CN115348507A - Impulse noise suppression method, system, readable storage medium and computer equipment - Google Patents
Impulse noise suppression method, system, readable storage medium and computer equipment Download PDFInfo
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R3/00—Circuits for transducers, loudspeakers or microphones
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
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Abstract
The invention provides an impulse noise suppression method, an impulse noise suppression system, a readable storage medium and computer equipment, wherein the method comprises the following steps: acquiring an audio signal of a current environment in real time, and extracting audio features of the audio signal to obtain a plurality of audio features of the audio signal; carrying out characteristic discrimination on each audio characteristic by using an audio database so as to identify pulse noise signals in the audio signals; judging whether the impulse noise signal is larger than a preset audio threshold value or not; if the impulse noise signal is larger than the preset audio threshold, inhibiting the impulse sample amplitude in the impulse noise signal by using an amplitude limiting function, and carrying out dynamic range companding on the processed impulse noise signal to obtain a primary impulse noise signal; and carrying out feedback elimination on the preliminary pulse noise signal so as to inhibit the pulse noise signal in the audio signal and obtain a target signal. The invention can inhibit the pulse noise signal in the audio signal so as to avoid the influence of the burst noise on the comfort level caused by the burst noise entering the human ear.
Description
Technical Field
The present invention relates to the field of audio signal processing technologies, and in particular, to a method and a system for suppressing impulse noise, a readable storage medium, and a computer device.
Background
With the rapid development of science and technology and the improvement of the comprehensive level of high-technology informatization, the demand of people for video/audio services is exponentially increased. When people are engaged in video/audio services, for example: a headset is generally worn for voice call, video call, listening to music, etc., and as the usage rate of the headset increases, the audio optimization effect of the headset becomes more and more important.
When people wear the earphone to carry out video/audio service, if be in under the noisy environment, can influence the use comfort of video/audio service, among the prior art, usually through adopting the mode of making an uproar to fall the sound audio reduction in with the environment of ambient sound, and then reduce the influence of ambient sound to people's pleasant sound to promote people's experience sense and use comfort.
However, when sudden noise is encountered, the sudden noise cannot be recognized due to the ambient noise reduction, and the sudden noise may directly enter the ear, thereby affecting the experience and comfort of the user.
Disclosure of Invention
In view of the foregoing, it is an object of the present invention to provide an impulse noise suppression method, system, readable storage medium and computer device to solve at least the above-mentioned deficiencies in the related art.
The invention provides an impulse noise suppression method, which comprises the following steps:
acquiring an audio signal of a current environment in real time, and performing audio feature extraction on the audio signal to obtain a plurality of audio features of the audio signal;
carrying out characteristic discrimination on each audio characteristic by using an audio database so as to identify impulse noise signals in the audio signals;
judging whether the impulse noise signal is larger than a preset audio threshold value or not;
if the impulse noise signal is larger than a preset audio threshold, inhibiting the impulse sample amplitude in the impulse noise signal by using an amplitude limiting function, and carrying out dynamic range companding on the processed impulse noise signal to obtain a primary impulse noise signal;
and carrying out feedback elimination on the preliminary pulse noise signal so as to inhibit the pulse noise signal in the audio signal and obtain a target signal.
Further, the step of performing audio feature extraction on the audio signal to obtain a plurality of audio features of the audio signal includes:
acquiring audio parameters of the audio signal, and extracting a plurality of audio frame features in the audio signal based on the unit frame of the audio signal and the audio parameters;
and processing the audio frame characteristics through the mean value, the variance and the standard deviation in sequence to obtain the audio segment characteristics corresponding to the audio frame characteristics.
Further, the step of performing feature discrimination on each audio feature by using an audio database to identify an impulse noise signal in the audio signal includes:
acquiring the sampling frequency of the audio signal and data in each frame of each audio segment characteristic;
and calculating the short-time energy and the short-time zero-crossing number of the data in each frame according to the sampling frequency, and identifying pulse noise signals in the audio band characteristics according to the short-time energy and the short-time zero-crossing number of the data in each frame and the short-time energy threshold value and the zero-crossing number threshold value.
