CN107527625A - Dolphin whistle signal aural signature extracting method based on analog cochlea in bionical auditory system - Google Patents
Dolphin whistle signal aural signature extracting method based on analog cochlea in bionical auditory system Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 24
- 241001481833 Coryphaena hippurus Species 0.000 title claims abstract description 19
- 210000003477 cochlea Anatomy 0.000 title claims abstract description 8
- 238000001228 spectrum Methods 0.000 claims abstract description 18
- 210000000067 inner hair cell Anatomy 0.000 claims abstract description 14
- 230000004044 response Effects 0.000 claims abstract description 14
- 238000000605 extraction Methods 0.000 claims abstract description 10
- 239000013598 vector Substances 0.000 claims abstract description 10
- 239000002858 neurotransmitter agent Substances 0.000 claims description 52
- 210000002768 hair cell Anatomy 0.000 claims description 22
- 210000004027 cell Anatomy 0.000 claims description 20
- 230000035699 permeability Effects 0.000 claims description 13
- 210000003027 ear inner Anatomy 0.000 claims description 11
- 210000000170 cell membrane Anatomy 0.000 claims description 10
- 230000005284 excitation Effects 0.000 claims description 6
- 239000000835 fiber Substances 0.000 claims description 6
- 230000006870 function Effects 0.000 claims description 6
- 230000008929 regeneration Effects 0.000 claims description 6
- 238000011069 regeneration method Methods 0.000 claims description 6
- 210000005036 nerve Anatomy 0.000 claims description 4
- 238000004088 simulation Methods 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000013016 damping Methods 0.000 claims description 3
- 230000007830 nerve conduction Effects 0.000 claims description 3
- 230000001172 regenerating effect Effects 0.000 claims description 3
- 230000002269 spontaneous effect Effects 0.000 claims description 3
- 210000001723 extracellular space Anatomy 0.000 claims description 2
- 230000000694 effects Effects 0.000 abstract description 4
- 238000012545 processing Methods 0.000 abstract description 3
- 230000009022 nonlinear effect Effects 0.000 abstract 1
- 230000007246 mechanism Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 244000287680 Garcinia dulcis Species 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 210000000721 basilar membrane Anatomy 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000009412 basement excavation Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 210000000860 cochlear nerve Anatomy 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000036039 immunity Effects 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 230000035800 maturation Effects 0.000 description 1
- 210000004379 membrane Anatomy 0.000 description 1
- 239000012528 membrane Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000026683 transduction Effects 0.000 description 1
- 238000010361 transduction Methods 0.000 description 1
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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
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
- G10L25/18—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
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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
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
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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
- 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
- G10L25/30—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique using neural networks
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- Physics & Mathematics (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Human Computer Interaction (AREA)
- Acoustics & Sound (AREA)
- Multimedia (AREA)
- Spectroscopy & Molecular Physics (AREA)
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- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
It is an object of the invention to provide the dolphin whistle signal aural signature extracting method based on analog cochlea in bionical auditory system, using following steps：(1) pretreatment signal is normalized；(2) signal that step 1 obtains is obtained into M subband signal by Gammatone auditory filter groups；(3) Fast Fourier Transform (FFT) is done to step 2 subband signal, by low pass filter, and generates hearing spectrum forms；(4) step 3 subband signal to subband hearing spectrum forms self-adaptive processing, is obtained into enhanced hearing spectrum forms, (5) calculate each subband sense of hearing spectrum energy of hearing spectrum forms, obtain M dimensional feature vectors by Meddis inner hair cell models.The present invention can solve in the prior art, and operand is big, can not rapid extraction feature；To nonlinear properties, nonstationary random response effect is undesirable；To the high dependence of ambient noise, the problem of application limitation.
Description
Technical field
The present invention relates to a kind of signal mode recognition methods, specifically aquatic organism signal mode identification side
Method.
Background technology
System for Underwater Acoustic Signals Recognition mainly includes feature extraction and classifier design two parts.The task of feature extraction is selection table
Effective and reliable and stable feature of target identities is levied, is one of key component of signal identification, it directly affects underwater sound letter
Number identification final result.Underwater world's sighting distance of dolphin life is limited, and by Long Term Evolution, dolphin has been evolved excellent sonar
System.By Sonar system, dolphin can complete individual identification in population, predation, hide the behaviors such as natural enemy.In dolphin sonar
In, the whistle signal of dolphin carries the task of individual exchange communication, and the Classification and Identification of whistle signal also turns into dolphin research
One of key link.
