CN116469409A - Binaural channel signal detection and adjustment method - Google Patents
Binaural channel signal detection and adjustment method Download PDFInfo
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- CN116469409A CN116469409A CN202310257209.5A CN202310257209A CN116469409A CN 116469409 A CN116469409 A CN 116469409A CN 202310257209 A CN202310257209 A CN 202310257209A CN 116469409 A CN116469409 A CN 116469409A
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
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Abstract
The invention relates to the field of channel signal detection, in particular to a binaural channel signal detection and adjustment method, which comprises a binaural difference detection module and a binaural equalization adjustment module, wherein the difference between ears is detected through a main observation listener, and then HRTF data of the ears are calibrated to form a personalized HRTF model aiming at a specific earphone and a specific listener user, so that the listener can more accurately feel the position of a virtual sound image, and the auditory spatial sensation is enhanced.
Description
Technical Field
The invention relates to the technical field of channel signal detection, in particular to a binaural channel signal detection and adjustment method.
Background
The head related transfer function (Head Related Transfer Function, HRTF) is a fundamental model for studying the perception of spatial sound sources by the human ear, typically by measurement in anechoic chambers. HRTF can be expressed as a time domain impulse response function related to the spatial direction and the left and right ears reflecting the two cues that are most important for human ears to perceive the direction of the sound source, binaural time differences and binaural intensity differences, i.e. sound sources in different directions will form different time differences and intensity differences in the left and right ears.
The HRTF model is mainly applied to the virtual space hearing technology. By performing signal processing based on an HRTF model, generally time domain convolution, on a certain sound source signal, binaural signals from any virtual direction can be generated, and playback is performed by using headphones, so that a listener can feel a realistic spatial hearing effect. A precondition for this effect is that the listener's binaural hearing level and the output frequency response of the headphones are identical.
However, this premise is not fully realized in practice, and the binaural hearing condition of the first person often varies, and the hearing levels in the respective frequency bands are not necessarily completely uniform. In addition, headphones often have differences in output frequency response, which is affected by the manufacturing process flow. The inconsistency of these two aspects can seriously affect the hearing experience of the virtual sound image, resulting in deviation of the direction of the sound image perceived by the listener from a preset direction.
For this purpose, a binaural channel signal detection adjustment method is proposed.
Disclosure of Invention
The present invention is directed to a binaural signal detection and adjustment method, which solves the problems set forth in the background art, and the basic detection process is to transmit binaural signals to a specific binaural earphone as audiometric signals by using a control device, such as a personal computer or a mobile phone. The two channels are identical and synchronized narrowband noise, with the aim of forming a virtual sound image directly in front of the listener. When the earphone returns the sound signal, the listener judges whether the sound source comes from the right front, and adjusts the direction of the sound image by the control device until the sound image is located right front.
In order to achieve the above purpose, the present invention provides the following technical solutions: a binaural channel signal detection adjustment method, comprising: the system comprises a binaural difference detection module and a binaural balance adjustment module;
the binaural difference detection module comprises a narrowband noise generation unit, a play control unit and a test recording unit, and transmits binaural signals to specific binaural headphones as audiometric signals by using control equipment such as a personal computer or a mobile phone. The two channels are identical and synchronized narrowband noise, with the aim of forming a virtual sound image directly in front of the listener. When the earphone returns the sound signal, the listener judges whether the sound source comes from the right front and adjusts the direction of the sound image through the control device until the sound image is positioned in the right front;
the binaural equalization adjustment module comprises a data processing unit and an equalization adjustment unit, and performs equalization adjustment on the HRTF model, wherein the basic principle is that the HRTF data is subjected to Fourier transformation to obtain a frequency spectrum coefficient, then the frequency spectrum coefficient is adjusted, and then the time domain HRTF data is recovered by inverse Fourier transformation.