Further, the calculation formula of the short-time energy of each piece of intra-frame data is as follows:
in the formula, E n For short-time energy, x (m) is intra-frame data, w (N) is a window function, and N is the number of data frame samples corresponding to the sampling frequency.
Further, the calculation formula of the short-time zero-crossing number of each piece of intra-frame data is as follows:
in the formula, Z n For short time zero crossing, x (m) is intraframe data, sgn [ ·]As a function of the sign, i.e.
w (N) is a window function, and N is the number of data frame samples corresponding to the sampling frequency.
Further, the step of identifying the impulse noise signal in each audio segment feature according to the short-time energy and the short-time zero-crossing number of the data in each frame and the short-time energy threshold and the zero-crossing number threshold comprises:
when the short-time energy of the data in the frame is greater than or equal to a short-time energy threshold and the short-time zero crossing number of the data in the frame is less than a zero crossing number threshold, judging that the data in the frame is a voice signal;
and when the short-time energy of the data in the frame is smaller than the short-time energy threshold and the short-time zero crossing number of the data in the frame is larger than the zero crossing number threshold, judging that the data in the frame is an impulse noise signal.
The present invention further provides an impulse noise suppression system, including:
the audio signal acquisition module is used for acquiring an audio signal of the current environment in real time and extracting audio features of the audio signal to obtain a plurality of audio features of the audio signal;
the characteristic distinguishing module is used for distinguishing the characteristics of the audio characteristics by utilizing an audio database so as to identify pulse noise signals in the audio signals;
the judging module is used for judging whether the pulse noise signal is larger than a preset audio threshold value or not;
the noise signal suppression module is used for suppressing a pulse sample amplitude in the pulse noise signal by using an amplitude limiting function if the pulse noise signal is greater than a preset audio threshold, and performing dynamic range companding on the processed pulse noise signal to obtain a primary pulse noise signal;
and the feedback elimination module is used for carrying out feedback elimination on the preliminary pulse noise signal so as to inhibit the pulse noise signal in the audio signal and obtain a target signal.
Further, the audio signal acquiring module includes:
an audio parameter acquisition unit configured to acquire an audio parameter of the audio signal and extract a plurality of audio frame features in the audio signal based on a unit frame of the audio signal and the audio parameter;
and the characteristic processing unit is used for processing the audio frame characteristics sequentially through the mean value, the variance and the standard deviation so as to obtain the audio segment characteristics corresponding to the audio frame characteristics.
Further, the feature determination module includes:
the characteristic acquisition unit is used for acquiring the sampling frequency of the audio signal and data in each frame of each audio segment characteristic;
and the characteristic discrimination unit is used for calculating the short-time energy and the short-time zero-crossing number of the data in each frame according to the sampling frequency and identifying the pulse noise signals in the audio band characteristics according to the short-time energy and the short-time zero-crossing number of the data in each frame and the short-time energy threshold value and the zero-crossing number threshold value.
Further, the feature identification unit is further configured to:
when the short-time energy of the data in the frame is greater than or equal to a short-time energy threshold and the short-time zero crossing number of the data in the frame is less than a zero crossing number threshold, judging that the data in the frame is a voice signal;
and when the short-time energy of the data in the frame is less than the short-time energy threshold value and the short-time zero-crossing number of the data in the frame is greater than the zero-crossing number threshold value, judging that the data in the frame is an impulse noise signal.
The invention also proposes a readable storage medium on which a computer program is stored which, when being executed by a processor, implements the impulse noise suppression method described above.
The invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the impulse noise suppression method when executing the computer program.
Compared with the prior art, the invention has the beneficial effects that: the method comprises the steps of acquiring an audio signal of an environment in real time, extracting audio features of the audio signal, and distinguishing the features of the extracted audio features to identify an impulse noise signal in the audio signal, and identifying the impulse noise signal in a feature distinguishing manner to facilitate suppression processing of the impulse noise signal; specifically, when the impulse noise signal is greater than the preset threshold, the amplitude limiting function is used for inhibiting the impulse sample amplitude in the impulse noise signal and performing dynamic range companding so as to improve the impulse noise reduction performance, and further, the impulse noise signal is subjected to feedback elimination so as to inhibit the impulse noise signal in the audio signal, so that the situation that sudden noise enters human ears and affects the comfort level is avoided.
