WO2018161429A1

WO2018161429A1 - Noise detection method, and terminal apparatus

Info

Publication number: WO2018161429A1
Application number: PCT/CN2017/083765
Authority: WO
Inventors: 张健; 张海宏; 陶蓓
Original assignee: 华为技术有限公司
Priority date: 2017-03-07
Filing date: 2017-05-10
Publication date: 2018-09-13
Also published as: CN109074814B; CN109074814A

Abstract

A noise detection method, and terminal apparatus, configured to detect a noise energy level in a signal. The noise detection method comprises: computing, according to a first formula, an amplitude spectrum of each audio signal frame (103); determining, according to candidate noise frequencies, a noise frequency (106), said candidate noise frequencies being obtained by means of performing cepstral analysis on said audio signal frame (104, 105); and computing, according to the noise frequency, the amplitude spectrum, and a predetermined computing algorithm, a value of a noise energy level of said audio signal frame (107).

Description

Noise detecting method and terminal device

The present application claims priority to Chinese Patent Application No. 200910131996.3, entitled "A Time-Division Duplex Noise Detection Method and Apparatus", filed on March 7, 2017, the entire contents of which are incorporated by reference. In this application.

Technical field

The present application relates to the field of communication systems and the field of voice processing, and in particular, to a noise detection method and a terminal device.

Background technique

Time Division Duplexing (TDD) noise and board vibration are "current sounds" caused by intermittently emitting large currents in mobile phones. Specifically, the Power Amplifier (PA) of the Time Division Multiple Access (TDMA) mobile phone of the Global System for Mobile communication (GSM) system transmits a large power every 4.616 ms. The current causes the electro-acoustic device to receive interference and demodulate the TDD noise. At the same time, the battery voltage drops at the same frequency, acting on the ceramic capacitor, causing mechanical vibration and passing through the main board to form a plate vibration.

In the existing detection technique, first, the input signal x(t) is first transformed from the time domain to the spectral domain to obtain the spectral signal S(f), and secondly, the spectral signal S(f) is transformed from the spectral domain to the cepstrum domain. The cepstrum signal C(q), finally, find the frequency q ₁ corresponding to the TDD noise in the cepstrum domain (if the signal sampling frequency is f _s and the TDD noise frequency is 217 Hz, the frequency of the cepstrum domain is calculated as: _{_{q 1 = f s / (2}} * 217)), and setting a preset threshold value to determine whether the input signal is a noise TDD, if the input signal in the frequency domain corresponding to q cepstral spectrum signal C ₁ (q ₁₎ greater than the preset The threshold determines that the input signal is TDD noise; if the spectral signal C(q ₁ ) corresponding to the frequency q _{1 of the} input signal in the cepstrum domain is not greater than a preset threshold, it is determined that the input signal is not TDD noise.

In the existing detection technology, the cepstrum domain cannot quantitatively indicate the size of the input signal due to the characteristics of the cepstrum domain itself. Therefore, the existing detection technique can only judge that the input signal is TDD noise, or the input signal is not TDD noise. However, when it is determined that the input signal is TDD noise, the TDD noise level cannot be determined.

Summary of the invention

The embodiment of the present application provides a noise detecting method and a terminal device for detecting a noise energy amount in a signal.

The first aspect of the present application provides a noise detection method, including:

First, the amplitude spectrum of each frame signal is calculated according to the first formula; secondly, the noise frequency is determined according to the candidate noise frequency distribution, wherein the candidate noise frequency distribution is obtained by performing cepstrum analysis on each frame signal; finally, in determining After the amplitude spectrum and the noise frequency of each frame signal, and correspondingly calculating the noise energy value of each frame signal according to the above noise frequency and amplitude spectrum, it can be understood that the above noise energy value can represent the noise level in each frame signal.