Preferably: the narrowband noise generating unit includes generating narrowband noise having a center frequency of 500Hz and a length of 10 s. The noise may be generated by filtering a length of 10s of white gaussian noise with a gammatine filter having a center frequency of 500 Hz. The gamma digital filter g (n) can be expressed as follows:
g(n)＝n D-1 e -2πbn·Δt cos(2πf c n·Δt+Φ)n＝0，1，2，...，K-1
d is the order of the filter, and is generally 3 or 4; b reflects the filter bandwidth; t is the reciprocal of the sampling rate Fs, which here is set to 44100Hz; fc is the filter center frequency, here set to 500; the initial phase of the filter is generally set to 0; n is the filter length, and k=3fs when the filter duration is 3 s.
Preferably: the play control unit plays the generated narrow-band noise to a listener through the play control device and the double ear earphone, and the listener judges the sound source direction and carries out left and right ear balance adjustment.
Preferably: in the equalizing adjustment process, the playing control unit increases or decreases the amplitude of the channel signal by 1dB every time, and repeats the process until the listener feels that the sound source is positioned right in front, records the amplitude gain of the left channel signal at the moment, and records the amplitude gain as g 500 The unit is dB, letI.e. the linear gain coefficient, as a test result for the 500Hz frequency point.
Preferably: the test recording unit is used for measuring the central frequencies of 500Hz,1000Hz,2000Hz,4000Hz and 8000Hz respectivelyTesting 16000Hz signal, and recording test result of each frequency point, which is recorded as g 1000 ，g 2000 ，g 3000 ，g 4000 ，g 8000 ，g 16000 。
Preferably: the data processing unit performs discrete Fourier transform on HRTF data transmitted from the angle theta to the left ear, and the transformation formula is as follows:
in the aboveFor the HRTF data transmitted to the left ear at the angle theta, the length is N, and the complex-form frequency spectrum coefficient is obtained through the Fourier transform DFT (& gt)>Since the HRTF data is a real sequence, +.>The first half and the second half of the sequence are conjugate symmetrical, so that only the pair +.>Processing the first half of the sequence.
Preferably: the equalization adjusting unit uses the pair of equalization gain coefficients G (i)Performing equalization adjustment, and equalizing the result
Is marked asThe adjustment formula is as follows:
in the aboveAnd N/2 coefficients in G (i) each correspond to N/2 frequency points f distributed evenly over the frequency domain i Its specific frequency value and sampling rate F of HRTF data s In relation, as can be calculated from the following formula,
。
preferably: the equalizing gain coefficient G (i) can be obtained by testing the first part of the binaural difference detection
Interpolation is carried out, and the interpolation method is as follows:
can be obtained by conjugate symmetry of the first half sequence:
the above formula represents complex conjugate operation.
Preferably: the HRTF dataGenerating equalized time domain HRTF data by inverse Fourier transform
In the above-mentioned method, the step of,and (3) obtaining an IDFT (inverse Fourier transform) result, namely the HRTF data subjected to personalized equalization.
Compared with the prior art, the invention has the beneficial effects that:
the difference between the ears is detected through the main observation hearing, and then the HRTF data of the ears are calibrated, so that a personalized HRTF model aiming at a specific earphone and a specific listener user is formed, the listener can more accurately feel the virtual sound image position, and the hearing space sense is enhanced.
Drawings
FIG. 1 is a system diagram of the present invention;
Detailed Description
The following are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1:
as shown in fig. 1, the binaural difference detection module, a basic flow of detection, is to transmit a binaural signal to a specific binaural earphone as an audiometric signal by using a control device, such as a personal computer or a mobile phone. The two channels are identical and synchronized narrowband noise, with the aim of forming a virtual sound image directly in front of the listener. When the earphone returns the sound signal, the listener judges whether the sound source comes from the right front and adjusts the direction of the sound image through the control device until the sound image is positioned in the right front;
in the first step, narrowband noise with a center frequency of 500Hz and a length of 10s is generated. The noise may be generated by filtering a length of 10s of white gaussian noise with a gammatine filter having a center frequency of 500 Hz. The gamma digital filter g (n) can be expressed as follows:
g(n)＝n D-1 e- 2πbn·Δt cos(2πf c n·Δt+Φ)n＝0，1，2，...，K-1
d is the order of the filter, and is generally 3 or 4; b reflects the filter bandwidth; t is the reciprocal of the sampling rate Fs, which here is set to 44100Hz; fc is the filter center frequency, here set to 500; the initial phase of the filter is generally set to 0; n is the filter length, and k=3fs when the filter duration is 3 s.