At present, it is based primarily upon time-frequency domain for the feature extracting method of dolphin whistle signal.Waveform configuration including time domain
Feature extracting method, the Power estimation method and time-frequency domain of frequency domain utilize various signal converter techniques extraction signal characteristic.Traditional
Feature extracting method achieves good effect by excavation for a long time.Time domain waveform to be mainly characterized by method simple,
Real-time is good.But underwater signal time domain waveform is complicated, it is difficult to waveform configuration feature of the extraction with high score category information.Frequency domain
The characteristics of analyzing feature is technology maturation, and method is simple, and spectrum information contains clear and definite physical concept, but is adapted to processing line
Property, stationary signal.The feature of Time-Frequency Analysis Method extraction can more reflect the time domain and frequency domain character of signal, but time frequency analysis is more
Complexity, amount of calculation, amount of storage are big, and calculating speed is slow, poor real.Under the Underwater Acoustic Environment of reality, by different hydrological conditions
Influence, the extraction of traditional time-frequency characteristics tends not to obtain preferable effect.
The content of the invention
It is an object of the invention to provide can solve the problem that operand is big in the prior art, can not rapid extraction feature, to non-
Linear signal, nonstationary random response effect are undesirable, to the high dependence of ambient noise, the problems such as application limitation based on
The dolphin whistle signal aural signature extracting method of analog cochlea in bionical auditory system.
The object of the present invention is achieved like this：
Dolphin whistle signal aural signature extracting method of the invention based on analog cochlea in bionical auditory system, its feature
It is：
(1) dolphin cry is sampled, obtains faithful record signal s (n), faithful record signal s (n) is normalized pre- place
Reason：
(2) signal that step (1) obtains is obtained into M subband signal, M is filter by Gammatone auditory filter groups
Ripple device number, quick FFT is carried out to each subband signal；
The impulse response of Gammatone wave filters is：
In formula：A represents the amplitude factor of gammatone wave filters, and n represents the exponent number of gammatone wave filters, fcRepresent
The centre frequency of gammatone wave filters,Represent the initial phase of gammatone wave filters, 2 π bERB (fc) represent damping because
Son, u (t) represent unit-step function；
ERB represents equivalent rectangular bandwidth, and its expression formula is：ERB(fc)=24.7+0.108fc；
It is as follows that Laplace transform is done to gammatone filter impulse responses functions：
Wherein, A is filter gain, and n is filter order, fcCentered on frequency,For phase, b=2 π ERB (fc),w
=2 π fc；
(3) Fast Fourier Transform (FFT) is done to step (2) subband signal, by low pass filter, and generates hearing spectrum forms；
(4) halfwave rectifier, generation simulation people are carried out by Meddis inner hair cells model to step (2) filtered signal
The hearing spectrum forms that ear perceives, calculate each channel band energy of hearing spectrum forms, form the characteristic vector containing aural signature；
(5) each channel band energy of each hearing spectrum forms is calculated, forms the characteristic vector containing aural signature：
The present invention can also include：
1st, Meddis models include five physical quantitys：The amount of neurotransmitter, capillary in cell membrane permeability, inner ear hair cells
The amount of intercellular space neurotransmitter, regenerate the amount of neurotransmitter, excitation probability in storehouse：
(1) cell membrane permeability：
Reflection neurotransmitter describes in the following way from inner hair cell to the permeability of hair cell gap transmission ability：
K (t) is cell membrane permeability, and stim (t) is the instantaneous amplitude for inputting sound wave, A, B, and g is cell parameters, k (t)=
A/ (A+B) g represents the spontaneous response of cell membrane；
(2) in inner ear hair cells neurotransmitter amount：
The amount q (t) of neurotransmitter changes over time rate and can be represented by the formula in inner ear hair cells：
Wherein, y (1-q (t))) it is the amount that manufactory adds to hair cell neurotransmitter, xw (t) is flowed back to by regenerating storehouse
The amount of hair cell neurotransmitter ,-k (t) q (t) flow to the amount of space between cells neurotransmitter out of hair cell；
(3) amount of outside neurotransmitter：
The amount c (t) of outside neurotransmitter changes over time to be described with following formula：
Wherein, k (t) q (t) are the neurotransmitters that inner hair cell flows into space between cells, and-lc (t) is that space between cells is flowed out
Neurotransmitter ,-rc (t) are the neurotransmitters flowed out to from space between cells in regeneration storehouse；
(4) amount of neurotransmitter in storehouse is regenerated：
Amount w (t) rates of changing with time of neurotransmitter are expressed from the next in regeneration storehouse：
(5) nerve fibre excitation probability：
The amount c (t) for eventually settling at the neurotransmitter in space between cells determines the probability that rear class nerve conduction fiber excites,
Represent as follows with scale factor h：
P (t)=hc (t) dt.
