CN1737905A - Device and method for eliminating voice communication terminal background noise - Google Patents

Device and method for eliminating voice communication terminal background noise Download PDF

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CN1737905A
CN1737905A CNA2004100585789A CN200410058578A CN1737905A CN 1737905 A CN1737905 A CN 1737905A CN A2004100585789 A CNA2004100585789 A CN A2004100585789A CN 200410058578 A CN200410058578 A CN 200410058578A CN 1737905 A CN1737905 A CN 1737905A
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background noise
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noise signal
conversion module
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CN100337270C (en
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张强
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Huawei Technologies Co Ltd
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    • 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
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R1/00—Details of transducers, loudspeakers or microphones
    • H04R1/10—Earpieces; Attachments therefor ; Earphones; Monophonic headphones
    • H04R1/1083—Reduction of ambient noise

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  • Computational Linguistics (AREA)
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  • Audiology, Speech & Language Pathology (AREA)
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Abstract

This invention discloses one language communication terminal noisy eliminating device, which comprises D/A converter module, player, voice senor device, A/D converter module, adaptive filter, noisy estimation module and adding module. This invention also discloses one method, which comprises the following steps: a, collecting voice communication terminal language signals and receiving background signals; b, receiving background noisy signals from the gotten signals; c, after noisy signal anti-phase for adding with sound communication terminals and offsetting the overlapped signals with background noise.

Description

Background noise eliminating device and method for voice communication terminal
Technical Field
The present invention relates to a speech processing technology of a communication terminal, and in particular, to a background noise eliminating device and method for a speech communication terminal.
Background
With the rapid development and increasing popularity of communication technology, communication has become an important means for people to communicate daily, and therefore, people also put higher demands on the voice quality of conversation. In actual communication, two parties of a communication user often talk in some noisy background environment. At this time, the sound heard by the receiver user includes not only the speech of the sender user but also other sounds around the sender and receiver users, such as the voice of another person, the sound of footsteps, the sound of collision of articles, music, and the sound of vehicles. These sounds other than the speech voices of both parties of the communication user are referred to as background noise, the background noise located around the sender user is referred to as sender background noise, and the background noise located around the receiver user is referred to as receiver background noise.
Fig. 1 is a schematic diagram of a voice transmission process of a mobile communication terminal, in which a microphone of a sender receives a voice of the sender and background noise of the sender at the same time, and after sampling, encoding, transmitting, and decoding the received voice, the voice is transmitted to an earphone or a speaker of a receiver, and the receiver listens to the transmitted voice through the earphone or the speaker and also listens to the background noise of the receiver. It can be seen that the speech is subjected to dual interference of the background noise of the transmitting party and the background noise of the receiving party during the transmission process. In many cases, the background noise masks the voice of the communicating speaker, so that the listener at the receiving end cannot correctly acquire the voice information transmitted by the speaker, thereby causing communication difficulties.
Based on the voice transmission process of the mobile communication terminal shown in fig. 1, the existing mobile communication terminals, such as CDMA mobile phones and GSM mobile phones, adopt the adaptive filtering technique to eliminate the background noise of the transmitting party before the vocoder of the transmitting party encodes the voice. Fig. 2 is a schematic structural diagram of a device for eliminating background noise of a transmitting party in a mobile communication terminal in the prior art, which includes: a microphone 201, a sampling module 202, an adaptive filter 203 and a speech coding module 204.
The microphone 201 receives the sender voice and the background noise, and then transmits the received sender voice and the received background noise to the sampling module 202; after receiving the sender's voice and background noise, the sampling module 202 samples them, that is, converts the analog signal into a digital signal, and outputs the obtained digital signal to the adaptive filter 203; the adaptive filter 203 eliminates background noise of the received signal and outputs the remaining voice signal to the voice coding module 204; the speech encoding module 204 encodes the received speech signal.