Drawings
FIG. 1 is a flow chart of a method for suppressing impulse noise according to a first embodiment of the present invention;
FIG. 2 is a detailed flowchart of step S101 in FIG. 1;
FIG. 3 is a diagram illustrating characteristics of audio segments in a first embodiment of the present invention;
FIG. 4 is a detailed flowchart of step S102 in FIG. 1;
FIG. 5 is a comparison graph of before and after impulse noise suppression according to the first embodiment of the present invention;
FIG. 6 is a block diagram of an impulse noise suppression system according to a second embodiment of the present invention;
fig. 7 is a block diagram showing a configuration of a computer device according to a third embodiment of the present invention.
Description of the main element symbols:
the following detailed description will further illustrate the invention in conjunction with the above-described figures.
Detailed Description
To facilitate an understanding of the invention, the invention will now be described more fully hereinafter with reference to the accompanying drawings. Several embodiments of the invention are presented in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. Example I
Referring to fig. 1, a method for suppressing impulse noise according to a first embodiment of the present invention is shown, and the method specifically includes steps S101 to S105:
s101, acquiring an audio signal of a current environment in real time, and performing audio feature extraction on the audio signal to obtain a plurality of audio features of the audio signal;
further, referring to fig. 2, the step S101 specifically includes steps S1011 to S1012:
s1011, acquiring audio parameters of the audio signal, and extracting a plurality of audio frame features in the audio signal based on the unit frame of the audio signal and the audio parameters;
and S1012, sequentially processing each audio frame feature by means of mean, variance and standard deviation to obtain an audio segment feature corresponding to each audio frame feature.
In specific implementation, in the process of identifying different audio signals, since the audio signal has a short-time characteristic, an audio parameter of the audio signal is obtained by using a unit frame of the audio signal, where the unit frame is usually 10 to 40ms (20 ms in this embodiment), and a plurality of audio frame features in the audio signal are extracted by using the unit frame and the audio parameter, where the audio frame features include a time-domain feature, a frequency-domain feature, and an acoustic perception feature:
the time domain feature is information of the audio signal in the time domain, and can be understood as time in the horizontal axis and the audio signal in the vertical axis. The information of the audio signal in time is described by the number of zero crossings, the energy of the short time, the volume, the autocorrelation coefficient, and the like.
The number of zero crossings is: the audio signal passes through the number of zero crossings from positive to negative and from negative to positive. For example: voiced sounds have a low zero crossing count and unvoiced sounds have a high zero crossing count (voiced sounds are voiced sounds when the vocal cords vibrate and unvoiced sounds are unvoiced sounds when the vocal cords do not vibrate).
The short-time energy is then: the calculation method by energy is used to monitor the switching moments of voiced and unvoiced sounds. In this embodiment, the zero crossing number is low where the short-time energy is large, and the zero crossing number is high where the short-time energy is small.
The frequency domain features are the time domain waveform signals are converted to frequency spectrum and then calculated.
Further, the audio frame features are processed sequentially through a mean, a variance and a standard deviation, so as to obtain audio segment features corresponding to the audio frame features (see fig. 3 for details).
S102, performing characteristic judgment on each audio characteristic by using an audio database to identify pulse noise signals in the audio signals;
further, referring to fig. 4, the step S102 specifically includes steps S1021 to S1022:
s1021, acquiring the sampling frequency of the audio signal and data in each frame of each audio segment characteristic;
s1022, calculating the short-time energy and the short-time zero-crossing number of the data in each frame according to the sampling frequency, and identifying the pulse noise signals in the characteristics of each audio segment according to the short-time energy and the short-time zero-crossing number of the data in each frame and the short-time energy threshold value and the zero-crossing number threshold value.