In the technical solution provided by the first aspect of the embodiment of the present application, it can be seen that the embodiment of the present application has the following advantages:

The corresponding amplitude spectrum is obtained in advance by calculating each frame signal, and then by performing cepstrum analysis on each frame signal. The obtained candidate noise frequency distribution is determined, and the noise frequency is determined. Finally, the noise energy value of each frame signal is obtained according to the amplitude spectrum and the noise frequency. Therefore, the embodiment of the present application can effectively detect each frame signal. The amount of noise energy. In a possible design, in a first possible implementation manner of the first aspect, before the noise frequency is determined according to each candidate noise frequency, the noise detection method further includes:

In the preset frequency search interval, each frequency of the amplitude value of each frame of the audio signal exceeds a preset threshold is determined as each target frequency, wherein the frequency search interval is a frequency interval in the cepstrum domain;

Calculating a geometric mean value of the amplitude value corresponding to the fundamental frequency, the second harmonic frequency of the fundamental frequency, and the third harmonic frequency of the fundamental frequency, respectively, using each target frequency as a fundamental frequency;

Each target frequency having the largest geometric mean value corresponding to the amplitude value in each frame of the audio signal is determined as each candidate noise frequency.

Secondly, in the first possible implementation manner of the first aspect, in the frequency search interval preset in the cepstrum domain, the target frequency is first determined in each frame of the audio signal, and then the target in each frame of the audio signal The frequency is filtered out of the candidate noise frequency. In this way, each candidate noise frequency is effectively selected from each frame of the audio signal.

In a possible design, in a second possible implementation manner of the first aspect, before calculating the amplitude value spectrum of each frame of the audio signal according to the first formula, the noise method further includes:

The sampled signal is subjected to framing and windowing to obtain at least two frames of audio signals.

Secondly, in the second possible implementation manner of the first aspect, the framing operation and windowing processing of the sampled signal can improve the performance of the algorithm for calculating the audio signal, and can also obtain the TDD noise or the sound of the board vibration over time. The relationship of change.

In a possible design, in a third possible implementation manner of the first aspect, before the sampling signal is subjected to framing and windowing to obtain at least two or more audio signals, the noise detecting method further includes:

The input audio signal is N-times up-sampled to obtain a sampled signal, where N is a positive integer not less than 2.

Secondly, in the third possible implementation manner of the first aspect, the input audio signal is sampled by using N times of interpolation and upsampling, so that the noise frequency is far away from the low frequency interference, thereby improving the accuracy of the noise detection detection.

In a possible design, in a fourth possible implementation manner of the first aspect, the preset calculation method includes a loudness calculation method.

Secondly, in the fourth possible implementation of the first aspect, the loudness calculation method can be used to calculate the noise energy size efficiently and accurately.

In a second aspect, the embodiment of the present application provides a terminal device, where the terminal device has the function of implementing the behavior of the terminal device in the foregoing method embodiment. This function can be implemented in hardware or in hardware by executing the corresponding software. The hardware or software includes one or more modules corresponding to the functions described above.

In a third aspect, an embodiment of the present application provides a terminal device, including: a processor, a memory, a bus, a transmitter, and a receiver; the memory is configured to store a computer to execute an instruction, and the processor is connected to the memory through the bus. When the terminal device is in operation, the processor executes the computer-executed instruction stored in the memory to cause the terminal device to perform the noise detecting method according to any one of the above first aspects.

In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, configured to be stored as the foregoing terminal device. The computer software instructions used, when run on a computer, cause the computer to perform the noise detection method of any of the above first aspects.

In a fifth aspect, an embodiment of the present application provides a computer program product comprising instructions, which when executed on a computer, enable the computer to perform the noise detecting method of any of the above first aspects.

In addition, the technical effects brought by the design mode of any one of the second aspect to the fifth aspect can be referred to the technical effects brought by different design modes in the first aspect, and details are not described herein again.

DRAWINGS

1 is a schematic diagram of an embodiment of a noise detecting method in an embodiment of the present application;

2 is a schematic diagram of an embodiment of a terminal device according to an embodiment of the present application;

3 is a schematic diagram of another embodiment of a terminal device according to an embodiment of the present application;

FIG. 4 is a schematic diagram of another embodiment of a terminal device according to an embodiment of the present application.

detailed description

The terms "first", "second", "third", "fourth", etc. (if present) in the specification and claims of the present application and the above figures are used to distinguish similar objects without having to use To describe a specific order or order. It is to be understood that the data so used may be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than what is illustrated or described herein. In addition, the terms "comprises" and "comprises" and "the" and "the" are intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to Those steps or units may include other steps or units not explicitly listed or inherent to such processes, methods, products or devices.

The noise detecting method in the embodiment of the present application is mainly used for detecting TDD noise and board vibration in a mobile phone, and of course, can also be used for noises of other harmonic forms, and the present application does not impose any limitation.