The specific structure of the adaptive filter 203 is shown in fig. 3. Where, x (n) is an input signal received by the microphone after the sampling process, and includes a sending-side voice signal s (n) and a sending-side background noise signal v (n), that is, x (n) ═ s (n) + v (n). x (n-delta) is delayed by delta to obtain x (n-delta) s (n-delta) + v (n-delta), and x (n-delta) passes through the filter part of the adaptive filter 203 to output the estimated value of the speech signal s (n)And the estimated value is calculated
Figure A20041005857800062
Is subtracted from the input signal x (n) to obtain the error signal e (n). The subtraction operation is not a general algebraic subtraction, but needs a corresponding algorithm to perform the operation, such as power spectral density analysis of the relevant power.
The adaptive filter 203 uses a Least Mean Square (LMS) algorithm with a weight wi(n) from the error signal e ( n ) = x ( n ) - s ^ ( n ) = v ( n ) + ( s ( n ) - s ^ ( n ) ) And adjusting, wherein i is more than or equal to 0 and less than or equal to M-1, and M is the order of the filter. If the weight vector W (n) and the input vector X (n) are defined as:
W(n)＝[w0(n) w1(n) … wM-2(n) wM-1(n)]T
X(n)＝[x0(n) x1(n) … xM-2(n) xM-1(n)]T
the LMS algorithm of the adaptive filter can be expressed as:
<math> <mrow> <mover> <mi>s</mi> <mo>^</mo> </mover> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msup> <mi>W</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mi>X</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>-</mo> <mi>&Delta;</mi> <mo>)</mo> </mrow> <mo>=</mo> <msup> <mi>W</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mi>S</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>-</mo> <mi>&Delta;</mi> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mi>W</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mi>V</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>-</mo> <mi>&Delta;</mi> <mo>)</mo> </mrow> </mrow> </math>
e ( n ) = x ( n ) - s ^ ( n )
W(n+1)＝W(n)+μX(n)e(n)。
where μ is the step size factor when searching according to the minimum mean square error criterion.
Since speech has quasi-periodicity, the speech signals s (n) and s (n- Δ) are strongly correlated, while the noise signals v (n) and v (n- Δ) are considered uncorrelated, and the noise signals and the speech signals are also considered uncorrelated. Based on this assumption, the input signal x (n) can be estimatedThe more relevant components. Meanwhile, the weight w of the filter is adjustedi(n) minimizing the mean square error of e (n) to obtain the best estimated value s (n) of the speech signal s (n) under the minimum mean square error criterion.
Although the prior art provides a scheme for eliminating the background noise of the sender, which can reduce the interference of the background noise to the speech, the prior art only considers the elimination of the background noise of the sender, but does not perform any processing on the background noise of the receiver, and ignores the interference of the background noise of the receiver to the sound emitted by the earphone of the receiver, and particularly when the receiver is in a noisy environment, the interference of the background noise of the receiver to the speech of the speaker is particularly serious. However, the current method for overcoming the background noise of the receiving party by the mobile communication terminal is to increase the volume of the earphone, and the method is limited by the maximum volume of the earphone, so that the effect in a noisy environment is still poor. Similarly, the conventional fixed communication terminal has the above-described problem.
Disclosure of Invention
In view of the above, the main object of the present invention is to provide an apparatus for eliminating background noise of a voice communication terminal, which can eliminate the background noise of a receiving side and reduce the interference of the background noise of the receiving side to a receiving side.
Another object of the present invention is to provide a method for eliminating background noise of a voice communication terminal, which can reduce interference of background noise of a receiving party to a receiving party.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
the invention discloses a device for eliminating background noise of a voice communication terminal, which comprises:
the D/A conversion module is used for converting the digital signal into an analog signal and outputting the analog signal;
the player is used for receiving and playing the analog signal output by the D/A conversion module;
the device also includes:
the sound sensing device is used for collecting and outputting the sound played by the player and the background noise of a receiver;
the A/D conversion module is used for converting the analog signal output by the sound sensing device into a digital signal and outputting the digital signal;
the adaptive filter is used for receiving a voice signal of a sender and the digital signal output by the A/D conversion module, estimating and outputting a noise signal in the digital signal output by the A/D conversion module;
the noise estimation module is used for predicting and outputting a background noise signal of a receiving party according to the noise signal output by the self-adaptive filter;
and the adder module is used for performing reverse phase superposition on the background noise signal of the receiving party output by the noise estimation module and the voice signal of the sending party and outputting the result to the D/A conversion module.
