WO2018161429A1 - Procédé de détection de bruit et appareil terminal - Google Patents

Procédé de détection de bruit et appareil terminal Download PDF

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Publication number
WO2018161429A1
WO2018161429A1 PCT/CN2017/083765 CN2017083765W WO2018161429A1 WO 2018161429 A1 WO2018161429 A1 WO 2018161429A1 CN 2017083765 W CN2017083765 W CN 2017083765W WO 2018161429 A1 WO2018161429 A1 WO 2018161429A1
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WO
WIPO (PCT)
Prior art keywords
frequency
noise
audio signal
frame
terminal device
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Application number
PCT/CN2017/083765
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English (en)
Chinese (zh)
Inventor
张健
张海宏
陶蓓
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华为技术有限公司
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Priority to CN201780026318.9A priority Critical patent/CN109074814B/zh
Publication of WO2018161429A1 publication Critical patent/WO2018161429A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M9/00—Arrangements for interconnection not involving centralised switching
    • H04M9/08—Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic
    • H04M9/082—Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic using echo cancellers
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/02—Constructional features of telephone sets
    • H04M1/19—Arrangements of transmitters, receivers, or complete sets to prevent eavesdropping, to attenuate local noise or to prevent undesired transmission; Mouthpieces or receivers specially adapted therefor
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • 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.
  • Time Division Duplexing (TDD) noise and board vibration are "current sounds" caused by intermittently emitting large currents in mobile phones.
  • 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.
  • 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.
  • 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 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.
  • 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.
  • 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:
  • 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.
  • the noise detection method further includes:
  • 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;
  • 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.
  • 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.
  • the noise method 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.
  • 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.
  • the noise detecting method 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.
  • 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.
  • the preset calculation method includes a loudness calculation method.
  • the loudness calculation method can be used to calculate the noise energy size efficiently and accurately.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • FIG. 1 is a schematic diagram of an embodiment of a noise detecting method in an embodiment of the present application
  • FIG. 2 is a schematic diagram of an embodiment of a terminal device according to an embodiment of the present application.
  • FIG. 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.
  • 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 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.
  • 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:
  • 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.
  • the input audio signal is X
  • the output sampling signal is Z.
  • 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.
  • the present application does not impose any restrictions on other sampling schemes that can achieve the same technical effects.
  • the sampling signal is performed.
  • the framing operation and the windowing process result in at least two frames of audio signals.
  • W 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.
  • 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.
  • the framing operation does not change the amplitude value of the input audio signal, and the windowing process mainly mitigates the spectrum leakage problem.
  • 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.
  • M i abs (fft ( Y i)); expression of M i
  • 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.
  • C i represents an ith frame audio signal in the cepstrum domain
  • 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.
  • each candidate noise frequency in 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.
  • determining each candidate noise frequency within the frequency search interval is:
  • 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
  • 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;
  • 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 .
  • 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.
  • 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.
  • the noise frequency is determined from each candidate noise frequency.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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 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 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:
  • each candidate noise frequency is obtained by performing cepstrum analysis on each frame of the audio signal
  • the amplitude spectrum is calculated by a preset calculation method to obtain a noise energy value of each frame of the audio signal.
  • 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;
  • 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.
  • 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 sampled signal is subjected to framing and windowing to obtain at least two frames of audio signals.
  • 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.
  • 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.
  • 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.
  • FIG. 4 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.
  • the disclosed system, apparatus, and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • 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.
  • 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.
  • 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.
  • a computer readable 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. .

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  • Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Computational Linguistics (AREA)
  • Quality & Reliability (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Noise Elimination (AREA)
  • Telephone Function (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)

Abstract

L'invention concerne un procédé de détection de bruit et un appareil terminal configuré pour détecter un niveau d'énergie de bruit dans un signal. Le procédé de détection de bruit comprend les étapes suivantes : calcul d'un spectre d'amplitude de chaque trame de signal audio conformément à une première formule (103) ; détermination d'une fréquence de bruit conformément à des fréquences de bruit candidates (106), lesdites fréquences de bruit candidates étant obtenues au moyen d'une analyse cepstrale sur ladite trame de signal audio (104, 105) ; et calcul d'une valeur d'un niveau d'énergie de bruit de ladite trame de signal audio conformément à la fréquence de bruit, au spectre d'amplitude et à un algorithme de calcul prédéterminé (107).
PCT/CN2017/083765 2017-03-07 2017-05-10 Procédé de détection de bruit et appareil terminal WO2018161429A1 (fr)

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CN201710131996 2017-03-07
CN201710131996.3 2017-03-07

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CN114125095B (zh) * 2020-08-31 2024-09-10 北京小米移动软件有限公司 一种终端设备、振动噪音的控制方法、装置及介质
CN113726367B (zh) * 2021-09-01 2023-01-20 嘉兴中科声学科技有限公司 信号检测方法、装置及电子设备
CN114040309B (zh) * 2021-09-24 2024-03-19 北京小米移动软件有限公司 风噪检测方法、装置、电子设备及存储介质
CN114385977B (zh) * 2021-12-13 2024-05-28 广州方硅信息技术有限公司 信号的有效频率检测方法、终端设备及存储介质

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