CN115426430A - Method for suppressing and processing hand-free call noise of space equipment - Google Patents

Method for suppressing and processing hand-free call noise of space equipment Download PDF

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CN115426430A
CN115426430A CN202211077167.9A CN202211077167A CN115426430A CN 115426430 A CN115426430 A CN 115426430A CN 202211077167 A CN202211077167 A CN 202211077167A CN 115426430 A CN115426430 A CN 115426430A
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朱博
雷志广
周震
曾政菻
邱新安
许珩
张泉斌
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Lanzhou Institute of Physics of Chinese Academy of Space Technology
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    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/60—Substation equipment, e.g. for use by subscribers including speech amplifiers
    • H04M1/6033—Substation equipment, e.g. for use by subscribers including speech amplifiers for providing handsfree use or a loudspeaker mode in telephone sets
    • H04M1/6041—Portable telephones adapted for handsfree use
    • 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

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Abstract

The application relates to the technical field of space, in particular to a method for suppressing and processing hands-free call noise of space equipment, which comprises the following steps: step 1: initializing variable parameters of the space equipment; step 2: converting input voice from a time domain to a frequency domain, and dividing the input voice into a plurality of sub-bands; and 3, step 3: calculating the energy of each sub-band; and 4, step 4: calculating the signal-to-noise ratio of each sub-band; and 5: carrying out voice measurement calculation according to the signal-to-noise ratio of the sub-band; step 6: calculating the deviation of the spectrum offset and judging the logic of updating the background noise; and 7: updating background noise and correcting the signal-to-noise ratio of the sub-band; and 8: calculating the gain of a sub-band, and filtering the frequency spectrum of the input signal according to the gain of the sub-band; and step 9: and reconstructing a time domain signal and performing automatic level control. The noise suppression device organically integrates noise suppression, voice detection and automatic level control, and greatly improves the noise resistance of the space equipment during hands-free call.

Description

Space equipment hands-free call noise suppression processing method
Technical Field
The application relates to the technical field of space, in particular to a method for suppressing and processing hands-free call noise of space equipment.
Background
In China, a space station which runs on orbit for a long time is built, and a astronaut can realize a communication task and a conference function with ground equipment or among different cabin sections through voice equipment in a cabin. The voice equipment has the functions of playing sound by a loudspeaker and receiving voice input by a built-in microphone, and can support astronauts to realize full-duplex hands-free conversation in the capsule.
In a conference system composed of hands-free voice terminals, environmental noise (such as a fan in a space station, electronic equipment, a noisy environment, etc.) interferes with the voice of a speaker, so that the voice quality is reduced, and the performance of the whole system is affected.
Since the last 80 s of the last century, various noise suppression technologies have been studied at home and abroad, and a spectral subtraction method, a wiener filtering method, a kalman filtering method and the like are proposed, and the method is applied to an actual communication system, so that the voice quality is obviously improved.
The application is an improved noise suppression (speech enhancement) algorithm developed based on the combination of spectral subtraction and subband technology according to the actual working condition of the speech system to which the voice equipment of the spatial station belongs, and is used for carrying out the ambient noise reduction processing on the low subband part of the near-end audio signal so as to carry out the subsequent echo cancellation AEC processing.
Disclosure of Invention
The application provides a noise suppression processing method for the hands-free call of the space equipment, which organically integrates noise suppression, voice detection and automatic level control into a whole, and greatly improves the noise resistance of the space equipment during the hands-free call.
In order to achieve the above object, the present application provides a method for processing a hands-free call noise suppression of a spatial device, comprising the following steps: step 1: initializing equipment variables, namely initializing variable parameters of the space equipment; and 2, step: converting input voice from a time domain to a frequency domain, and dividing the input voice into a plurality of sub-bands; and step 3: calculating the energy of each sub-band according to a first estimation formula; and 4, step 4: calculating the signal-to-noise ratio of each sub-band by combining a second estimation formula according to the energy of each sub-band; and 5: carrying out voice measurement calculation according to the signal-to-noise ratio of the sub-band; step 6: calculating the deviation of the spectrum offset, and judging the logic of updating the background noise; and 7: updating background noise and correcting the signal-to-noise ratio of the sub-band; and 8: calculating the gain of a sub-band, and filtering the frequency spectrum of the input signal according to the gain of the sub-band; and step 9: and reconstructing a time domain signal, controlling an automatic level, finishing noise suppression processing and outputting voice.