In specific implementation, since the audio signal is an unsteady signal and has a short-time stationary characteristic, most of the noise is steady, such as white noise/machine noise, and most of the energy in the audio signal is contained in a low frequency band, while the noise signal is usually smaller in energy and contains information of a higher frequency band;
therefore, in this embodiment, the sampling frequency of the audio signal and the data in each frame of the audio segment characteristics are obtained, where in this embodiment, the sampling frequency is 8KHz, which means that each frame contains 160 sample points, the short-time energy of the data in each frame is calculated according to the sampling frequency and the corresponding sample points, i.e. the short-time energy of the audio signal, the sample points in the frame are shifted by 1, the product corresponding to two adjacent sample points is calculated, where the point with the negative sign is the zero crossing here, the short-time zero-crossing number of the frame is calculated by the product number of all negative numbers in the frame, and the calculation formula of the short-time energy of the data in each frame is:
in the formula, E n For short-time energy, x (m) is intra-frame data, w (N) is a window function, and N is the number of data frame samples corresponding to the sampling frequency.
The calculation formula of the short-time zero-crossing number of the data in each frame is as follows:
in the formula, Z n For short time zero crossing, x (m) is intraframe data, sgn [ ·]As a function of the sign, i.e.
w (N) is a window function, and N is the number of data frame samples corresponding to the sampling frequency.
Acquiring a short-time energy threshold and a zero-crossing threshold of a pulse noise signal by using an audio database, and identifying the pulse noise signal in each audio band characteristic by using the short-time energy threshold and the zero-crossing threshold of the pulse noise signal and the short-time energy and the short-time zero-crossing of the obtained data in each frame;
specifically, when the short-time energy of the data in the frame is greater than or equal to a short-time energy threshold and the short-time zero-crossing number of the data in the frame is less than a zero-crossing number threshold, the data in the frame is determined to be a voice signal;
namely: when E is n Not less than STE threshold (short time energy threshold), and Z n If the value is less than ZCC threshold value (zero crossing threshold value), the data in the frame is judged to be a voice signal;
when the short-time energy of the data in the frame is smaller than a short-time energy threshold value and the short-time zero crossing number of the data in the frame is larger than a zero crossing number threshold value, judging that the data in the frame is a pulse noise signal;
namely: when E is n < STE threshold (short time energy threshold), and Z n And when the value is greater than the ZCC threshold value (zero crossing threshold value), the data in the frame is judged to be an impulse noise signal.
S103, judging whether the impulse noise signal is larger than a preset audio threshold value or not;
in specific implementation, it is determined whether the decibel of the impulse noise signal is greater than a preset audio threshold (in this embodiment, the preset audio threshold is 85 dB), and when the decibel of the impulse noise signal is greater than the preset audio threshold, it means that the impulse noise signal affects the hearing of the human ear, so that the impulse noise signal needs to be correspondingly suppressed;
when the decibel of the impulse noise signal is not greater than the preset audio threshold, it means that the impulse noise signal is within the range of sound pressure in the ear canal, and for the processing of the impulse noise signal, only the normal voice signal except the impulse noise signal needs to be enhanced.
It should be noted that, in some optional embodiments, when the earphone is worn, a certain noise reduction function is performed on external noise through an earplug of the earphone, and generally, the physical noise reduction can achieve a noise reduction effect of 15 to 20dB, so when the earphone has the physical noise reduction function, the preset audio threshold is 105dB.
S104, if the impulse noise signal is larger than a preset audio threshold, inhibiting an impulse sample amplitude in the impulse noise signal by using an amplitude limiting function, and performing dynamic range companding on the processed impulse noise signal to obtain a primary impulse noise signal;
in specific implementation, if the impulse noise signal is greater than a preset audio threshold, inhibiting an impulse sample amplitude in the impulse noise signal by using an amplitude limiting function, and performing dynamic range companding on the processed impulse noise signal to obtain a primary impulse noise signal;
specifically, an audio signal is input, a window function type and a window length are set, a signal with noise STFT is set, a time spectrogram is utilized, a first screening threshold value is set, a window with possible impulse noise is selected, a correlation detection coefficient is set, screening is carried out again, a noise time domain position is returned by a formula, the processed audio signal is output through signal restoration and reconstruction, wherein the restoration algorithm step comprises the steps of setting a threshold band-pass limiter, passing the signal with noise through a limiter, setting an improved median filtering parameter, reconstructing the threshold filtering signal and obtaining the reconstructed signal.
