Noise howling component perception saliency evaluation method, device, equipment and medium
By acquiring and processing the characteristic loudness of noise signals, removing howling components and calculating their contribution, the problems of low correlation and large error in existing evaluation methods are solved, and a fast and accurate evaluation of the perceived salience of howling components is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-24
- Publication Date
- 2026-03-10
AI Technical Summary
Existing methods for evaluating noise feedback components suffer from low correlation with perception, large errors, unstable evaluation results, and failure to consider the masking effect, thus failing to accurately characterize human auditory perception.
By acquiring the characteristic loudness of the original signal, removing the howling component, and calculating the loudness of the reference signal, and combining the masking effect, the characteristic loudness contribution and perceived salience of the howling component are calculated.
It achieves a fast and accurate evaluation of the perceived salience of noise howling components, can automatically or manually identify howling peaks, has a fast calculation speed, does not require model training, and the results are consistent with human ear perception.
Smart Images
Figure CN121641069A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of vehicle vibration and noise analysis technology, and in particular to a method, apparatus, equipment, and medium for evaluating the perceived salience of noise howling components. Background Technology
[0002] In manufacturing industries such as automobiles, machinery, and electrical engineering, as well as in daily transportation and work environments, noise components with relatively monotonous frequency compositions and continuous presence are frequently present, commonly referred to as howling. Accurately evaluating the audible significance of howling is a prerequisite for controlling howling in engineering. Current sound quality analysis standards lack indicators that directly describe the perceived significance of howling components. Therefore, it is necessary to establish objective indicators that align with subjective perception to characterize the audible significance of a particular howling component within a noise segment.
[0003] Currently, the publicly available methods for establishing evaluation indicators for howling problems are mainly divided into two categories. The first type of method calculates several objective indicators of the sample and establishes a relationship with the subjective evaluation results of howling to obtain an evaluation model for the severity of howling. The second type of method starts from the howling perception mechanism and directly calculates new indicators for evaluating howling problems by calculating objective indicators.
[0004] However, the first type of method sometimes fails to match the objective indicators selected for feedback perception. For example, indicators such as loudness, sharpness, and speech intelligibility have low correlation with feedback perception. Consequently, the evaluation model fitted to subjective scores is prone to significant errors. The number of evaluation samples and the subjective scores given by personnel can easily have an unstable impact on the evaluation results. The second type of method generally uses sound pressure level as an objective parameter for calculation, comparing the feedback component with the sound pressure level after removing the feedback component to obtain the evaluation result of the feedback component's prominence. However, sound pressure level cannot accurately represent human auditory perception and does not consider the influence of masking effects. The difference between the energy of the frequency band where the feedback component is located and the energy of a lower frequency band has a decisive influence on the perceived prominence of the feedback component. Summary of the Invention
[0005] This invention provides a method, apparatus, device, and medium for evaluating the perceived salience of noise howling components. It addresses the problems of previous howling component evaluation methods, which relied on calculating several objective indicators of samples and establishing a relationship with subjective howling evaluation results, exhibiting low correlation with howling perception, large errors, and instability in evaluation results due to the number of evaluation samples and the characteristics of the evaluators. It also addresses related howling component evaluation methods based on howling perception mechanisms, which suffer from issues such as sound pressure level not accurately representing human auditory perception and not considering the masking effect. Specifically, the difference between the energy of the frequency band containing the howling component and a lower frequency band has a decisive influence on the perceived prominence of the howling component.
[0006] A first aspect of the present invention provides a method for evaluating the perceived salience of noise howling components, comprising the following steps: Acquire the original signal containing howling components and calculate the first characteristic loudness of the original signal; remove the howling components from the original signal to obtain a reference signal and calculate the second characteristic loudness of the reference signal; calculate the characteristic loudness contribution caused by the howling components based on the first and second characteristic loudnesses; calculate the reference loudness of the reference signal in the howling influence range, and calculate the perceived salience of the howling components based on the characteristic loudness contribution caused by the howling components and the reference loudness.
[0007] Optionally, acquiring the original signal with a howling component and calculating the first characteristic loudness of the original signal includes: Acquire the raw signal containing the howling component; The first characteristic loudness of the original signal is calculated by selecting a preset loudness standard.