Further, in step 1, initializing a frame number variable, an input data frame buffer variable, a pre-emphasis and de-emphasis variable, an output overlap-add data variable, an output array variable, and a continuous speech frame counter variable to zero; and initializing a sub-band energy estimation variable, a long-time power spectrum estimation variable and a sub-band noise estimation variable into determined values.
Further, in step 2, the input speech is converted from the time domain to the frequency domain by using an interframe overlapping method, and the frame length is 10ms.
Further, in step 6, calculating the deviation of the spectrum offset includes the following steps: step 6.1: calculating a dB value of the sub-band power spectrum; step 6.2: calculating a long-term average power spectrum; step 6.3: and calculating the deviation between the current frame power spectrum and the long-term power spectrum.
Further, in step 6, the background noise update logic includes regular update logic and forced update logic.
Further, in step 8, calculating the subband gain includes the following steps: step 8.1: calculating a gain factor of the current frame; step 8.2: calculating the gain of each sub-band; step 8.3: linear subband gains are calculated.
Further, in step 9, the reconstructing of the time domain signal comprises the following steps: step 9.1: transforming the filtered frequency domain signal into a time domain signal by inverse Fourier transform; step 9.2: performing overlap-add processing on the signals; step 9.3: the signal is de-emphasized.
Further, in step 9, the automatic level control includes an output gain variable control and a decibel representation variable control.
The invention provides a method for suppressing and processing the noise of the hand-free call of the space equipment, which has the following beneficial effects:
the method has strong adaptability, can meet the requirements that a user can speak at far and near ends and different distances simultaneously under the condition of hands-free, and noise does not occur, has high calculation efficiency, adopts a set of method combining voice detection, automatic level control and voice enhancement for spatial voice equipment, improves the traditional voice enhancement algorithm by utilizing spectral subtraction and subband technology, thereby greatly reducing the calculated amount of the whole system, has strong flexibility, can realize effective automatic level control according to the result of the voice detection and the characteristics of voice signals, compares the energy of the current frame with the long-term average energy, determines to enhance or attenuate the signals according to the result, and updates the long-term average energy according to the energy of the current frame.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, are included to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
fig. 1 is a schematic flow chart of a method for processing hands-free call noise suppression of a spatial device according to an embodiment of the present application;
Detailed Description
In order to make the technical solutions of the present application better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the accompanying drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances in order to facilitate the description of the embodiments of the application herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.
Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
In addition, the term "plurality" shall mean two as well as more than two.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
As shown in fig. 1, the present application provides a method for processing noise suppression of hands-free talk of spatial equipment, which includes the following steps: step 1: initializing equipment variables, namely initializing variable parameters of the space equipment; step 2: converting input voice from a time domain to a frequency domain, and dividing the input voice into a plurality of sub-bands; and step 3: calculating the energy of each sub-band according to a first estimation formula; and 4, step 4: calculating the signal-to-noise ratio of each sub-band by combining a second estimation formula according to the energy of each sub-band; and 5: carrying out voice measurement calculation according to the signal-to-noise ratio of the sub-band; step 6: calculating the deviation of the spectrum offset and judging the logic of updating the background noise; and 7: updating background noise and correcting the signal-to-noise ratio of the sub-band; and 8: calculating the gain of a sub-band, and filtering the frequency spectrum of the input signal according to the gain of the sub-band; and step 9: and reconstructing a time domain signal, controlling automatic level, finishing noise suppression processing and outputting voice.
