CN105244040B - A kind of audio signal consistency control methods - Google Patents
A kind of audio signal consistency control methods Download PDFInfo
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- CN105244040B CN105244040B CN201510429221.5A CN201510429221A CN105244040B CN 105244040 B CN105244040 B CN 105244040B CN 201510429221 A CN201510429221 A CN 201510429221A CN 105244040 B CN105244040 B CN 105244040B
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- 238000005070 sampling Methods 0.000 claims abstract description 63
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- 238000005314 correlation function Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
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Abstract
The invention discloses a kind of audio signal consistency control methods, it is the following steps are included: obtain sampled data, extension length, calculate fast correlation similitude, calculate similarity and offset, determine that two paths of data is consistent if similarity is greater than or equal to threshold value, judge whether sampled data has carried out approximate envelop processing if similarity is less than threshold value, determine that two paths of data is inconsistent if having carried out approximate envelop processing, repeats abovementioned steps after carrying out approximate envelop processing to sampled data if not carrying out approximate envelop processing.This programme can monitoring with the consistency of accurate judgement two-way audio signal, suitable for broadcasting station to broadcasting signal.
Description
Technical field
The present invention relates to audio data analysis process fields, more particularly, to a kind of audio signal consistency control methods.
Background technique
In the entire transmission in broadcasting station, monitoring link, detected both for the physical index of audio, than
Such as: whether breaking, level is relatively low or higher, reverse phase.But whether detection means is correctly lacked for the content of audio, such as
The signal that master control finally exports whether be studio's sound console output signal, air-launched signal whether be master control final stage output
Signal the problems such as currently without suitable detection means, accident only etc., which has occurred, can just detect.
State Intellectual Property Office of the People's Republic of China discloses Publication No. on December 01st, 2010
The patent document of CN101902677A, title are audio detection device and method, the device include: MIC circuit detection module and
Phonation circuit detection module;MIC circuit detection module, for obtaining the amplitude and frequency of the sine wave signal after MIC circuit sampling
Whether qualified rate with frequency determines MIC circuit according to amplitude, and exports sine wave signal;Phonation circuit detection module includes: tool
There are the change-over panel and processor of MIC circuit;Change-over panel is believed for sampling the analog signal of phonation circuit output, and by simulation
Number digital signal is converted to, is sent to processor;Processor is analyzed and processed for the amplitude to digital signal with frequency,
Judge whether phonation circuit is qualified.This scheme can not carry out the judgement of consistency to audio signal.
Summary of the invention
The present invention is mainly the skill for solving to carry out audio signal consistency present in the prior art accurate judgement
Art problem, providing one kind can be analyzed by the characteristic signal to audio, the whether consistent audio letter of detection two paths of signals content
Number consistency control methods, finds brodasting breakup convenient for broadcasting station in time.
What the present invention was mainly addressed by following technical proposals in view of the above technical problems: a kind of audio signal one
The control methods of cause property, comprising the following steps:
S01, N number of sampled data is obtained from first via audio signal as first via sampled data, from the second tunnel audio
N number of sampled data is obtained in signal as the second tunnel sampled data;
S02, benefit 0 length will be extended to as 2N behind first via sampled data, 0 extension will be mended behind the second tunnel sampled data
It is 2N to length;
S03, Fast Fourier Transform (FFT) is carried out to the first via sampled data after extension and then conjugation is asked to obtain the first number
According to, to after extension the second tunnel sampled data carry out Fast Fourier Transform (FFT) then ask conjugation to obtain the second circuit-switched data, ask first
The cross-correlation function of circuit-switched data and the second circuit-switched data is carrying out Fast Fourier Transform (FFT) to cross-correlation function, is obtaining similitude number
According to;
S04, the maximum value for choosing absolute value in similarity data, then calculate similarity value and maximum value offset;
If S05, similarity value are greater than or equal to consistency threshold value, then it is assumed that first via sampled data and the sampling of the second tunnel
Data are consistent, and comparison process terminates;If similarity is less than consistency threshold value, S06 is entered step;
S06, judge whether first via sampled data and the second tunnel sampled data have already passed through approximate envelop processing, if
No, then approximate envelop processing is carried out to first via sampled data and the second tunnel sampled data, then repeats step S02 extremely
S05;If having already passed through approximate envelop processing, determine that first via sampled data and the second tunnel sampled data are inconsistent.