In order to facilitate the understanding of the noise detection method in the embodiment of the present application, the noise detection method in the embodiment of the present application will be described below in conjunction with a specific embodiment.

Embodiment 1 As shown in FIG. 1 , an embodiment of a noise detecting method in an embodiment of the present application includes:

101. Perform an N-time interpolation upsampling on the input audio signal to obtain a sampling signal.

In this embodiment, optionally, the input audio signal is subjected to N times of interpolation upsampling to obtain a sampling signal, where N is a positive integer greater than or equal to 2. Specifically, the input audio signal is X, and the output sampling signal is Z. According to the upsampling principle, the relationship between X and Z can be obtained, which can be represented by a relationship: Z=upsample(X, N), where It is stated that upsample represents the upsampling function.

Secondly, it should be noted that the N-time interpolation upsampling of the input audio signal does not change the amplitude value of the input audio signal, and actually increases the sampling frequency by N times. In addition, the present application does not impose any restrictions on other sampling schemes that can achieve the same technical effects.

102. Perform framing and windowing on the sampled signal to obtain at least two frames of audio signals.

In this embodiment, optionally, after sampling the input signal to obtain a sampling signal, the sampling signal is performed. The framing operation and the windowing process result in at least two frames of audio signals.

Optionally, the framing operation may be specifically: indicating a kth point in the sampling signal Z by Z(k), setting a length of each frame of the audio signal to be 1, and a moving step size between each two frames of the audio signal is s, Then the ith frame audio signal Z _i is 1 point in Z, where Z _i can be expressed as: Z _i =[z*(1+(i-1)*s), z*(2+(i- 1) *s), ..., z*(l+(i-1)*s)], l, i are positive integers, s is a positive integer greater than 0 and less than l, where s Typical values are usually l/2, l/4 or l/8.

Optionally, the windowing process may be specifically: if the windowing function is W, then W can be expressed as: W _i =[W(1), W(2), . . . , W(l)], It should be noted that the window function W can be selected according to actual needs, and the application does not limit the window function W, which can be a common window function (such as a rectangular window, a triangular window, a Hanning window, a Hamming window, and One of the Gaussian windows, etc., or other newly designed window functions, is not limited in this application.

Optionally, after the framing operation and the windowing process, the obtained at least two frames of audio signals Y _i may be expressed as: Y _i =[W(1)*Z _i (1), W(2)*Z _i (2), ..., W(l) * Z _i (l)].

Secondly, it should be noted that the framing operation can not only improve the performance of the algorithm for calculating the audio signal, but also the relationship between the TDD noise or the amplitude of the plate vibration sound over time. In addition, the framing operation does not change the amplitude value of the input audio signal, and the windowing process mainly mitigates the spectrum leakage problem.

103. Calculate an amplitude spectrum of each frame of the audio signal according to the first formula.

In this embodiment, after at least two frames of audio signals are obtained through the framing operation and the windowing process, the amplitude spectrum of each frame of the audio signal is calculated according to the first formula, and the amplitude spectrum of each frame of the audio signal is obtained.

Alternatively, in one possible method of calculation in order to M _i represents the i-th frame of the audio signal in the spectral domain, then M _i can be expressed _{as: M i = abs (fft (} Y i)); expression of M _i The middle abs represents the absolute value; the fft represents the fast Fourier transform.

104. Calculate a cepstrum of each frame of the audio signal according to the second formula.

In this embodiment, after calculating the amplitude spectrum of each frame of the audio signal, the cepstrum of each frame of the audio signal is calculated according to the second formula, and the cepstrum of each frame of the audio signal is obtained.

Optionally, in a possible calculation manner, C _i represents an ith frame audio signal in the cepstrum domain, and C _i can be expressed as: C _i =real(ifft(log(M _i ))); , log represents the logarithm; ift represents the fast inverse Fourier transform, real represents the real number.

105. Determine each candidate noise frequency in the frequency search interval.

In this embodiment, optionally, after calculating the cepstrum of each frame of the audio signal, determining each candidate noise frequency in the frequency search interval, wherein the frequency search interval is a frequency range corresponding to the cepstrum domain, and the frequency search interval thereof The specific determination manner may be preset according to the experience of the prophet, or may be determined according to different mobile phone systems, and the application does not impose any restrictions.