[0008] Optionally, removing the howling component from the original signal to obtain a reference signal, and calculating the second characteristic loudness of the reference signal, includes: Calculate the spectrum of the original signal; The howling component in the spectrum is removed, and the frequency positions where the howling component was removed are interpolated and filled to obtain the reference signal; The second characteristic loudness of the reference signal is calculated by selecting a preset standard.
[0009] Optionally, removing the howling component from the spectrum and interpolating to fill in the frequency positions where the howling component was removed to obtain the reference signal includes: The howling component in the spectrum is removed by digital signal processing methods, and the frequency positions of the removed howling component are filled in to obtain the spectrum with the howling component removed. Based on the inverse fast Fourier transform method, a new time-domain signal is generated according to the spectrum after removing the howling component, and the new time-domain signal is used as the reference signal.
[0010] Optionally, removing the howling component from the spectrum and interpolating to fill in the frequency positions where the howling component was removed to obtain the reference signal includes: The original signal is filtered by a narrowband band-stop filter to obtain a signal with the howling component removed. A narrowband random signal with the same bandwidth as the narrowband bandstop filter is superimposed on the signal to which the howling component has been removed to generate a new time-domain signal, and the new time-domain signal is used as the reference signal.
[0011] Optionally, calculating the characteristic loudness contribution caused by the howling component based on the first characteristic loudness and the second characteristic loudness includes: Identify the range of characteristic loudness variation between the first characteristic loudness and the second characteristic loudness; Calculate the difference in characteristic loudness at each frequency point within the characteristic loudness variation range, and calculate the characteristic loudness contribution caused by the howling component based on the difference.
[0012] A second aspect of the present invention provides a device for evaluating the perceived salience of noise howling components, comprising: An acquisition module is used to acquire the original signal containing a howling component and to calculate the first characteristic loudness of the original signal; The removal module is used to remove the howling component from the original signal to obtain a reference signal, and to calculate the second characteristic loudness of the reference signal; The contribution calculation module is used to calculate the characteristic loudness contribution caused by the howling component based on the first characteristic loudness and the second characteristic loudness. The saliency calculation module is used to calculate the reference loudness of the reference signal in the howling influence range, so as to calculate the perceived saliency of the howling component based on the characteristic loudness contribution caused by the howling component and the reference loudness.
[0013] A third aspect of the present invention provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the noise howling component perceived salience evaluation method as described in the above embodiments.
[0014] A fourth aspect of the present invention provides a computer program product, which, when executed by a processor, implements the above-described method for evaluating the perceived salience of noise howling components.
[0015] A fifth aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for evaluating the perceived salience of noise howling components.
[0016] The present invention provides a method, apparatus, device, and medium for evaluating the perceived salience of noise howling components. This method processes the howling component in the original signal, removing the peak values of the howling spectrum and interpolating the frequency range containing the howling component to smooth the spectrum at the peak values, resulting in a signal with the howling component removed. The characteristic loudness curves of the original signal and the signal with the howling component removed are calculated separately, and the difference between the two is used to calculate the change in characteristic loudness in the frequency band containing the howling component. The ratio of this change to the characteristic loudness in the frequency band containing the howling component in the original signal is then calculated, yielding the auditory perceived salience of the howling component. This method is fast, requires no model training, and the program developed using this method can automatically or manually identify the howling peak values after inputting the signal to be analyzed, immediately completing the calculation of the perceived salience of the howling component.
[0017] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0018] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart of a method for evaluating the perceived salience of noise howling components according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the specific execution of a noise howling component perception salience evaluation method provided in an embodiment of the present invention; Figure 3 A schematic diagram of the spectrum of an original sound signal with a howling component according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the characteristic loudness curve of a raw sound signal with a howling component according to an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating an interpolation connection of frequency positions for removing howling components according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the spectrum of a reference signal with feedback components removed, according to an embodiment of the present invention. Figure 7 This is a schematic diagram of the characteristic loudness curve of a reference signal with howling components removed, according to an embodiment of the present invention. Figure 8 This is a schematic diagram illustrating the characteristic loudness change caused by removing howling components according to an embodiment of the present invention; Figure 9 This is a schematic diagram illustrating the relationship between the characteristic loudness contribution of a howling component and the reference loudness according to an embodiment of the present invention. Figure 10 This is a block diagram of a noise howling component perception salience evaluation device provided according to an embodiment of the present invention; Figure 11 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention.