Specifically, the method for processing the hands-free call noise suppression of the spatial device provided by the embodiment of the present application organically integrates the noise suppression method, the voice detection method, and the automatic level control method based on the parameters in the noise suppression algorithm, and realizes an improved noise suppression method based on the combination of spectral subtraction and subband technology. The basic principle is that each frame of input voice is firstly converted into a frequency domain and divided into 16 sub-bands, then the signal-to-noise ratio of each sub-band is estimated, voice and noise detection is carried out by utilizing a voice measurement mechanism, accurate estimation of background noise is realized, the gain of each sub-band is modified according to the signal-to-noise ratio of each sub-band, and the estimation of the background noise is realized.
Further, in step 1, initializing a frame number variable, an input data frame buffer variable, a pre-emphasis and de-emphasis variable, an output overlap-add data variable, an output array variable, and a continuous speech frame counter variable to zero; and initializing a sub-band energy estimation variable, a long-time power spectrum estimation variable and a sub-band noise estimation variable into determined values.
Further, in step 2, the input speech is converted from the time domain to the frequency domain by using an interframe overlapping method, and the frame length is 10ms.
Furthermore, in step 5, the speech measure mainly describes the similarity between the current frame and the speech according to the subband signal-to-noise ratio, and is used as a measure for quantitatively judging whether the current frame is speech or noise.
Further, in step 6, calculating the deviation of the spectral shift includes the following steps: step 6.1: calculating a dB value of the sub-band power spectrum; step 6.2: calculating a long-term average power spectrum; step 6.3: and calculating the deviation between the current frame power spectrum and the long-term power spectrum. The spectrum offset deviation is calculated and mainly used for estimating the background noise, and in the calculation process, the energy spectrum of the current frame can be calculated firstly, then the noise updating threshold is calculated, then the background noise energy is determined, and whether the background noise needs to be updated or not is judged.
Further, in step 6, the background noise update logic includes regular update logic and forced update logic.
Further, in step 7, after the background noise is updated, the speech measurement detection result needs to be combined, and the signal-to-noise ratio threshold is used for judging to determine whether to correct the sub-band signal-to-noise ratio.
Further, in step 8, calculating the subband gain includes the following steps: step 8.1: calculating a gain factor of the current frame; step 8.2: calculating the gain of each sub-band; step 8.3: linear subband gains are calculated. The subband gain is calculated mainly for frequency domain filtering, and the subband gain is multiplied by the frequency spectrum of each subband of the input signal, so as to realize the filtering of the input frequency spectrum.
Further, in step 9, the reconstructing of the time domain signal comprises the following steps: step 9.1: transforming the filtered frequency domain signal into a time domain signal by inverse Fourier transform; step 9.2: performing overlap-add processing on the signals; step 9.3: the signal is de-emphasized. The reconstruction of the time domain signal mainly refers to the transformation of the input signal from the frequency domain to the time domain again.
Further, in step 9, the automatic level control includes an output gain variable control and a decibel representation variable control. The automatic level control mainly compares the current frame energy with the long-term average energy, determines whether to enhance or weaken the current voice according to the comparison result, and updates the long-term average capability according to the current frame energy. The specific measure is to determine the processing strategy of the level by controlling two variables of the output gain ALC _ gain and the decibel value gain _ db thereof.