Wherein the sound sensing device may comprise at least one microphone.
In the above solution, the apparatus may further include a superimposer, which is located between the microphones and the a/D conversion module, and is configured to superimpose analog signals output by the microphones and output the superimposed analog signals to the a/D conversion module;
or the superimposer is positioned between the A/D conversion module and the self-adaptive filter and is used for superimposing the signals which are output to the A/D conversion module by the plurality of microphones and are respectively subjected to analog-to-digital conversion by the A/D conversion module and outputting the superimposed signals to the self-adaptive filter.
In addition, the a/D conversion module may be an a/D conversion module that performs analog-to-digital conversion on signals output by the plurality of microphones and outputs the signals to the adaptive filter; the adaptive filter may be an adaptive filter that receives the multiple signals output by the a/D conversion module and performs filtering processing on the multiple signals, respectively.
The player may contain at least one earphone or speaker.
The invention also discloses a method for eliminating the background noise of the voice communication terminal, which comprises the following steps:
a. collecting a voice signal sent by a voice communication terminal and a background noise signal of a receiving party;
b. estimating a receiver background noise signal from the obtained signal;
c. and superposing the estimated background noise signal of the receiving party with the voice signal of the sending party received by the voice communication terminal after the phase of the background noise signal of the receiving party is reversed, and carrying out noise cancellation on the superposed signal and the actual background noise of the receiving party.
Wherein the step a may further comprise:
simultaneously acquiring multiple paths of signals, superposing the acquired multiple paths of signals, and performing analog-to-digital conversion on the superposition result and outputting the result;
or simultaneously acquiring multiple paths of signals, respectively performing analog-to-digital conversion on the acquired multiple paths of signals, and then overlapping and outputting conversion results.
In the foregoing scheme, the step b may include: the method comprises the steps of taking a voice signal of a sending party received by a voice communication terminal as a reference signal for adaptive filtering processing, obtaining a noise signal estimation value in a digital signal by using the adaptive filtering processing, and then predicting an estimation value of a background noise signal of a receiving party by using the noise signal estimation value.
In addition, the step a may further include: simultaneously collecting multiple paths of signals, respectively carrying out analog-to-digital conversion on the multiple paths of signals and respectively outputting the multiple paths of signals; correspondingly, the step b further comprises the following steps: and respectively carrying out self-adaptive filtering processing on each path of output digital signals to obtain a noise signal estimation value in each path of digital signals, and predicting an estimation value of a background noise signal of a receiving party by using the obtained noise signal estimation value.
The method for obtaining the noise signal by using the adaptive filtering process may be: an estimate of the noise signal is obtained using a minimum mean square error algorithm.
In the foregoing embodiment, the method may further include: and respectively carrying out adaptive filtering processing on the multi-path input signals, and selecting the maximum value of a plurality of processing results obtained through the adaptive filtering processing or the sum of all the processing results at this time as the estimated value of the noise signal.
In the above scheme, the method for predicting the receiver background noise signal estimation value may be: the background noise signal estimation value at the current moment is the sum of the background noise signal estimation value at the previous moment and the noise signal estimation value obtained through the self-adaptive filtering processing.
The key point of the invention is that: the device mainly comprises a self-adaptive filter and a noise estimation module which are used for estimating background noise, the background noise is estimated through the self-adaptive filter and the noise estimation module, the background noise estimation value is superposed with a voice signal after being in an anti-phase state, then the voice signal containing the background noise estimation value is played through an earphone, the background noise estimation value in the voice signal and the actual background noise of a receiving party are mutually offset, and the voice signal after noise elimination is obtained.
Therefore, the device and the method for eliminating the background noise of the voice communication terminal can well offset the background noise around the earphone, reduce the interference of the background noise of a receiving party to the receiving party and ensure that the receiving party can clearly hear the voice of the sending party under the condition that the volume of the earphone is not large.