[0019] Explanation of reference numerals in the attached figures: 100-Noise howling component perception salience evaluation device, 1001-Acquisition module, 1002-Removal module, 1003-Contribution calculation module, 1004-Salience calculation module, 1101-Memory, 1102-Processor, 1103-Communication interface. Detailed Implementation
[0020] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0021] The following describes, with reference to the accompanying drawings, a method, apparatus, device, and medium for evaluating the perceived salience of noise howling components according to embodiments of the present invention.
[0022] Figure 1 This is a flowchart illustrating a method for evaluating the perceived salience of noise howling components provided in an embodiment of the present invention.
[0023] like Figure 1 As shown, the method for evaluating the perceived salience of noise howling components includes the following steps: In step S101, the original signal with howling components is acquired, and the first characteristic loudness of the original signal is calculated.
[0024] In some embodiments, acquiring the original signal containing a howling component and calculating a first characteristic loudness of the original signal includes: Acquire the raw signal containing the howling component; Select a preset standard to calculate the first characteristic loudness of the original signal.
[0025] In actual execution, to acquire a raw signal containing a howling component, the first characteristic loudness of the raw signal can be calculated by selecting diffusion field conditions or free field conditions from standards such as ISO532-1, ISO532B, DIN45631, or ANSY S3.4, depending on the specific requirements. The unit is sone, and the frequency band range for ensuring the first characteristic loudness is 0~24 Bark, with an interval of 0.1 Bark. In the formula The representative characteristic frequency band values.
[0026] In step S102, the howling component in the original signal is removed to obtain the reference signal, and the second characteristic loudness of the reference signal is calculated.
[0027] In some embodiments, the howling component in the original signal is removed to obtain a reference signal, and a second characteristic loudness of the reference signal is calculated, including: Calculate the spectrum of the original signal; The howling component in the spectrum is removed, and the frequency positions where the howling component was removed are interpolated and filled to obtain the reference signal; Select a preset loudness standard to calculate the second characteristic loudness of the reference signal.
[0028] In some embodiments, the howling component in the spectrum is removed, and the frequency positions where the howling component was removed are interpolated to obtain a reference signal, including: The howling component in the spectrum is removed by digital signal processing methods, and the frequency positions of the removed howling component are filled in to obtain the spectrum with the howling component removed. Based on the inverse fast Fourier transform method, a new time-domain signal is generated from the spectrum after removing the howling component, and the new time-domain signal is used as the reference signal.
[0029] In some embodiments, the howling component in the spectrum is removed, and the frequency positions where the howling component was removed are interpolated to obtain a reference signal, including: The original signal is filtered by a narrowband band-stop filter to obtain a signal with the howling component removed. A new time-domain signal is generated by superimposing a narrowband random signal with the same bandwidth as a narrowband bandstop filter onto the signal after removing the howling component, and the new time-domain signal is used as the reference signal.
[0030] In actual execution, the spectrum of the original signal with the howling component is calculated. The frequency resolution of this spectrum should be able to effectively identify the howling peak and its frequency range. The frequency resolution should generally not be lower than 2Hz.
[0031] Furthermore, the howling component in the spectrum is removed using digital signal processing methods. This can be achieved by filling in the frequency locations where the howling component was removed using methods such as smoothing interpolation, linear interpolation, and random number generation, thus avoiding spectral dips at those frequency locations and obtaining a reference signal. Specifically, The howling component in the spectrum is removed using digital signal processing methods. The frequency positions of the removed howling component are then filled in using methods such as smoothing interpolation, linear interpolation, and random number generation to obtain the spectrum with the howling component removed. Then, based on the inverse fast Fourier transform method, a new time-domain signal is directly generated from the spectrum with the howling component removed, and this new time-domain signal is used as the reference signal. Alternatively, the original signal can be filtered using a narrowband band-stop filter to remove the howling component, and then a narrowband random signal with the same bandwidth as the narrowband band-stop filter is superimposed, ensuring that the superimposed narrowband signal does not produce any bumps or dips in the spectrum, to generate a new time-domain signal, which is then used as the reference signal.