Optionally, one possible implementation of determining each candidate noise frequency within the frequency search interval is:

First, the frequency search interval in the cepstrum domain is determined according to the experience of the prophet. It should be noted that there are many amplitude values in the cepstrum domain, but the amplitude values in the cepstrum domain cannot quantitatively represent the audio signal of each frame. Size

Secondly, the preset threshold is used to select each frequency of each frame signal that exceeds the preset threshold as the target frequency, and the preset threshold is substantially a preset amplitude value (for example, the maximum amplitude in the cepstrum domain may be specifically The value of the preset threshold can be set according to the actual application scenario, and the present application does not impose any restrictions on this;

Again, each target frequency selected from each frame signal is used as the fundamental frequency f _base , and the second harmonic frequency f ₂ and the third harmonic frequency f ₃ corresponding to the fundamental frequency are sequentially calculated to obtain a fundamental frequency f _base . After the second harmonic frequency f ₂ and the third harmonic frequency f ₃ , the three frequencies are calculated according to the geometric square value formula, and the geometric square value p(f _base ) of the corresponding amplitude value in the cepstrum domain, wherein, Ground, the geometric squared formula can be:

Other forms of geometric squared formulas are also possible, and no limitation is imposed on this application.

Finally, the target frequency with the largest geometric square value in each of the calculated audio signals is used as the candidate noise frequency of the current frame.

106. Determine a noise frequency according to each candidate noise frequency.

In this embodiment, after searching and determining each noise frequency, the noise frequency is determined from each candidate noise frequency.

Optionally, a possible way to determine the noise frequency from each candidate noise frequency is: counting the number of occurrences of each of the candidate noise frequencies, and then the most occurrences, and the total number of occurrences of all frequencies The frequency of the number of times (frames) exceeds the preset threshold is determined as the noise frequency, and there is a frequency f _t , and the number of occurrences accounts for 60% of the number of occurrences of all frequencies (one candidate frequency per frame, that is, the total number of frames). Greater than 50% threshold. That is, the noise is considered to be TDD noise or plate vibration, and f _{t is} its noise frequency. Of course, it may be other possible determination manners, and the present application does not impose any limitation. If the number of times without any candidate frequency exceeds the preset threshold, it can be judged that this noise is not TDD noise or plate vibration, that is, it is not necessary to calculate its energy value.

107. Calculate the noise energy value of each frame of the audio signal according to the noise frequency, the amplitude spectrum, and the preset calculation method.

In this embodiment, after determining the noise frequency according to each candidate noise frequency, the noise energy value corresponding to the noise frequency in each frame of the audio signal is calculated according to the noise frequency, the amplitude spectrum, and a preset calculation method, wherein the noise energy value is represented by The size of the TDD noise or the plate vibration sound, if the noise energy value is higher, the TDD noise or the plate vibration sound is larger; if the noise energy value is lower, the TDD noise or the plate vibration sound is smaller.

Alternatively, one possible way to calculate the noise energy value is to calculate the noise energy value of the TDD noise or the plate vibration sound by using the loudness calculation method. At the same time, the energy value corresponding to the second harmonic frequency f ₂ and the third harmonic frequency f ₃ corresponding to the noise frequency can be calculated. In addition, for other calculation methods, the application does not impose any restrictions.

In this embodiment, the corresponding amplitude spectrum is obtained in advance by calculating each frame signal, and then the noise frequency is determined by the candidate noise frequency distribution obtained by performing cepstrum analysis on each frame signal, and finally, according to the above amplitude spectrum and the above The noise frequency is calculated correspondingly to obtain the noise energy value of each frame signal. Therefore, the embodiment of the present application can effectively detect the noise energy amount in each frame signal.

The foregoing embodiment is a detailed description of the noise detecting method in the present application. To facilitate the understanding of the terminal device in the embodiment of the present application, the terminal device in the embodiment of the present application will be described below in conjunction with a specific embodiment.

Embodiment 2 As shown in FIG. 2, an embodiment of a terminal device in this embodiment of the present application includes:

a first calculating module 201, configured to calculate an amplitude spectrum of each frame of the audio signal according to the first formula;

The first determining module 202 is configured to determine a noise frequency according to each candidate noise frequency, where each candidate noise frequency is obtained by performing cepstrum analysis on each frame of the audio signal;

a second calculating module 203, configured to calculate, according to the noise frequency, the amplitude spectrum, and a preset calculation method The noise energy value of each frame of the audio signal.