Drawings
Fig. 1 is a schematic diagram of a voice delivery process of a mobile communication terminal;
fig. 2 is a schematic structural diagram of a device for eliminating background noise of a transmitting side in a mobile communication terminal according to the prior art;
fig. 3 is a schematic structural diagram of an adaptive filter in the transmitting-side background noise removal apparatus shown in fig. 2;
fig. 4 is a schematic structural composition diagram of an embodiment of a device for eliminating background noise of a receiving party in a mobile communication terminal according to the present invention;
FIG. 5 is a block diagram of an adaptive filter in an embodiment of the receiving background noise cancellation apparatus shown in FIG. 4;
FIG. 6 is a schematic diagram illustrating an arrangement of an earphone and a microphone according to an embodiment of the apparatus for removing background noise of a receiving party of the present invention;
FIG. 7 is a flow chart of a method for eliminating background noise of a voice communication terminal according to the present invention;
fig. 8 is a schematic structural component diagram of an embodiment of a device for eliminating background noise of a receiving party in a fixed communication terminal according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The device provided by the invention mainly comprises a self-adaptive filter and a noise estimation module which are used for estimating the background noise, the background noise is estimated through the self-adaptive filter and the noise estimation module, the background noise estimation value is superposed with the voice signal after the phase reversal, and then the voice signal containing the background noise estimation value is played through an earphone, so that the background noise estimation value and the actual background noise of a receiving party are mutually offset, and the voice signal after noise elimination is obtained.
Fig. 4 is a schematic structural diagram of an embodiment of the apparatus for removing background noise at a receiving end according to the present invention, including: adder module 401, D/A conversion module 402A headphone 403, a voice transmission channel 404, a microphone 405, an a/D conversion module 406, an adaptive filter 407, and a noise estimation module 408. The adder module 401 is configured to add the transmitting side voice signal s (n) received by the voice communication terminal and the receiving side background noise signal estimation value with the opposite phaseStacking; the D/a conversion module 402 is used to convert the digital signal into an analog signal, which is referred to as digital-to-analog conversion for short; the earphone 403 is a player for playing sound signals, and is used to play signals obtained by superimposing a voice signal and an opposite-phase receiver background noise signal, or a speaker may be used as a player instead of the earphone; the voice transmission channel 404 is used for transmitting the sound signal to the receiving party, and voice and noise are superposed on the voice transmission channel 404; the microphone 405 is a sensing device for collecting a sound signal, and is used for receiving a voice signal and background noise left after cancellation; the a/D conversion module 406 is used for sampling the analog signal, that is, converting the analog signal into a digital signal, referred to as analog-to-digital conversion; the adaptive filter 407 is configured to estimate a noise signal value in the acquired signal; the noise estimation module 408 is used to predict an estimate of the background noise.
As shown in fig. 4, a voice signal of a transmitting side received by the voice communication terminal is transmitted to the D/a conversion module 402 through the adder module 401, and the D/a conversion module 402 converts the received signal from a digital signal to an analog signal and outputs the converted analog signal to the earphone 403. The earphone 403 plays the received analog signal and transmits it to the receiving party and the microphone 405 through the voice transmission channel 404, and the voice transmission channel 404 also transmits the receiving party background noise v to the receiving party and the microphone 405.
The microphone 405 receives the voice signal and the noise signal to obtain a signal x, and the signal x is sent to the a/D conversion module 406 for sampling to obtain x (n), and then the a/D conversion module 406 sends x (n) to the adaptive filter 407. The adaptive filter 407 performs adaptive filtering with the speech signal s (n) as a reference input to estimate an estimated value of the noise signal
Figure A20041005857800112
. The noise estimation module 408 estimates a value based on the noise signalEstimating value of predictive background noise signalAnd estimating the background noise
Figure A20041005857800115
To adder 401.