[0032] Furthermore, based on actual needs, the diffusion field condition or free field condition from standards such as ISO532-1, ISO532B, DIN45631, or ANSY S3.4 can be selected to calculate the second characteristic loudness of the reference signal. .
[0033] It should be noted that the process of calculating characteristic loudness is based on the standard method of ISO 532-1 or ISO 532B, which is the most reliable objective psychoacoustic indicator for characterizing human ear perception. The indicator calculation based on characteristic loudness as the basic parameter can accurately reflect the human ear's perception of the magnitude of noise in different frequency bands and fully considers the masking effect. It is extremely rigorous and theoretically sound for evaluating the perceived significance of howling components based on the human ear perception mechanism. However, the embodiments of the present invention do not make specific limitations, and those skilled in the art can choose the appropriate standard method according to actual needs.
[0034] In step S103, the characteristic loudness contribution caused by the howling component is calculated based on the first characteristic loudness and the second characteristic loudness.
[0035] In some embodiments, calculating the characteristic loudness contribution caused by the howling component based on a first characteristic loudness and a second characteristic loudness includes: Identify the range of characteristic loudness variation between the first and second characteristic loudness; Calculate the difference in characteristic loudness at each frequency point within the characteristic loudness variation range, and calculate the contribution of the howling component to the characteristic loudness based on the difference.
[0036] In actual implementation, such as Figure 2 As shown, compare the first characteristic loudness With the second characteristic loudness The characteristic loudness curves and numerical results are used to identify the intervals in which characteristic loudness changes occur after removing the howling component, denoted as... .
[0037] Furthermore, the difference in characteristic loudness at each frequency point within this interval is calculated. : - ,
[0038] Furthermore, the characteristic loudness contribution caused by the howling component is calculated based on the difference: .
[0039] It should be noted that the quantitative evaluation of the perceived significance of howling components in noise is achieved through the analysis and calculation of characteristic loudness. The frequency band range and difference of the change in characteristic loudness between the original signal and the reference signal are used to characterize the frequency band range and characteristic loudness contribution of the howling component. The mechanism is that the howling component in the original signal is affected by the masking effect of the frequency band where the howling component is located and lower frequency bands. The loudness of the reference signal within the frequency band range where the howling component changes represents the masking effect of the frequency band where the howling component is located and lower frequency bands. Howling components that cannot cause a change in characteristic loudness in this frequency band range will be masked and imperceptible. The characteristic loudness contribution of the howling component is changed is the part that breaks through the masking effect on the basis of this masking effect, that is, the amount of howling component that is perceptible.
[0040] In step S104, the reference loudness of the reference signal in the howling influence range is calculated, so as to calculate the perceived salience of the howling component based on the characteristic loudness contribution caused by the howling component and the reference loudness.
[0041] In some embodiments, the perceived salience of the howling component is calculated based on the characteristic loudness contribution of the howling component and the baseline loudness, including: The characteristic loudness contribution caused by the howling component is compared with the reference loudness, including but not limited to the comparison and calculation of the two in the form of a ratio or difference; The result of comparing the characteristic loudness contribution caused by the howling component with the baseline loudness is expressed as a percentage or other numerical value as the perceived significance of the noise howling component.
[0042] In actual implementation, such as Figure 2 As shown, the reference signal after removing the howling component is calculated within the howling influence range. The benchmark loudness :
[0043] The characteristic loudness contribution caused by the howling component The reference loudness of the howling area In comparison, the perceived salience of the howling component was obtained: .
[0044] It should be noted that the characteristic loudness contribution caused by the howling component is divided by the baseline loudness of the howling influence range. The result is used to evaluate the perceived salience of the howling component and is expressed as a percentage. The mechanism is that the characteristic loudness contribution caused by the howling component is an absolute quantity, while the human ear's evaluation of the salience of the howling component is a relative quantity. This relative baseline should be related to the loudness of the frequency band in which the howling component is located. Therefore, dividing the characteristic loudness contribution caused by the howling component by the baseline loudness of the howling influence range yields a relative value that conforms to human ear perception, namely the perceived salience of the howling component.