And secondly, playing the generated narrow-band noise to a listener through a playing control device (such as a personal computer or a mobile phone) and the double ear earphone, and judging the sound source direction by the listener and carrying out left and right ear balance adjustment. The headphones are synchronized to play the narrowband signal generated in the first step, and if the listener experiences a direction that is not directly in front, the listener is adjusted through a user interface on the control device. For example, the listener perceives the sound image to be left, and "left adjustment" may be selected. The control device increases the left channel signal amplitude by 1dB for each selection. If the listener selects "right adjustment", the left channel signal amplitude is reduced by 1dB. Repeating the steps until the listener perceives that the sound source is positioned in front of the front, recording the amplitude gain of the left channel signal, and recording as g 500 The unit is dB, letI.e. the linear gain coefficient, as a test result for the 500Hz frequency point.
Third, testing 1000Hz,2000Hz,4000Hz,8000Hz and 16000Hz signals by the same method, and recording the test result of each frequency point, which is recorded as g 1000 ，g 2000 ，g 3000 ，g 4000 ，g 8000 .g 16000 ；
An HRTF data model is generated.
Example 2:
the basic principle of the binaural equalization adjustment module is to perform equalization adjustment on the HRTF model according to the detection result in embodiment 1, fourier transform is performed on HRTF data to obtain spectral coefficients, and the spectral coefficients are adjusted according to the test result in embodiment 1 and then restored to time domain HRTF data by inverse fourier transform. In the specific process, only the HRTF data of each angle of the left ear is subjected to balanced adjustment.
First, discrete Fourier transform is performed on HRTF data transmitted from an angle θ to the left ear
In the aboveFor the HRTF data transmitted to the left ear at the angle theta, the length is N, and the complex-form frequency spectrum coefficient is obtained through the Fourier transform DFT (& gt)>Since the HRTF data is a real sequence, +.>The first half and the second half of the sequence are conjugate symmetrical, so that only the pair +.>Processing the first half of the sequence.
Second, the equalization gain factor G (i) is used for the pairEqualizing, and marking the result after equalizing as +.>
In the aboveAnd N/2 coefficients in G (i) each correspond to N/2 frequency points f distributed evenly over the frequency domain i Its specific frequency value and sampling rate F of HRTF data s In relation, as can be calculated from the following formula,
g (i) may be obtained by interpolating the test result obtained by the above-described first partial binaural difference detection, by the following method,
can be obtained by conjugate symmetry of the first half sequence:
the above formula represents complex conjugate operation.
Third step, the generatedGenerating equalized time domain HRTF data by inverse Fourier transform
In the above-mentioned method, the step of,the HRTF data after personalized equalization is the result of inverse fourier transform IDFT ().
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A binaural channel signal detection adjustment method, characterized in that: the system comprises a binaural difference detection module and a binaural balance adjustment module;
the binaural difference detection module comprises a narrowband noise generation unit, a play control unit and a test recording unit, and transmits binaural signals to specific binaural headphones as audiometric signals by using control equipment such as a personal computer or a mobile phone. The two channels are identical and synchronized narrowband noise, with the aim of forming a virtual sound image directly in front of the listener. When the earphone returns the sound signal, the listener judges whether the sound source comes from the right front and adjusts the direction of the sound image through the control device until the sound image is positioned in the right front;
the binaural equalization adjustment module comprises a data processing unit and an equalization adjustment unit, and performs equalization adjustment on the HRTF model, wherein the basic principle is that the HRTF data is subjected to Fourier transformation to obtain a frequency spectrum coefficient, then the frequency spectrum coefficient is adjusted, and then the time domain HRTF data is recovered by inverse Fourier transformation.