Adder module 401 estimates speech signal s (n) and background noise signal
Figure A20041005857800116
Performing superposition to obtain a signalAnd outputs the signal to the D/a conversion module 402, and plays the signal through the earphone 403. Background noise estimate in signals broadcast by headphone 403
Figure A20041005857800118
And the receiver background noise v cancel each other out so that the sound delivered to the receiver and microphone 405 is primarily speech and some noise left after cancellation.
The specific structure of the adaptive filter 407 is shown in fig. 5. Wherein x (n) including the speech signal and the noise signal passes through the filter portion of the adaptive filter 407 to recover the best estimation value of the speech signal s (n)Best estimation of speech signal s (n)
Figure A20041005857800122
Subtracting the delayed signal s (n-delta) of the speech signal s (n) to obtain the error signal
The adaptive filter 407 uses the LMS algorithm with a weight wi(n) from the error signal <math> <mrow> <msub> <mover> <mi>v</mi> <mo>^</mo> </mover> <mi>e</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <mover> <mi>s</mi> <mo>^</mo> </mover> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>-</mo> <mi>s</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>-</mo> <mi>&Delta;</mi> <mo>)</mo> </mrow> </mrow> </math> And adjusting, wherein i is more than or equal to 0 and less than or equal to M-1, and M is the order of the filter. Since the speech signal and the background noise signal are uncorrelated, the weight w of the filter is adjustedi(n) reactingThe mean square error of the method is minimum, so that the best estimated value of the x (n) middle voice signal s (n) under the minimum mean square error criterion can be obtained
Figure A20041005857800127
At the same time consider thatIs the best estimate of the residual noise signal after background noise cancellation. Where Δ is the delay of the speech signal and can be searched according to the minimum mean square error criterion. Of course, the adaptive filter 407 may also employ other adaptive algorithms and optimization criteria.
The noise estimation module 408 is used to estimate the best estimation value based on the noise signal
Figure A20041005857800129
A current background noise estimate is predicted. The simplest prediction method is v ^ ( n ) = v ^ ( n - 1 ) + v ^ e ( n ) . Wherein,
Figure A200410058578001211
for the current background noise estimate value,
Figure A200410058578001212
is an estimate of the background noise at the previous time instant.
In order to make the noise cancellation effect better, the number of the earphones 403 and the microphones 405 in fig. 4 may be plural, and the number of the earphones and the Microphones (MIC) may be different, and the microphones may be located in an area where the noise cancellation is desired. Typically, the area where it is desired to cancel noise is around the headset when the phone is received, but there are exceptions in other applications. For example, when sleeping, if the mobile phone is used as a tool for reducing surrounding noise, the area can be larger. Taking an earphone and three microphones as an example, the arrangement between them is shown in fig. 6. Wherein, the earphone is located the centre, and three microphones are located around the earphone and become 120 degrees angular distribution.
The signals received by the microphones simultaneously can be transmitted to the adaptive filter after being superposed, or can be transmitted to the adaptive filter independently and processed by the adaptive filter respectively. If superposition is needed, a superposer is needed to be added at a corresponding position in the device. For example, the output signals of multiple microphones can be added together before a/D conversion, and then the adder is arranged between the microphones and the a/D conversion module; or the A/D conversion module and the adaptive filter are overlapped together after the A/D conversion, and the superimposer is arranged between the A/D conversion module and the adaptive filter. Alternatively, the signals may be subjected to a/D conversion and then sent to adaptive filters for processing.
Based on the apparatus shown in fig. 4, the background noise cancellation method for a voice communication terminal according to the present invention is shown in fig. 7, and includes the following steps:
step 701, collecting a sound signal obtained by adding the sound emitted by the earphone of the voice communication terminal and the background noise of the receiving party, and converting the sound signal from an analog signal to a digital signal.
The number of the microphones used for acquiring the signals may be one or more, that is, the acquiring signals may be one or more. When a plurality of microphones are used for collecting signals, the signals output by the plurality of microphones can be firstly superposed, and then A/D conversion is carried out and output; or the signals output by a plurality of microphones are respectively subjected to A/D conversion and then are superposed for output; alternatively, signals output from a plurality of microphones may be a/D converted and then output.