The above process can relatively accurately judge the similarity of first via sampled signal and the second tunnel sampled signal.According to
After calculated offset deviates audio signal, the consistency of audio signal can be more precisely calculated.
Preferably, similarity value ratio calculation formula is as follows:
Ratio=fSamplemax*M/sum
In formula, fSamplemaxFor the maximum value of absolute value in similarity data, M is the number of similarity data, and sum is
The sum of the absolute value of all similarity datas.
Preferably, maximum value offset offset is determined according to following methods: fSamplemaxFor in similarity data
I-th of data, if i is less than or equal to M/2, offset=i;If i is greater than M/2, offset=i-M/2;
fSamplemaxFor the maximum value of absolute value in similarity data, M is the number of similarity data.
Preferably, approximate envelop is handled specifically: first via sampled data is divided into the window that length is 2 milliseconds
Mouthful, it is maximized to form first window maximum data * X1 from each window;It is 2 that second tunnel sampled data, which is divided into length,
The window of millisecond, is maximized to form the second window maximum data * Y1 from each window;Calculate the exhausted of first via sampled data
To the mean value meanX1 of value;Calculate the mean value meanY1 of the absolute value of the second tunnel sampled data;Each data in * X1 are subtracted
MeanX1, data obtained are as first via sampled data;Each data in * Y1 are subtracted into meanY1, number obtained
According to as the second tunnel sampled data.
And bottom smaller for volume is made an uproar apparent audio content, and the phase of step S02-S05 being calculated directly is carried out
It is smaller like spending, it will be generally less than consistency threshold value, small signal interference can be eliminated after carrying out approximate envelop processing at this time, mentioned
High differentiation rate.
Preferably, the value range of the consistency threshold value is 20-30.
By the way that accurate consistency threshold value can be oriented after a certain amount of sampling analysis.
Preferably, ought continuously determine that first via sampled data and the second tunnel sampled data are inconsistent three times, first is assert
Road audio signal and the second tunnel audio signal are inconsistent.
When there is first via audio signal and the inconsistent situation of the second tunnel audio signal, early warning can be carried out, is prompted
Staff is modified or safeguards.
This programme can be used for following occasion:
Radio station master control:
For judging the consistency of master control final stage output signal and sound console output signal;
The consistency of master control final stage signal and the empty collection of letters number;
Transmitting station:
The consistency of the sky collection of letters number and optical transmitter and receiver output signal;
Monitoring center:
User judges whether broadcasting signal is disturbed or invades;
Bring substantial effect of the present invention is can reliably to calculate the similarity and offset of two-way audio signal
Amount eliminates the influence of audio signal decaying, has high accuracy of judgement degree.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the invention.
Specific embodiment
Below with reference to the embodiments and with reference to the accompanying drawing the technical solutions of the present invention will be further described.
Embodiment: a kind of audio signal consistency control methods of the present embodiment, as shown in Figure 1, comprising the following steps:
The audio data of certain number of sampling points is recorded, extension length first is twice, is assigned a value of 0 for subsequent.
float fSample[N*2]
FSample [i]=0 N≤i≤N*2
Then sampled data is subjected to FFT transform, fft algorithm is described as follows:
According to the characteristics such as odd, even, empty, real of discrete fourier transform, the algorithm of Discrete Fourier Transform is improved and is obtained
Fast Fourier transformation algorithm FFT is obtained, if the sequence of complex numbers that x (n) is N, by DFT transform, the calculating of any X (m) requires n times
Complex multiplication and N-1 complex addition, and a complex multiplication is equal to four real multiplications and twice real addition, primary plural number
Addition is equal to real addition twice, even if a complex multiplication and a complex addition are defined as primary " operation " (four realities
Number multiplication and four real additions), then finding out the X (m) of N sequence of complex numbers, i.e. N point DFT transform about just needs N^2 fortune
It calculates.In FFT, one N sequence (setting N=2k, k is positive integer) is divided into two N/ using the periodicity and symmetry of WN
2 subsequences, each N/2 point DFT transform need (N/2) 2 operations, then with n times operation the DFT transform of two N/2 points
It is combined into the DFT transform of a N point.After converting in this way, total operation times reform into N+2* (N/2) ^2=N+ (N^2)/2,
Save about 50% operand.