As shown in FIG. 3, optionally, in a possible design, the terminal device further includes: a second determining module 304, a third calculating module 305, and a third determining module 306; wherein each module function is as follows:

The second determining module 304 is configured to determine, in the preset frequency search interval, each frequency of the amplitude value of each frame of the audio signal exceeding a preset threshold as each target frequency;

a third calculating module 305, configured to calculate, as a fundamental frequency, a fundamental frequency, a second harmonic frequency of the fundamental frequency, and a geometric mean value of the amplitude value respectively corresponding to the third harmonic frequency of the fundamental frequency;

The third determining module 306 is configured to determine each target frequency corresponding to the maximum geometric mean as each candidate noise frequency.

As shown in FIG. 3, optionally, in a possible design, the terminal device further includes: a first processing module 307, wherein the first processing module 307 is configured to perform framing and windowing processing on the sampling signal, Obtain at least two frames of audio signals.

As shown in FIG. 3, optionally, in a possible design, the terminal device further includes: a second processing module 308, wherein the second processing module 308 is configured to perform N times of insertion of the input audio signal. Sampling, the sampled signal is obtained, wherein the N is a positive integer not less than 2.

The foregoing embodiment 2 describes the terminal device in the embodiment of the present application in detail from the aspect of the virtual functional device. The following describes the terminal device in the embodiment of the present application from the aspect of the physical structure, which may be specifically as follows:

The third embodiment, as shown in FIG. 4, another embodiment of the terminal device in the embodiment of the present application includes: a receiver 401, a transmitter 402, a processor 403, a memory 404, and a bus 405.

The memory 404 can include read only memory and random access memory and provides instructions and data to the processor 403. A portion of the memory 404 may also include a non-volatile random access memory (English name: Non-Volatile Random Access Memory, English abbreviation: NVRAM).

The memory 404 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof:

Operation instructions: including various operation instructions for implementing various operations;

Operating system: Includes a variety of system programs for implementing various basic services and handling hardware-based tasks.

The processor 403 in the embodiment of the present application may be used to perform operations corresponding to the first communication network element in the foregoing embodiment, and may include the following operations:

Calculating an amplitude spectrum of each frame of the audio signal according to the first formula;

Determining a noise frequency according to each candidate noise frequency, wherein each candidate noise frequency is obtained by performing cepstrum analysis on each frame of the audio signal;

According to the noise frequency, the amplitude spectrum is calculated by a preset calculation method to obtain a noise energy value of each frame of the audio signal.

Optionally, the processor 403 may be configured to: determine, in a preset frequency search interval, each frequency in the audio signal of each frame that exceeds a preset threshold as each target frequency;

Using each target frequency as a fundamental frequency, calculating a fundamental frequency, a second harmonic frequency of the fundamental frequency, and a geometric mean value of the amplitude value corresponding to the third harmonic frequency of the fundamental frequency;

Each target frequency corresponding to the maximum geometric mean is determined as each candidate noise frequency.

Optionally, the processor 403 is configured to perform the following steps: performing N-times up-sampling on the input audio signal to obtain the sampling signal, where the N is a positive integer not less than 2;

The processor 403 controls the operation of the first communication network element, and the processor 403 may also be referred to as a central processing unit (English full name: Central Processing Unit, English abbreviation: CPU). Memory 404 can include read only memory and random access memory and provides instructions and data to processor 403. A portion of memory 404 may also include NVRAM. In a specific application, the components of the first communication network element are coupled together by a bus system 405. The bus system 405 may include a power bus, a control bus, a status signal bus, and the like in addition to the data bus. However, for clarity of description, various buses are labeled as bus system 405 in the figure.