Step 702, using a voice signal of a sender as reference input, performing adaptive filtering processing on a collected digital voice signal, and estimating a noise signal in the digital voice signal; the adaptive filter may adopt LMS algorithm, or may adopt other adaptive algorithms and optimal criteria.
For the case where the signals output from the plurality of microphones are subjected to a/D conversion and then output to the adaptive filters, it is necessary to perform adaptive filtering processing on each of the signals. A brief explanation is given here by way of example of three microphones and one earphone.
For example, the signals received by three microphones are respectively processed by adaptive filters under the minimum mean square error criterion to obtain the estimated values of three noise signals
Figure A20041005857800131
Figure A20041005857800132
And
Figure A20041005857800133
. Then calculate v ^ e ( n ) = max ( v ^ e 1 ( n ) , v ^ e 2 ( n ) , v ^ e 3 ( n ) ) Or v ^ e ( n ) = sum ( v ^ e 1 ( n ) , v ^ e 2 ( n ) , v ^ e 3 ( n ) ) , Where max is the maximum operation and sum is the summation operation. That is, the maximum value of the three estimated values obtained after the adaptive filtering process may be selected or the three estimated values may be superimposed to be output as the adaptive filtering result. Because of the different delays of the signals, it is necessary to estimate the noise signals of the channels, for example
Figure A20041005857800141
And
Figure A20041005857800142
and carrying out synchronous processing, and then selecting or superposing.
Since the human ear's perception of sound is not proportional to the power of sound, but proportional to the decibel number of sound, it is also possible to do so
Figure A20041005857800143
Taking the logarithm of the absolute value of, i.e.Then to make
Figure A20041005857800145
The minimum is the optimal criterion. Accordingly, for the case of multiple inputs, it is also possible to do so for each
Figure A20041005857800146
Is logarithmic and then summed, i.e. <math> <mrow> <mi>&Sigma;</mi> <mrow> <mo>(</mo> <mi>log</mi> <mo>|</mo> <msub> <mover> <mi>v</mi> <mo>^</mo> </mover> <mi>e</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </math> Then to make <math> <mrow> <mi>&Sigma;</mi> <mrow> <mo>(</mo> <mi>log</mi> <mo>|</mo> <msub> <mover> <mi>v</mi> <mo>^</mo> </mover> <mi>e</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> </mrow> </math> The minimum is the optimal criterion.
703, predicting an estimation value of an actual background noise signal according to the obtained noise signal; the simplest prediction method is as follows: v ^ ( n ) = v ^ ( n - 1 ) + v ^ e ( n ) . wherein,for the current background noise signal estimate,is an estimate of the background noise signal at the previous time instant,
Figure A200410058578001412
is the best estimation value of the noise signal obtained by the adaptive filtering.
Step 704, superposing the actual background noise signal estimation value obtained by prediction with a sender voice signal after the actual background noise signal estimation value is in an opposite phase, and outputting the superposed signal through an earphone;
step 705, the sound signal output by the earphone and the background noise of the receiving party are superposed during voice transmission to cancel the background noise, and the receiving party obtains the voice signal of the sending party after noise cancellation.
The above scheme can be applied to fixed communication terminals as well, and the differences are only that: because the signal received by the existing fixed communication terminal is an analog signal, the received analog signal needs to be converted into a digital signal first, and then noise estimation and noise elimination processing are carried out; accordingly, as shown in fig. 8, an a/D conversion module 800 is added before the input end of the voice signal of the sender in the apparatus of the present invention, so as to convert the input analog signal into a digital signal.