1≤K≤N
1≤n≤N
By the two-way sampled data after FFT budget, conjugation is sought, then carries out a FFT operation, process is known as calculating quick phase
Close similitude.
Then the data of Fourier transform are maximized, maximum average value are calculated by number of samples, and pass through maximum value
Start bit calculate maximum value offset, can thus calculate the sampled point offset of similarity value and two-way audio, count
Calculation method are as follows:
Number of sampling points: N
Offset: offset
Similarity: ratio
Data after Fourier transform: fSample has positive and negative values because audio signal is sine wave, answers when so calculating
When use absolute value carries out size comparison.
Data volume summation: sum
Ratio < | fSample [i] |? ratio=| fSample [i] | offset=i
Sum=Sum+ | fSample [i] |
1≤i≤N
When similarity (ratio) value is greater than certain value range, (value is commonly defined as 20- after long-term test
30) after, so that it may which it is consistent to regard as two paths of signals, then further according to calculated offset (offset), carries out two paths of signals
Offset, migration algorithm are as follows:
FSample [i]=fSample [i+offset]
1≤i≤(N-offset)
It is subsequent to the data deviated calculate will similarity value more close to contrast range, improve accuracy.
It is smaller for volume, and bottom is made an uproar apparent audio content, it is smaller in the approximation that current algorithm obtains, generally
Scheduled range can be less than, it is obvious which fluctuates situation, and similarity value is generally in 10-15 or so, the situation, using taking sound
The mode of the approximate envelop of frequency route carries out secondary calculating, can eliminate small signal interference and improve differentiation rate.2 milliseconds are taken every time
The maximum value of window obtains the mean value of * X1, * Y1 and two paths of signals:
Sample rate is set as 48000, then 2 milliseconds of window sample number is 96
1≤i≤N;I+=96;j++
Sum=sum+ | fSample [i] |
1≤i≤N
Mean value in * X1, * Y1 signal is removed:
RX=*X1-meanX1
RY=*Y1-meanY1
Then to data rX, rY of secondary calculating again before the step of, calculate fast correlation similitude, to calculated
Data carry out the calculating of similarity and offset again, obtain new comparing result, further increase accuracy.Due to this assonance
The frequency that frequency occurs in the actual environment is not high, and calculating twice can promote CPU burden, therefore is lower as similarity value
When secondary authentication policy exist.
Determination strategy is added on the basis of fast correlation similitude, it is (general that continuous 2 decision thresholds are less than setting value
For 20-30), and think that two paths of signals is inconsistent when offset fluctuation range larger (sampling greater than 1s).
After fast correlation Similarity measures, the similarity and offset of two-way audio can be reliably calculated,
Again by a certain amount of sampling analysis after, so that it may orient accurate decision threshold, can be effective right according to this threshold values
The consistency of two paths of signals detected, early warning, and due to having carried out FFT operation twice, taking similarity is the signal carried out
The calculating of curve, the decaying of audio signal have no effect on calculated result, and accuracy of judgement degree can achieve 99.99% or more.
Specific embodiment described herein is only an example for the spirit of the invention.The neck of technology belonging to the present invention
The technical staff in domain can make various modifications or additions to the described embodiments or replace by a similar method
In generation, however, it does not deviate from the spirit of the invention or beyond the scope of the appended claims.
Although the terms such as sampled data, Fast Fourier Transform (FFT) are used more herein, it is not precluded using other
A possibility that term.The use of these items is only for be more convenient to describe and explain essence of the invention;They are explained
It at any additional limitation is disagreed with spirit of that invention.