[0045] It is understandable that the frequency band characteristic loudness is extremely sensitive to howling components. For howling components that are not masked by low frequencies, the changes in howling components have extremely high resolution. However, inaudible howling components will be located below the masking slope of the low-frequency band characteristic loudness, and the removal of howling components will not produce any change in the characteristic loudness of the corresponding frequency band, i.e., the contribution of characteristic loudness is zero. Therefore, the embodiments of the present invention can accurately evaluate the perceived significance of howling components in various noise types and describe the subjective feeling of howling problems with quantitative objective indicators.
[0046] The following detailed description of the noise howling component perception salience evaluation method proposed in this invention will be provided through a specific embodiment.
[0047] Step 1, as follows Figure 3 As shown, a raw signal with a howling component is obtained, and its spectrum is calculated. The howling component is 2kHz.
[0048] Step two, as Figure 4 As shown, the characteristic loudness of the original signal is calculated using the diffusion field conditions in the ISO 532-1 standard, and the results are as follows. , The value range is 0.1~24 Bark characteristic frequency band interval, with an interval of 0.1 Bark.
[0049] Step 3, as Figure 5 As shown, the howling component in the spectrum is removed by digital signal processing methods, and the frequency positions where the howling component was removed are interpolated and filled to make the spectrum of the original howling frequency positions smoothly connected, thus obtaining the reference signal.
[0050] Among them, such as Figure 6 As shown, a new time-domain signal is generated from the spectrum after removing the howling component, and used as a reference signal. This mainly includes two methods: 1. The iFFT method directly generates the time-domain signal from the spectrum; 2. The original signal is filtered using narrowband filtering to remove the howling component, and then a narrowband random signal of the same bandwidth is superimposed to generate a new time-domain signal, ensuring that the superimposed narrowband signal does not produce any bumps or dips in the spectrum.
[0051] Step four, as Figure 7 As shown, the characteristic loudness of the reference signal is calculated. The selected method and result format should be consistent with the characteristic loudness of the original signal. The characteristic loudness of the reference signal is obtained as follows: .
[0052] Step 5, as Figure 8 As shown, comparison and Characteristic loudness curves and numerical results are used to identify the intervals in which characteristic loudness changes occur after removing the howling component, denoted as... ,in, , .
[0053] Step 6: Calculate the difference in characteristic loudness at each frequency point within the interval. The results are shown in Table 1.
[0054] - ,
[0055] Table 1. Characteristic loudness values for the characteristic loudness variation range (unit: sone)
[0056] Step 7: Calculate the characteristic loudness contribution caused by the howling component: .
[0057] Step 8: Calculate the reference signal after removing the howling component within the howling influence range. The baseline loudness: .
[0058] Step nine, as Figure 9 As shown, the characteristic loudness contribution caused by the howling component is... The reference loudness of the howling area In comparison, the perceived salience of the howling component was obtained: .
[0059] In summary, the noise howling component perception salience evaluation method proposed in this embodiment of the invention processes the howling component in the original signal, removes the howling spectral peaks from the spectrum, and interpolates the frequency range where the howling component is located to make the howling peaks into a smooth spectrum, thus obtaining the signal after removing the howling component. The characteristic loudness curves of the original signal and the signal after removing the howling component are calculated separately, and the difference between the two is used to calculate the change in characteristic loudness of the frequency band where the howling component is located. Furthermore, the ratio of this change to the characteristic loudness of the frequency band where the howling component is located in the original signal is calculated, thus obtaining the auditory perception salience of the howling component. This method is fast, does not require model training, and the program written using this method can automatically or manually identify the howling peaks after inputting the signal to be analyzed, and immediately complete the calculation of the howling component perception salience.
[0060] Next, the noise howling component perception salience evaluation device according to an embodiment of the present invention is described with reference to the accompanying drawings.
[0061] Figure 10 This is a block diagram of a noise howling component perception salience evaluation device provided in an embodiment of the present invention.
[0062] like Figure 10 As shown, the noise howling component perception salience evaluation device 100 includes: an acquisition module 1001, a removal module 1002, a contribution calculation module 1003, and a salience calculation module 1004.