The present application is further illustrated by the following more specific examples:
step 1: initializing equipment variables, initializing variable parameters of the space equipment, and initializing the following variables to zero, wherein the variables comprise: frame number m, input data frame buffer d (m), pre-emphasis and de-emphasis variables, output overlap-add data h (m), output array S' (n), continuous speech frame counter variable updantenum, the following variables are initialized to certain values: subband energy estimation Ech (m), long-term power spectrum estimation
Figure BDA0003828526440000061
A subband noise estimate En (m);
step 2: converting input voice from time domain to frequency domain, and dividing the input voice into a plurality of sub-bands, the frame length is 10ms, namely 80 points data is one frame (L = 80), and the number of data points overlapped is 24 by adopting the method of inter-frame overlapping, so the number of data points of an input data frame buffer D (m, n) is L + D =104 points, wherein the former D point data is the last D point data of the former frame, namely: d (m, n) = D (m-1, L + n), 0 ≦ n < D, where m represents the current frame; pre-emphasis processing is carried out on input voice s (n), windowing processing is carried out on input data d (M, n) after pre-emphasis by using a smooth trapezoidal window, zero padding is carried out, discrete Fourier transform input data G (n) with M =128 points are formed, discrete Fourier transform is carried out on G (n), spectrum G (k) of an input signal is obtained, and in actual calculation, G (n) is considered to be a real number, so that real FFT of M points can be rapidly calculated by using complex FFT of M/2 points;
and step 3: calculating the energy of each sub-band according to a first estimation formula, and calculating the energy Ech (m) of each sub-band of the current frame according to the following estimation formula:
Figure BDA0003828526440000071
NC =16, which is the number of subbands, emin =0.0625, which is the subband minimum energy, and α ch (m) is a subband energy smoothing factor;
and 4, step 4: calculating the signal-to-noise ratio of each sub-band according to a second estimation formula, and calculating the signal-to-noise ratio of each sub-band of the current frame according to the following estimation formula:
Figure BDA0003828526440000072
where En (m, i) is an estimate of the ith subband noise energy of the current frame, 0.375 is the quantization step size of the signal-to-noise ratio, and σ q (i) is quantized to an integer and defined between 0 and 89;
and 5: and performing voice measure calculation according to the signal-to-noise ratio of the sub-band, wherein the voice measure v (m) describes the similarity degree of the current frame and the voice according to the signal-to-noise ratio of the sub-band, and is a measuring standard for representing whether the current frame is the voice or the noise, wherein:
Figure BDA0003828526440000073
the voice measurement table { V } has 90 elements, and V (k) is the kth value in the voice measurement table { V };
and 6: calculating the deviation of the spectrum offset, judging the logic of noise updating, and adopting the following steps when calculating the deviation of the spectrum offset:
step 6.1: calculating the dB value of the sub-band power spectrum EdB (m, i),
EdB(m，i)＝10log10(Ech(m，i))，0≤i<NC；
step 6.2: calculating the Long-term average Power Spectrum
Figure BDA0003828526440000074
Figure BDA0003828526440000081
Step 6.3: calculating the deviation Delta E (m) between the current frame power spectrum and the long-term power spectrum,
Figure BDA0003828526440000082
logic for judging background noise update according to the deviation of the spectrum offset;
and 7: updating background noise, correcting the signal-to-noise ratio of a sub-band, setting an update flag (update _ flag = TRUE) when the background noise is updated, and updating the background noise of the next frame according to the following formula:
En(m+1,i)＝max{Emin,αnEn(m,i)+(1-αn)Ech(m,i)}，0≤i<NC
where Emin =0.00625 is the allowed subband minimum energy, and α n =0.9 is the subband noise energy smoothing factor;
correcting the signal-to-noise ratio of the sub-band, firstly judging whether the signal-to-noise ratio of the sub-band needs to be corrected through setting and resetting, then correcting the signal-to-noise ratio of the sub-band, then limiting the corrected signal-to-noise ratio of the sub-band by using a signal-to-noise ratio threshold sigma th, inspecting voice measurement when the signal-to-noise ratio is corrected, and if the signal-to-noise ratio of the sub-band is smaller than the voice measurement threshold, assigning the signal-to-noise ratio of each sub-band to be 1;
and step 8: and calculating the gain of the sub-band by adopting the following steps:
step 8.1: the gain factor gamman of the current frame is calculated,
Figure BDA0003828526440000083
wherein γ min = -13dB, is the minimum gain value, efluor =1, is the lower bound of noise energy, en (m) is the estimated value of the noise power spectrum of the previous frame;
step 8.2: the gain γ dB (i) for each subband is calculated,
γdB(i)＝μg(σ”q(i)-σth)+γn，0≤i<NC，
wherein μ g =0.39, is a gain factor;
step 8.3: linear subband gain γ ch (i) is calculated,
Figure BDA0003828526440000091