Advantage of the invention is that：The present invention is directed to traditional characteristic extracting method, computationally intensive, realization complexity, Yi Shouhuan
The problem of border influence of noise, it is proposed that a kind of dolphin whistle signal aural signature based on analog cochlea in bionical auditory system carries
Method is taken, and the process of establishing of whole model is described in detail, including the frequency dividing filter of the basilar membrane based on human hearing characteristic
The conversion of inner hair cell signal, the process of auditory nerve granting rate calculating characteristic vector on ripple, basilar memebrane.Gammatone filters utensil
There is sharp frequency selective characteristic, the decay at the edge of wave filter is very slow, and the energy effectively avoided between nearby frequency bands is let out
Leakage, can quickly handle voice signal, and its Frequency Response is consistent with the filtering characteristic of people's basilar membrane, while the wave filter is only
Less parameter is needed just can preferably to simulate human auditory system, it is easy to accomplish.Meddis modeling inner hair cell treatment mechanisms
Self-adaptive processing is carried out to input signal, the correct recognition rata of acoustic signature is improved, there is certain inhibitory action to noise.By right
The simulation of human ear basilar memebrane frequency selection mechanism and inner ear hair cells transduction mechanism it is this based on Gammatone wave filter groups and
The feature extracting method amount of calculation of Meddis models, realize that difficulty is less than conventional method, while this be based on bionical auditory model
Feature extracting method there is good noise immunity and robustness.
Brief description of the drawings
Fig. 1 is the impulse response waveform of Gammatone wave filters；
Fig. 2 is the amplitude-frequency response of Gammatone wave filters；
Fig. 3 is inner hair cell illustraton of model；
Fig. 4 is the flow chart of the inventive method.
Embodiment
Illustrate below in conjunction with the accompanying drawings and the present invention is described in more detail：
With reference to Fig. 1-4, dolphin cry obtains through 128kHz sample rates.
For faithful record signal：
Step 1：Pretreatment is normalized to marine faithful record signal s (n)；
Step 2：By the signal that step 1 obtains by Gammatone auditory filter groups, obtaining M subband signal, (M is
Number of filter), quick FFT is carried out to each subband signal.The impulse response of Gammatone wave filters is：
In formula：A represents the amplitude factor of gammatone wave filters；N represents the exponent number of gammatone wave filters；fcRepresent
The centre frequency of gammatone wave filters；Represent the initial phase of gammatone wave filters；2πbERB(fc) represent damping because
Son；U (t) represents unit-step function；
ERB represents equivalent rectangular bandwidth, and its expression formula is：ERB(fc)=24.7+0.108fc；
It is as follows that Laplace transform is done to gammatone filter impulse responses functions：
Wherein, A is filter gain, and n is filter order, fcCentered on frequency,For phase, b=2 π ERB (fc),w
=2 π fc。
Step 3：Fast Fourier Transform (FFT) is done to step 2 subband signal, by low pass filter, and generates hearing spectrum forms.
Step 4：Halfwave rectifier, generation simulation are carried out by Meddis inner hair cells model to the filtered signal of step 2
The hearing spectrum forms of auditory perceptual, each channel band energy of hearing spectrum forms is calculated, forms the characteristic vector containing aural signature.
Meddis inner hair cell models are as shown in Figure 3.
Meddis models mainly include five physical quantitys：The amount of neurotransmitter, capillary intercellular in permeability, inner ear hair cells
The amount of gap neurotransmitter, regenerate the amount of neurotransmitter, excitation probability in storehouse.
(1) cell membrane permeability
Permeability reflects neurotransmitter from inner hair cell to the ability of hair cell gap transmission.Permeability is available as follows
Mode describes：
K (t) is cell permeability of the membrane, and stim (t) is the instantaneous amplitude for inputting sound wave, and A, B, g is cell parameters.k(t)
=A/ (A+B) g represents the spontaneous response of cell membrane, describes a non-linear process.
(2) in inner ear hair cells neurotransmitter amount
The amount q (t) of neurotransmitter changes over time rate and can be represented by the formula in inner ear hair cells：
Wherein, y (1-q (t)) is the amount that manufactory adds to hair cell neurotransmitter, and xw (t) is flowed back to by regenerating storehouse
The amount of hair cell neurotransmitter ,-k (t) q (t) flow to the amount of space between cells neurotransmitter out of hair cell.They are together decided on
The amount of neurotransmitter in inner ear hair cells changes with time rate.
(3) amount of outside neurotransmitter
The amount c (t) of outside neurotransmitter changes over time available following formula description：
Wherein, k (t) q (t) are the neurotransmitters that inner hair cell flows into space between cells, and-lc (t) is that space between cells is flowed out
Neurotransmitter ,-rc (t) are the neurotransmitters flowed out to from space between cells in regeneration storehouse, and the amount of space between cells neurotransmitter is at any time
Between rate of change thus three decision.