The method disclosed in the foregoing embodiment of the present application may be applied to the processor 403 or implemented by the processor 403. Processor 403 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the foregoing method may be completed by an integrated logic circuit of hardware in the processor 403 or an instruction in a form of software. The processor 403 may be a general-purpose processor, a digital signal processor (English name: Digital Signal Processing, English abbreviation: DSP), an application specific integrated circuit (English name: Application Specific Integrated Circuit, English abbreviation: ASIC), ready-made programmable Gate array (English name: Field-Programmable Gate Array, English abbreviation: FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The methods, steps, and logical block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general purpose processor may be a microprocessor or the processor or any conventional processor or the like. The steps of the method disclosed in the embodiments of the present application may be directly implemented by the hardware decoding processor, or may be performed by a combination of hardware and software modules in the decoding processor. The software module can be located in a conventional storage medium such as random access memory, flash memory, read only memory, programmable read only memory or electrically erasable programmable memory, registers, and the like. The storage medium is located in memory 404, and processor 403 reads the information in memory 404 and, in conjunction with its hardware, performs the steps of the above method.

The related description of FIG. 4 can be understood by referring to the related description and effect of the method part of FIG. 1, and no further description is made here.

A person skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

In the several embodiments provided by the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application, in essence or the contribution to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .

The above embodiments are only used to explain the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still The technical solutions described in the embodiments are modified, or the equivalents of the technical features are replaced by the equivalents. The modifications and substitutions of the embodiments do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

A noise detecting method, comprising:

Calculating an amplitude spectrum of each frame of the audio signal according to the first formula;

Determining a noise frequency according to each candidate noise frequency, wherein each candidate noise frequency is obtained by performing cepstrum analysis on each frame of the audio signal;

According to the noise frequency, the amplitude spectrum, and a preset calculation method are calculated to obtain a noise energy value of each frame of the audio signal.
The noise detecting method according to claim 1, wherein before the determining the noise frequency according to each candidate noise frequency, the method further comprises:

Determining, in a preset frequency search interval, each frequency of the amplitude value of each frame of the audio signal exceeding a preset threshold as each target frequency;

Calculating a fundamental frequency, a fundamental frequency, a second harmonic frequency of the fundamental frequency, and a geometric mean value of amplitude values respectively corresponding to a third harmonic frequency of the fundamental frequency;

Each target frequency corresponding to the maximum geometric mean is determined as each candidate noise frequency.
The noise detecting method according to claim 1 or 2, wherein before the calculating the amplitude value spectrum of each frame of the audio signal according to the first formula, the method further comprises:

The sampled signal is subjected to framing and windowing to obtain at least two frames of audio signals.
The noise detecting method according to claim 3, wherein before the framing and windowing processing of the sampled signal signal to obtain at least two or more audio signals, the method further comprises:

The input audio signal is N-times up-sampled to obtain the sampled signal, wherein the N is a positive integer not less than 2.
The noise detecting method according to any one of claims 1 to 4, wherein the preset calculating method includes a loudness calculating method.
A terminal device, comprising:

a first calculating module, configured to calculate an amplitude spectrum of each frame of the audio signal according to the first formula;

a first determining module, configured to determine a noise frequency according to each candidate noise frequency, where each candidate noise frequency is obtained by performing cepstrum analysis on each frame of the audio signal;

And a second calculating module, configured to calculate, according to the noise frequency, the amplitude spectrum, and a preset calculation method, a noise energy value of each frame of the audio signal.
The terminal device according to claim 6, wherein the terminal device further comprises:

a second determining module, configured to determine, in a preset frequency search interval, each frequency of the amplitude value of each frame of the audio signal exceeding a preset threshold as each target frequency;

a third calculating module, configured to calculate, as a fundamental frequency, a fundamental frequency, a second harmonic frequency of the fundamental frequency, and a geometric mean value of the amplitude value corresponding to the third harmonic frequency of the fundamental frequency ;

And a third determining module, configured to determine each target frequency corresponding to the maximum geometric mean as each candidate noise frequency.
The terminal device according to claim 6 or 7, wherein the terminal device further comprises:

The first processing module is configured to perform framing and windowing processing on the sampling signal to obtain at least two frames of audio signals.
The terminal device according to claim 8, wherein the terminal device further comprises:

And a second processing module, configured to perform N times of interpolation on the input audio signal to obtain the sampling signal, where the N is a positive integer not less than 2.
The terminal device according to any one of claims 6 to 9, characterized in that the preset calculation method comprises a loudness calculation method.
A terminal device, comprising:

Receiver, transmitter, memory, bus, and processor;

The bus for connecting the receiver, the transmitter, the memory, and the processor;

The memory is configured to store an operation instruction;

The processor is configured to perform the operations in the above claims 1 to 5 by calling the operation instruction.