[0063] The acquisition module 1001 acquires the original signal containing the howling component and calculates the first characteristic loudness of the original signal. The removal module 1002 removes the howling component from the original signal to obtain a reference signal and calculates the second characteristic loudness of the reference signal. The contribution calculation module 1003 calculates the characteristic loudness contribution caused by the howling component based on the first and second characteristic loudnesses. The salience calculation module 1004 calculates the reference loudness of the reference signal in the howling influence range, and calculates the perceived salience of the howling component based on the characteristic loudness contribution caused by the howling component and the reference loudness.
[0064] In some embodiments, the acquisition module 1001 includes: Acquisition unit, used to acquire the original signal containing howling components; The first calculation unit is used to select a preset loudness standard to calculate the first characteristic loudness of the original signal.
[0065] In some embodiments, the removal module 1002 includes: The second calculation unit is used to calculate the spectrum of the original signal; The removal and filling unit is used to remove the howling component from the spectrum and interpolate and fill the frequency positions of the removed howling component to obtain the reference signal. The third calculation unit is used to select a preset loudness standard to calculate the second characteristic loudness of the reference signal.
[0066] In some embodiments, the removal and filling unit includes: The first removal subunit is used to remove the howling component from the spectrum using digital signal processing methods, and to fill in the frequency positions of the removed howling component to obtain the spectrum with the howling component removed. The first generation subunit is used to generate a new time-domain signal based on the spectrum after removing the howling component using the inverse fast Fourier transform method, and to use the new time-domain signal as a reference signal.
[0067] In some embodiments, the removal and filling unit includes: The second removal subunit is used to filter the original signal through a narrowband bandstop filter to obtain a signal with the howling component removed. The second generation subunit is used to superimpose a narrowband random signal with the same bandwidth as the narrowband bandstop filter onto the signal after removing the howling component, so as to generate a new time-domain signal, and use the new time-domain signal as a reference signal.
[0068] In some embodiments, the contribution calculation module 1003 includes: The identification unit is used to identify the characteristic loudness variation range between the first characteristic loudness and the second characteristic loudness; The fourth calculation unit is used to calculate the difference in characteristic loudness at each frequency point within the characteristic loudness variation range, and to calculate the contribution of the howling component to the characteristic loudness based on the difference.
[0069] It should be noted that the foregoing explanation of the embodiment of the noise howling component perception salience evaluation method also applies to the noise howling component perception salience evaluation device of this embodiment, and will not be repeated here.
[0070] The noise howling component perception salience evaluation device proposed in this embodiment processes the howling component in the original signal, removes the howling spectral peaks from the spectrum, and interpolates the frequency range where the howling component is located to make the howling peaks into a smooth spectrum, thus obtaining the signal after removing the howling component. The characteristic loudness curves of the original signal and the signal after removing the howling component are calculated separately, and the difference between the two is used to calculate the change in characteristic loudness of the frequency band where the howling component is located. Furthermore, the ratio of this change to the characteristic loudness of the frequency band where the howling component is located in the original signal is calculated, thus obtaining the auditory perception salience of the howling component. This method is fast, does not require model training, and the program written using this method can automatically or manually identify the howling peaks after inputting the signal to be analyzed, and immediately complete the calculation of the howling component perception salience.
[0071] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.
[0072] The electronic device may include: a memory 1101, a processor 1102, and a computer program stored on the memory 1101 and capable of running on the processor 1102.
[0073] When the processor 1102 executes the program, it implements the noise howling component perception salience evaluation method provided in the above embodiments.
[0074] Furthermore, electronic devices also include: Communication interface 1103 is used for communication between memory 1101 and processor 1102.
[0075] The memory 1101 is used to store computer programs that can run on the processor 1102.
[0076] The memory 1101 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage.
[0077] If the memory 1101, processor 1102, and communication interface 1103 are implemented independently, then the communication interface 1103, memory 1101, and processor 1102 can be interconnected via a bus to complete communication between them. 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 into address buses, data buses, control buses, etc. For ease of representation, Figure 11 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.