(4) amount of neurotransmitter in storehouse is regenerated
Amount w (t) rates of changing with time of neurotransmitter are expressed from the next in regeneration storehouse：
(5) nerve fibre excitation probability
The amount c (t) for eventually settling at the neurotransmitter in space between cells determines the probability that rear class nerve conduction fiber excites,
Represent as follows with scale factor h：
P (t)=hc (t) dt
Step 5：, each channel band energy of each hearing spectrum forms is calculated, forms the characteristic vector containing aural signature.
The centre frequency of above example setup algorithm is from 5kHz to 10kHz, the dolphin whistle signal feature that will extract
Vector is analyzed, and compared with extracting characteristic vector under different degrees of underwater ambient noise.As a result show to extract feature
There are higher correct recognition rata, a preferable noise robustness, it was demonstrated that effectiveness of the invention.
Claims (2)
1. based on the dolphin whistle signal aural signature extracting method of analog cochlea in bionical auditory system, it is characterized in that：
(1) dolphin cry is sampled, obtains faithful record signal s (n), faithful record signal s (n) is normalized pretreatment：
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(2) signal that step (1) obtains is obtained into M subband signal, M is wave filter by Gammatone auditory filter groups
Number, quick FFT is carried out to each subband signal；
The impulse response of Gammatone wave filters is：
In formula：A represents the amplitude factor of gammatone wave filters, and n represents the exponent number of gammatone wave filters, fcRepresent
The centre frequency of gammatone wave filters,Represent the initial phase of gammatone wave filters, 2 π bERB (fc) represent damping because
Son, u (t) represent unit-step function；
ERB represents equivalent rectangular bandwidth, and its expression formula is：ERB(fc)=24.7+0.108fc；
It is as follows that Laplace transform is done to gammatone filter impulse responses functions：
Wherein, A is filter gain, and n is filter order, fcCentered on frequency,For phase, b=2 π ERB (fc), w=2 π
fc；
(3) Fast Fourier Transform (FFT) is done to step (2) subband signal, by low pass filter, and generates hearing spectrum forms；
(4) halfwave rectifier, generation simulation human ear sense are carried out by Meddis inner hair cells model to step (2) filtered signal
The hearing spectrum forms known, each channel band energy of hearing spectrum forms is calculated, forms the characteristic vector containing aural signature；
(5) each channel band energy of each hearing spectrum forms is calculated, forms the characteristic vector containing aural signature：
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2. the dolphin whistle signal aural signature extraction according to claim 1 based on analog cochlea in bionical auditory system
Method, it is characterized in that：Meddis models include five physical quantitys：The amount of neurotransmitter in cell membrane permeability, inner ear hair cells,
The amount of capillary intercellular space neurotransmitter, regenerate the amount of neurotransmitter, excitation probability in storehouse：
(1) cell membrane permeability：
Reflection neurotransmitter describes in the following way from inner hair cell to the permeability of hair cell gap transmission ability：
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K (t) is cell membrane permeability, and stim (t) is the instantaneous amplitude for inputting sound wave, A, B, and g is cell parameters, k (t)=A/ (A
+ B) g represent cell membrane spontaneous response；
(2) in inner ear hair cells neurotransmitter amount：
The amount q (t) of neurotransmitter changes over time rate and can be represented by the formula in inner ear hair cells：
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Wherein, y (1-q (t)) is the amount that manufactory adds to hair cell neurotransmitter, and xw (t) is to flow back to capillary by regenerating storehouse
The amount of born of the same parents' neurotransmitter ,-k (t) q (t) flow to the amount of space between cells neurotransmitter out of hair cell；
(3) amount of outside neurotransmitter：
The amount c (t) of outside neurotransmitter changes over time to be described with following formula：
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Wherein, k (t) q (t) are the neurotransmitters that inner hair cell flows into space between cells, and-lc (t) is the nerve of space between cells outflow
Mediator ,-rc (t) are the neurotransmitters flowed out to from space between cells in regeneration storehouse；
(4) amount of neurotransmitter in storehouse is regenerated：
Amount w (t) rates of changing with time of neurotransmitter are expressed from the next in regeneration storehouse：
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</mrow>
<mo>;</mo>
</mrow>
(5) nerve fibre excitation probability：
The amount c (t) for eventually settling at the neurotransmitter in space between cells determines the probability that rear class nerve conduction fiber excites, with than
Example factor h represents as follows：
P (t)=hc (t) dt.
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