Claims (6)
1. a kind of audio signal consistency control methods, which comprises the following steps:
S01, N number of sampled data is obtained from first via audio signal as first via sampled data, from the second tunnel audio signal
It is middle to obtain N number of sampled data as the second tunnel sampled data;
S02, benefit 0 length will be extended to as 2N behind first via sampled data, extend to length for mending 0 behind the second tunnel sampled data
Degree is 2N;
S03, Fast Fourier Transform (FFT) is carried out to the first via sampled data after extension and then conjugation is asked to obtain the first circuit-switched data, it is right
The second tunnel sampled data after extension carries out Fast Fourier Transform (FFT) and then conjugation is asked to obtain the second circuit-switched data, seeks the first circuit-switched data
With the cross-correlation function of the second circuit-switched data, Fast Fourier Transform (FFT) is being carried out to cross-correlation function, is obtaining similarity data;
S04, the maximum value for choosing absolute value in similarity data, then calculate similarity value and maximum value offset;
If S05, similarity value are greater than or equal to consistency threshold value, then it is assumed that first via sampled data and the second tunnel sampled data
Unanimously, comparison process terminates;If similarity is less than consistency threshold value, S06 is entered step;
S06, judge whether first via sampled data and the second tunnel sampled data have already passed through approximate envelop processing, if do not had
Have, then approximate envelop processing is carried out to first via sampled data and the second tunnel sampled data, then repeat step S02 to S05;
If having already passed through approximate envelop processing, determine that first via sampled data and the second tunnel sampled data are inconsistent.
2. a kind of audio signal consistency control methods according to claim 1, which is characterized in that similarity value ratio
Calculation formula is as follows:
Ratio=fSamplemax*M/sum
In formula, fSamplemaxFor the maximum value of absolute value in similarity data, M is the number of similarity data, and sum is all
The sum of the absolute value of similarity data.
3. a kind of audio signal consistency control methods according to claim 1, which is characterized in that maximum value offset
Offset is determined according to following methods: fSamplemaxFor i-th of data in similarity data, if i is less than or equal to M/2,
Then offset=i;If i is greater than M/2, offset=i-M/2;fSamplemaxFor the maximum of absolute value in similarity data
Value, M are the number of similarity data.
4. a kind of audio signal consistency control methods according to claim 2 or 3, which is characterized in that approximate envelop
Processing specifically: it is 2 milliseconds of window that first via sampled data, which is divided into length, is maximized to form the from each window
One window maximum data * X1;Second tunnel sampled data is divided into the window that length is 2 milliseconds, takes maximum from each window
Value forms the second window maximum data * Y1;Calculate the mean value meanX1 of the absolute value of first via sampled data;The second tunnel is calculated to adopt
The mean value meanY1 of the absolute value of sample data;Each data in * X1 are subtracted into meanX1, data obtained are as the first via
Sampled data;Each data in * Y1 are subtracted into meanY1, data obtained are as the second tunnel sampled data.
5. a kind of audio signal consistency control methods according to claim 1, which is characterized in that the consistency threshold value
Value range be 20-30.
6. a kind of audio signal consistency control methods according to claim 1, which is characterized in that when continuously determining three times
First via sampled data and the second tunnel sampled data are inconsistent, assert that first via audio signal and the second tunnel audio signal are different
It causes.
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CN102142257A (en) * | 2010-12-28 | 2011-08-03 | 北大方正集团有限公司 | Audio signal processing method and device |
CN103426439A (en) * | 2013-05-08 | 2013-12-04 | 杭州联汇数字科技有限公司 | Method for detecting consistency of broadcast television audio signal content |
CN104468697A (en) * | 2014-10-10 | 2015-03-25 | 浙江广播电视集团 | Radio station data transmission load distribution method |
CN104505101A (en) * | 2014-12-24 | 2015-04-08 | 北京巴越赤石科技有限公司 | Real-time audio comparison method |
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Publication number | Priority date | Publication date | Assignee | Title |
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US3919479A (en) * | 1972-09-21 | 1975-11-11 | First National Bank Of Boston | Broadcast signal identification system |
CN102142257A (en) * | 2010-12-28 | 2011-08-03 | 北大方正集团有限公司 | Audio signal processing method and device |
CN103426439A (en) * | 2013-05-08 | 2013-12-04 | 杭州联汇数字科技有限公司 | Method for detecting consistency of broadcast television audio signal content |
CN104468697A (en) * | 2014-10-10 | 2015-03-25 | 浙江广播电视集团 | Radio station data transmission load distribution method |
CN104505101A (en) * | 2014-12-24 | 2015-04-08 | 北京巴越赤石科技有限公司 | Real-time audio comparison method |
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