2. The binaural channel signal detection adjustment method according to claim 1, characterized in that: the narrowband noise generating unit includes generating narrowband noise having a center frequency of 500Hz and a length of 10 s. The noise may be generated by filtering a length of 10s of white gaussian noise with a gammatine filter having a center frequency of 500 Hz. The gamma digital filter g (n) can be expressed as follows:
g(n)＝n D-1 e -2πbn·Δt cos(2πf c n·Δt+Φ) n＝0，1，2，...，K-1
d is the order of the filter, and is generally 3 or 4; b reflects the filter bandwidth; t is the reciprocal of the sampling rate Fs, which here is set to 44100Hz; fc is the filter center frequency, here set to 500; the initial phase of the filter is generally set to 0; n is the filter length, and k=3fs when the filter duration is 3 s.
3. The binaural channel signal detection adjustment method according to claim 2, characterized in that: the play control unit plays the generated narrow-band noise to a listener through the play control device and the double ear earphone, and the listener judges the sound source direction and carries out left and right ear balance adjustment.
4. A binaural channel signal detection adjustment method according to claim 3, characterized in that: in the equalizing adjustment process, the playing control unit increases or decreases the amplitude of the channel signal by 1dB every time, and repeats the process until the listener feels that the sound source is positioned right in front, records the amplitude gain of the left channel signal at the moment, and records the amplitude gain as g 500 The unit is dB, letI.e. the linear gain coefficient, as a test result for the 500Hz frequency point.
5. The binaural channel signal detection adjustment method according to claim 1, characterized in that: the test recording unit tests signals with center frequencies of 500Hz,1000Hz,2000Hz,4000Hz,8000Hz and 16000Hz respectively, records the test result of each frequency point and records the test result as g 1000 ，g 2000 ，g 3000 ，g 4000 ，g 8000 ，g 16000 And the test corresponding to the 6 groups of frequencies respectively.
6. The binaural channel signal detection adjustment method according to claim 1, characterized in that: the data processing unit performs discrete Fourier transform on HRTF data transmitted from the angle theta to the left ear, and the transformation formula is as follows:
in the aboveHRTF data for θ -angle transfer to left earThe length is N, and the complex-form frequency spectrum coefficient is obtained through the Fourier transform DFT (& gt)>Since the HRTF data is a real sequence, +.>The first half and the second half of the sequence are conjugate symmetrical, so that only the pair +.>Processing the first half of the sequence.
7. The binaural channel signal detection adjustment method according to claim 1, characterized in that: the equalization adjusting unit uses the pair of equalization gain coefficients G (i)Equalizing, and marking the result after equalizing as +.>The adjustment formula is as follows:
in the aboveAnd N/2 coefficients in a (i) each correspond to N/2 frequency points f distributed evenly over the frequency domain i Its specific frequency value and sampling rate F of HRTF data s In relation, as can be calculated from the following formula,
8. the binaural channel signal detection adjustment method according to claim 7, characterized in that: the equalizing gain coefficient G (i) may be obtained by interpolating a test result obtained by the first part of binaural difference detection, where an interpolation method is as follows:
can be obtained by conjugate symmetry of the first half sequence:
the above formula represents complex conjugate operation.
9. The binaural channel signal detection adjustment method according to claim 7, characterized in that: the HRTF dataGenerating equalized time domain HRTF data by inverse Fourier transform
In the above-mentioned method, the step of,and (3) obtaining an IDFT (inverse Fourier transform) result, namely the HRTF data subjected to personalized equalization.
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