After the processed audio signal is obtained, the dynamic range of the audio signal is compressed or limited, and the relative change range between the maximum level and the minimum level of the signal is reduced, so that the effects of reducing distortion and reducing noise are achieved.
The embodiment provides a dynamic range expansion algorithm for dynamically adjusting a noise simulation critical point by combining a noise estimation algorithm based on recursive average and a dynamic range companding algorithm. By dynamically evaluating the noise level, the noise simulation threshold is adjusted in real time, and noise reduction processing is further performed on high noise generated instantly while sound pickup enhancement is performed, so that the problem that the noise is amplified while voice is amplified by a dynamic range companding algorithm is solved.
And S105, performing feedback elimination on the preliminary pulse noise signal to suppress the pulse noise signal in the audio signal to obtain a target signal.
In specific implementation, an action instruction for eliminating the pulse noise signal is fed back to the preliminary pulse noise signal, and locking feedback processing is performed on the ultra-large signal in the preliminary pulse noise signal, so that the pulse noise signal is suppressed or eliminated.
Specifically, the gain output is controlled on the circuit to limit the preliminary impulse noise signal within the sound signal. And (3) carrying out noise reduction treatment on high noise generated instantly, controlling gain output, automatically cutting off the voice enhancement circuit when a noise signal exceeds a set threshold value, blocking the connection between a receiver and a power amplifier circuit, and delaying the time until more than 200mS is reached after the impact noise is finished. Meanwhile, the signal of the transmitter is processed, and the amplitude limiting smooth suppression processing is carried out on the burst pulse signal, so that the large noise signal is prevented from being transmitted to a receiving end.
Referring to fig. 5, a test curve after the impulse noise suppression is shown, where L1 represents an audio signal curve of 0dB in a null field (equivalent to a 0dB reference value in a noise environment), L2 represents a noise reduction curve (i.e., an audio signal curve collected when the earphone is worn), L3 represents a pickup enhancement curve, and L4 represents an audio signal curve after the impulse noise suppression.
In summary, in the impulse noise suppression method in the above embodiment of the present invention, the audio signal of the environment is obtained in real time, the audio feature extraction is performed on the audio signal, the extracted audio feature is subjected to feature discrimination to identify the impulse noise signal in the audio signal, and the impulse noise signal is identified in a feature discrimination manner to facilitate suppression processing on the impulse noise signal; specifically, when the impulse noise signal is greater than the preset threshold, the amplitude limiting function is used for inhibiting the impulse sample amplitude in the impulse noise signal and performing dynamic range companding so as to improve the impulse noise reduction performance, and further, the impulse noise signal is subjected to feedback elimination so as to inhibit the impulse noise signal in the audio signal, so that the situation that sudden noise enters human ears and affects the comfort level is avoided.
Example two
Referring to fig. 6, a system for suppressing impulse noise according to a second embodiment of the present invention is shown, and the system includes:
the audio signal acquisition module 11 is configured to acquire an audio signal of a current environment in real time, and perform audio feature extraction on the audio signal to obtain a plurality of audio features of the audio signal;
further, the audio signal obtaining module 11 includes:
an audio parameter acquisition unit configured to acquire an audio parameter of the audio signal and extract a plurality of audio frame features in the audio signal based on a unit frame of the audio signal and the audio parameter;
and the characteristic processing unit is used for processing the audio frame characteristics sequentially through the mean value, the variance and the standard deviation so as to obtain the audio segment characteristics corresponding to the audio frame characteristics.
A feature discriminating module 12, configured to perform feature discrimination on each audio feature by using an audio database, so as to identify a pulse noise signal in the audio signal;
further, the feature discriminating module 12 includes:
the characteristic acquisition unit is used for acquiring the sampling frequency of the audio signal and data in each frame of each audio segment characteristic;
and the characteristic discrimination unit is used for calculating the short-time energy and the short-time zero-crossing number of the data in each frame according to the sampling frequency and identifying the pulse noise signals in the audio band characteristics according to the short-time energy and the short-time zero-crossing number of the data in each frame and the short-time energy threshold value and the zero-crossing number threshold value.