the spectrum of the input signal is then filtered according to the gain of the subband, and the spectrum G (k) of each subband of the input signal is multiplied by the subband gain γ ch (i), thereby realizing the filtering of the spectrum of the input signal. To ensure that the imaginary part of the inverse fourier transform is zero, H (k) is required to be conjugate symmetric, i.e. the following condition must be satisfied: h (M-k) = H (k), 0<k < -M/2, wherein < > represents complex conjugation;
and step 9: reconstructing the time domain signal by adopting the following steps:
step 9.1: the filtered frequency domain signal is transformed into a time domain signal by inverse fourier transform,
Figure BDA0003828526440000092
step 9.2: the signals are subjected to an overlap-add process,
Figure BDA0003828526440000093
step 9.3: the de-emphasis process is performed on the signal,
s’(n+1)＝h’(n)+ξd s’(n)，
ξ d =0.8, which is a de-emphasis factor;
and then, carrying out automatic level control, wherein the automatic level control comprises two variables of output gain ALC _ gain and gain _ dB represented by decibel of the output gain ALC _ gain and the gain _ dB, the ALC _ gain and the gain _ dB respectively keep initial values of 1 dB and 0dB before the two values are calculated by adopting an automatic level control method, comparing the energy of the current frame with the long-term average energy through the automatic level control, judging to enhance or attenuate the voice by an algorithm, updating the long-term average energy according to the energy of the current frame, finishing noise suppression processing, and outputting the voice.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims (8)

1. A space equipment hands-free call noise suppression processing method is characterized by comprising the following steps:
step 1: initializing equipment variables, namely initializing variable parameters of the space equipment;
step 2: converting input voice from a time domain to a frequency domain, and dividing the input voice into a plurality of sub-bands;
and 3, step 3: calculating the energy of each sub-band according to a first estimation formula;
and 4, step 4: calculating the signal-to-noise ratio of each sub-band by combining a second estimation formula according to the energy of each sub-band;
and 5: carrying out voice measurement calculation according to the signal-to-noise ratio of the sub-band;
step 6: calculating the deviation of the spectrum offset, and judging the logic of updating the background noise;
and 7: updating background noise and correcting the signal-to-noise ratio of the sub-band;
and 8: calculating the gain of a sub-band, and filtering the frequency spectrum of the input signal according to the gain of the sub-band;
and step 9: and reconstructing a time domain signal, controlling an automatic level, finishing noise suppression processing and outputting voice.
2. The spatial device hands-free call noise suppression processing method according to claim 1, wherein in step 1, a frame number variable, an input data frame buffer variable, a pre-emphasis and de-emphasis variable, an output overlap-add data variable, an output array variable, a continuous speech frame counter variable are initialized to zero; and initializing a sub-band energy estimation variable, a long-time power spectrum estimation variable and a sub-band noise estimation variable into determined values.
3. The method for processing noise suppression of hands-free call of spatial equipment according to claim 1, wherein in step 2, the input voice is converted from time domain to frequency domain by adopting an interframe overlapping method, and the frame length is 10ms.
4. The spatial device hands-free call noise suppression processing method according to claim 1, wherein in step 6, calculating the deviation of the spectral shift includes the steps of:
step 6.1: calculating a dB value of the sub-band power spectrum;
step 6.2: calculating a long-term average power spectrum;
step 6.3: and calculating the deviation between the current frame power spectrum and the long-term power spectrum.
5. The spatial device hands-free call noise suppression processing method according to claim 4, wherein in step 6, the background noise update logic includes regular update logic and forced update logic.
6. The spatial device hands-free call noise suppression processing method according to claim 1, wherein in step 8, calculating the subband gain comprises the steps of:
step 8.1: calculating a gain factor of the current frame;
step 8.2: calculating the gain of each sub-band;
step 8.3: linear subband gains are calculated.
7. The spatial device hands-free call noise suppression processing method according to claim 1, wherein in step 9, the reconstruction of the time domain signal comprises the steps of:
step 9.1: transforming the filtered frequency domain signal into a time domain signal by inverse Fourier transform;
step 9.2: performing overlap-add processing on the signals;
step 9.3: the signal is de-emphasized.
8. The spatial device hands-free call noise suppression processing method according to claim 1, wherein in step 9, the automatic level control includes an output gain variable control and a decibel representation variable control.
CN202211077167.9A 2022-09-01 2022-09-01 Method for suppressing and processing hand-free call noise of space equipment Pending CN115426430A (en)

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