[0078] Optionally, in a specific implementation, if the memory 1101, processor 1102, and communication interface 1103 are integrated on a single chip, then the memory 1101, processor 1102, and communication interface 1103 can communicate with each other through an internal interface.
[0079] The processor 1102 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.
[0080] This invention also provides a computer program product, which, when executed by a processor, implements the above-described method for evaluating the perceived salience of noise howling components.
[0081] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for evaluating the perceived salience of noise howling components.
[0082] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0083] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0084] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.
[0085] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
[0086] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0087] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
[0088] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
[0089] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.
Claims
1. A method of evaluating perceptual prominence of a noise howl component, characterized by, The method comprises the following steps: obtaining an original signal with a howling component and calculating a first characteristic loudness of the original signal; removing the howling component in the original signal to obtain a reference signal and calculating a second characteristic loudness of the reference signal; calculating a characteristic loudness contribution caused by the howling component according to the first characteristic loudness and the second characteristic loudness; calculating a reference loudness of the reference signal in a howling influence interval to calculate a howling component perceptual salience according to the characteristic loudness contribution caused by the howling component and the reference loudness.
2. The noise howl component-aware perceptual loudness rating method of claim 1, wherein, The step of obtaining an original signal with a howling component and calculating a first characteristic loudness of the original signal comprises: obtaining an original signal with a howling component; selecting a preset loudness standard to calculate the first characteristic loudness of the original signal.
3. The noise howl component-aware perceptual loudness rating method of claim 2, wherein, The step of removing the howling component in the original signal to obtain a reference signal and calculating a second characteristic loudness of the reference signal comprises: calculating a spectrum of the original signal; removing the howling component in the spectrum and interpolating and filling the frequency position of the removed howling component to obtain the reference signal; selecting a preset loudness standard to calculate the second characteristic loudness of the reference signal.
4. The noise howl component perceptual prominence evaluation method according to claim 3, characterized in that, The step of removing the howling component in the spectrum and interpolating and filling the frequency position of the removed howling component to obtain the reference signal comprises: removing the howling component in the spectrum and filling the frequency position of the removed howling component by a digital signal processing method to obtain a spectrum without the howling component; generating a new time domain signal according to the spectrum without the howling component based on an inverse fast Fourier transform method, and taking the new time domain signal as the reference signal.
5. The noise howl component-aware perceptual loudness rating method of claim 3, wherein, The step of removing the howling component in the spectrum and interpolating and filling the frequency position of the removed howling component to obtain the reference signal comprises: filtering the original signal by a narrow-band band-stop filter to obtain a signal without the howling component; superimposing a narrow-band random signal with the same bandwidth as the narrow-band band-stop filter on the signal without the howling component to generate a new time domain signal, and taking the new time domain signal as the reference signal.
6. The noise howl component-aware perceptual loudness rating method of claim 1, wherein, The step of calculating a characteristic loudness contribution caused by the howling component according to the first characteristic loudness and the second characteristic loudness comprises: identifying a characteristic loudness change interval between the first characteristic loudness and the second characteristic loudness; calculating a difference value generated by the characteristic loudness change of each frequency point in the characteristic loudness change interval, and calculating the characteristic loudness contribution caused by the howling component according to the difference value.
7. A noise howl component perceptual prominence evaluation apparatus, characterized by comprising: The method comprises: an obtaining module, configured to obtain an original signal with a howling component and calculate a first characteristic loudness of the original signal; a removing module, configured to remove the howling component in the original signal to obtain a reference signal and calculate a second characteristic loudness of the reference signal; a contribution calculation module, configured to calculate a characteristic loudness contribution caused by the howling component according to the first characteristic loudness and the second characteristic loudness; The prominence calculation module is configured to calculate a reference loudness of the reference signal in the howling influence interval, and to calculate the howling component perceptual prominence according to a characteristic loudness contribution amount caused by the howling component and the reference loudness.
8. An electronic device, comprising: The method comprises: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the noise howling component perceptual prominence evaluation method according to any one of claims 1-6.
9. A computer program product, characterised in that, The computer program / instructions, when executed by the processor, implement the noise howling component perceptual prominence evaluation method according to any one of claims 1-6.
10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the noise howling component perceptual prominence evaluation method according to any one of claims 1-6.