In some optional embodiments, the feature discriminating unit is further configured to:
when the short-time energy of the data in the frame is greater than or equal to a short-time energy threshold and the short-time zero crossing number of the data in the frame is less than a zero crossing number threshold, judging that the data in the frame is a voice signal;
and when the short-time energy of the data in the frame is smaller than the short-time energy threshold and the short-time zero crossing number of the data in the frame is larger than the zero crossing number threshold, judging that the data in the frame is an impulse noise signal.
A judging module 13, configured to judge whether the impulse noise signal is greater than a preset audio threshold;
the noise signal suppression module 14 is configured to suppress a pulse sample amplitude in the impulse noise signal by using a clipping function if the impulse noise signal is greater than a preset audio threshold, and perform dynamic range companding on the processed impulse noise signal to obtain a preliminary impulse noise signal;
and a feedback elimination module 15, configured to perform feedback elimination on the preliminary impulse noise signal, so as to suppress the impulse noise signal in the audio signal, and obtain a target signal.
The functions or operation steps of the modules and units when executed are substantially the same as those of the method embodiments, and are not described herein again.
The implementation principle and the generated technical effect of the impulse noise suppression system provided by the embodiment of the present invention are the same as those of the method embodiment described above, and for the sake of brief description, no mention is made in the embodiment of the apparatus, and reference may be made to the corresponding contents in the method embodiment described above.
EXAMPLE III
Referring to fig. 7, a computer device according to a third embodiment of the present invention is shown, which includes a memory 10, a processor 20, and a computer program 30 stored in the memory 10 and executable on the processor 20, wherein the processor 20 implements the impulse noise suppression method when executing the computer program 30.
The memory 10 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The memory 10 may in some embodiments be an internal storage unit of the computer device, for example a hard disk of the computer device. The memory 10 may also be an external storage device in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 10 may also include both an internal storage unit and an external storage device of the computer apparatus. The memory 10 may be used not only to store application software installed in the computer device and various kinds of data, but also to temporarily store data that has been output or will be output.
In some embodiments, the processor 20 may be an Electronic Control Unit (ECU), a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor or other data Processing chips, and is configured to run program codes stored in the memory 10 or process data, for example, execute an access restriction program.
It should be noted that the configuration shown in fig. 7 does not constitute a limitation of the computer device, and in other embodiments the computer device may include fewer or more components than shown, or some components may be combined, or a different arrangement of components.
An embodiment of the present invention further provides a readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the impulse noise suppression method as described above.
Those of skill in the art will understand that the logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be viewed as implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Further, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent application shall be subject to the appended claims.
Claims (10)
1. An impulse noise suppression method, comprising:
acquiring an audio signal of a current environment in real time, and performing audio feature extraction on the audio signal to obtain a plurality of audio features of the audio signal;
carrying out characteristic discrimination on each audio characteristic by using an audio database so as to identify impulse noise signals in the audio signals;
judging whether the impulse noise signal is larger than a preset audio threshold value or not;
if the impulse noise signal is larger than a preset audio threshold, inhibiting the impulse sample amplitude in the impulse noise signal by using an amplitude limiting function, and carrying out dynamic range companding on the processed impulse noise signal to obtain a primary impulse noise signal;
and carrying out feedback elimination on the preliminary pulse noise signal so as to inhibit the pulse noise signal in the audio signal and obtain a target signal.
2. The impulse noise suppression method according to claim 1, wherein said step of performing audio feature extraction on said audio signal to obtain a plurality of audio features of said audio signal comprises:
acquiring audio parameters of the audio signal, and extracting a plurality of audio frame features in the audio signal based on the unit frame of the audio signal and the audio parameters;
and processing each audio frame characteristic by mean value, variance and standard deviation in sequence to obtain the audio segment characteristic corresponding to each audio frame characteristic.