According to the scheme, the residual noise after noise cancellation can be obtained through adaptive filtering processing, the background noise of the receiving party can be estimated through continuous superposition of noise prediction processing, then the estimated background noise of the receiving party and the actual background noise of the receiving party are used for cancellation processing, and therefore the interference of the background noise to the receiving party can be reduced.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (12)

1. An apparatus for removing background noise of a voice communication terminal, comprising:
the D/A conversion module is used for converting the digital signal into an analog signal and outputting the analog signal;
the player is used for receiving and playing the analog signal output by the D/A conversion module;
it is characterized in that the device further comprises:
the sound sensing device is used for collecting and outputting the sound played by the player and the background noise of a receiver;
the A/D conversion module is used for converting the analog signal output by the sound sensing device into a digital signal and outputting the digital signal;
the adaptive filter is used for receiving a voice signal of a sender and the digital signal output by the A/D conversion module, estimating and outputting a noise signal in the digital signal output by the A/D conversion module;
the noise estimation module is used for predicting and outputting a background noise signal of a receiving party according to the noise signal output by the self-adaptive filter;
and the adder module is used for performing reverse phase superposition on the background noise signal of the receiving party output by the noise estimation module and the voice signal of the sending party and outputting the result to the D/A conversion module.
2. The device of claim 1, wherein the sound sensing device comprises at least one microphone.
3. The device of claim 2, further comprising a superimposer, located between the microphones and the a/D conversion module, for superimposing the analog signals output by the microphones and outputting the superimposed analog signals to the a/D conversion module;
or the superimposer is positioned between the A/D conversion module and the self-adaptive filter and is used for superimposing the signals which are output to the A/D conversion module by the plurality of microphones and are respectively subjected to analog-to-digital conversion by the A/D conversion module and outputting the superimposed signals to the self-adaptive filter.
4. The apparatus of claim 2, wherein the a/D conversion module is an a/D conversion module that performs analog-to-digital conversion on the signals output by the plurality of microphones respectively and outputs the signals to the adaptive filter respectively; the adaptive filter is used for receiving the multi-channel signals output by the A/D conversion module and respectively carrying out filtering processing.
5. The apparatus of claim 1, wherein the player comprises at least one of an earphone or a speaker.
6. A method for eliminating background noise of a voice communication terminal is characterized by comprising the following steps:
a. collecting a voice signal sent by a voice communication terminal and a background noise signal of a receiving party;
b. estimating a receiver background noise signal from the obtained signal;
c. and superposing the estimated background noise signal of the receiving party with the voice signal of the sending party received by the voice communication terminal after the phase of the background noise signal of the receiving party is reversed, and carrying out noise cancellation on the superposed signal and the actual background noise of the receiving party.
7. The method of claim 6, wherein step a further comprises:
simultaneously acquiring multiple paths of signals, superposing the acquired multiple paths of signals, and performing analog-to-digital conversion on the superposition result and outputting the result;
or simultaneously acquiring multiple paths of signals, respectively performing analog-to-digital conversion on the acquired multiple paths of signals, and then overlapping and outputting conversion results.
8. The method of claim 6, wherein step b comprises: the method comprises the steps of taking a voice signal of a sending party received by a voice communication terminal as a reference signal for adaptive filtering processing, obtaining a noise signal estimation value in a digital signal by using the adaptive filtering processing, and then predicting an estimation value of a background noise signal of a receiving party by using the noise signal estimation value.
9. The method of claim 6, wherein step a further comprises: simultaneously collecting multiple paths of signals, respectively carrying out analog-to-digital conversion on the multiple paths of signals and respectively outputting the multiple paths of signals; correspondingly, the step b further comprises the following steps: and respectively carrying out self-adaptive filtering processing on each path of output digital signals to obtain a noise signal estimation value in each path of digital signals, and predicting an estimation value of a background noise signal of a receiving party by using the obtained noise signal estimation value.
10. The method according to claim 8 or 9, wherein the method for obtaining the noise signal by using the adaptive filtering process comprises: an estimate of the noise signal is obtained using a minimum mean square error algorithm.
11. The method of claim 10, further comprising: and respectively carrying out adaptive filtering processing on the multi-path input signals, and selecting the maximum value of a plurality of processing results obtained through the adaptive filtering processing or the sum of all the processing results at this time as the estimated value of the noise signal.
12. The method according to claim 8 or 9, wherein the method of predicting the receiver background noise signal estimate is: the background noise signal estimation value at the current moment is the sum of the background noise signal estimation value at the previous moment and the noise signal estimation value obtained through the self-adaptive filtering processing.
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