectral deviation characteristics and the first threshold and the second threshold, and in conjunction with the current state, a state transition decision is executed to obtain the first signal state.

3. The method according to claim 2, characterized in that, The preset multi-state decision logic also includes multiple counting thresholds; Accordingly, the step of performing a state transition decision based on the comparison results of the spectral deviation feature with the first threshold and the second threshold, combined with the current state, to obtain the first signal state includes: Based on the comparison results between the spectral deviation characteristics and the first threshold and the second threshold, the counting threshold is used as a transition delay constraint, and combined with the current state, a state transition decision is executed to obtain the first signal state.

4. The method according to claim 3, characterized in that, The step of comparing the spectral deviation feature with the first threshold and the second threshold, using the counting threshold as a transition delay constraint, and combining it with the current state to perform a state transition decision to obtain the first signal state includes: When the current state is the third state, if the spectral deviation feature is not less than the first threshold, then the first signal state is switched to the first state; if the spectral deviation feature is between the second threshold and the first threshold, then based on the comparison result of the first count value and the first count threshold, it is determined whether to switch the first signal state to the second state or maintain the third state; if the spectral deviation feature is not greater than the second threshold, then the first signal state is maintained as the third state and the first count value is updated. When the current state is the second state, if the spectral deviation feature is not less than the first threshold, the first signal state is switched to the first state; if the spectral deviation feature is not greater than the second threshold, the first signal state is switched to the third state or maintained in the second state is determined based on the comparison result of the second count value and the second count threshold; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is maintained in the second state. When the current state is the first state, if the spectral deviation feature is not greater than the second threshold, the first signal state is switched to the second state; if the spectral deviation feature is between the second threshold and the first threshold, the first signal state is switched to the second state or maintained in the first state is determined according to the comparison result of the third count value and the third count threshold; if the spectral deviation feature is not less than the first threshold, the first signal state is maintained in the first state.

5. The method according to any one of claims 1 to 4, characterized in that, The step of adjusting the digital audio signal of the radio receiving device according to the first signal state and / or the second signal state includes: Based on the first signal state and / or the second signal state, a corresponding gain adjustment mode is determined; wherein, the gain adjustment mode includes a mute mode and a non-mute mode; The target signal gain is determined according to the gain adjustment mode; wherein the gain adjustment mode includes a first signal gain corresponding to the mute mode and a second signal gain corresponding to the non-mute mode; According to the target signal gain, the digital audio signal is subjected to smooth gain adjustment; wherein, the smooth gain adjustment includes: when switching from non-mute mode to mute mode, gradually reducing the gain to the first signal gain; when switching from mute mode to non-mute mode, gradually increasing the gain to the second signal gain.

6. The method according to any one of claims 1 to 4, characterized in that, The feature extraction process of the digital audio signal to obtain spectral deviation features and temporal energy features includes: The digital audio signal is preprocessed to obtain a preprocessed digital audio signal; wherein the preprocessing includes at least one of the following: transsampling processing, signal overlap framing processing, pre-emphasis processing, and windowing processing. The preprocessed digital audio signal is subjected to spectral deviation feature extraction processing to obtain spectral deviation features; The preprocessed digital audio signal is subjected to time-domain energy feature extraction processing to obtain time-domain energy features.

7. The method according to claim 6, characterized in that, The step of extracting spectral deviation features from the preprocessed digital audio signal to obtain spectral deviation features includes: The preprocessed digital audio signal is subjected to a short-time Fourier transform to obtain the spectrum; Calculate the amplitude spectrum based on the given spectrum; The spectral deviation characteristics are calculated based on the amplitude spectrum and the preset frequency modulation noise spectrum template.

8. A soft mute control device for a radio receiver, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

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