3. The impulse noise suppression method according to claim 2, wherein the step of performing feature discrimination on each of the audio features by using an audio database to identify the impulse noise signal in the audio signal comprises:
acquiring the sampling frequency of the audio signal and data in each frame of each audio segment characteristic;
and calculating the short-time energy and the short-time zero-crossing number of the data in each frame according to the sampling frequency, and identifying the pulse noise signals in the characteristics of each audio band according to the short-time energy and the short-time zero-crossing number of the data in each frame and the short-time energy threshold value and the zero-crossing number threshold value.
4. The method of claim 3, wherein the short-time energy of each of the intra-frame data is calculated by the formula:
in the formula, E n For short-time energy, x (m) is intra-frame data, w (N) is a window function, and N is the number of data frame samples corresponding to the sampling frequency.
5. The impulse noise suppression method according to claim 3, wherein the short-time zero-crossing number of each of said intra-frame data is calculated by the formula:
in the formula, Z n For short time zero crossing, x (m) is intraframe data, sgn [ ·]As a function of the sign, i.e.
w (N) is a window function, and N is the number of data frame samples corresponding to the sampling frequency.
6. The method of claim 3, wherein the step of identifying the impulse noise signal in each of the audio segment features based on the short-time energy and short-time zero crossings and the short-time energy threshold and zero crossings threshold of each of the intraframe data comprises:
when the short-time energy of the data in the frame is greater than or equal to a short-time energy threshold and the short-time zero crossing number of the data in the frame is less than a zero crossing number threshold, judging that the data in the frame is a voice signal;
and when the short-time energy of the data in the frame is smaller than the short-time energy threshold and the short-time zero crossing number of the data in the frame is larger than the zero crossing number threshold, judging that the data in the frame is an impulse noise signal.
7. An impulse noise suppression system, comprising:
the audio signal acquisition module is used for acquiring an audio signal of the current environment in real time and extracting audio features of the audio signal to obtain a plurality of audio features of the audio signal;
the characteristic distinguishing module is used for distinguishing the characteristics of the audio characteristics by utilizing an audio database so as to identify pulse noise signals in the audio signals;
the judging module is used for judging whether the pulse noise signal is larger than a preset audio threshold value or not;
the noise signal suppression module is used for suppressing the pulse sample amplitude in the pulse noise signal by using an amplitude limiting function and performing dynamic range companding on the processed pulse noise signal to obtain a primary pulse noise signal if the pulse noise signal is greater than a preset audio threshold;
and the feedback elimination module is used for carrying out feedback elimination on the preliminary pulse noise signal so as to inhibit the pulse noise signal in the audio signal and obtain a target signal.
8. An impulse noise suppression system according to claim 7, characterized in that said audio signal acquisition module comprises:
an audio parameter acquisition unit, configured to acquire an audio parameter of the audio signal, and extract a plurality of audio frame features in the audio signal based on a unit frame of the audio signal and the audio parameter;
and the characteristic processing unit is used for processing the audio frame characteristics sequentially through the mean value, the variance and the standard deviation so as to obtain the audio segment characteristics corresponding to the audio frame characteristics.
9. A readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the impulse noise suppression method as claimed in any one of claims 1 to 6.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the impulse noise suppression method as claimed in any one of claims 1 to 6 when executing the computer program.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116614742A (en) * | 2023-07-20 | 2023-08-18 | 江西红声技术有限公司 | Clear voice transmitting and receiving noise reduction earphone |
| CN116758934A (en) * | 2023-08-18 | 2023-09-15 | 深圳市微克科技有限公司 | Method, system and medium for realizing intercom function of intelligent wearable device |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116614742A (en) * | 2023-07-20 | 2023-08-18 | 江西红声技术有限公司 | Clear voice transmitting and receiving noise reduction earphone |
| CN116758934A (en) * | 2023-08-18 | 2023-09-15 | 深圳市微克科技有限公司 | Method, system and medium for realizing intercom function of intelligent wearable device |
| CN116758934B (en) * | 2023-08-18 | 2023-11-07 | 深圳市微克科技有限公司 | Method, system and medium for realizing intercom function of intelligent wearable device |
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