CN113973250B - Noise suppression method and device and hearing-aid earphone - Google Patents
Noise suppression method and device and hearing-aid earphone Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R1/00—Details of transducers, loudspeakers or microphones
- H04R1/10—Earpieces; Attachments therefor ; Earphones; Monophonic headphones
- H04R1/1083—Reduction of ambient noise
Abstract
The present disclosure relates to a noise suppression method, a device, and an auxiliary hearing earphone, where the noise suppression method is used for noise suppression of the auxiliary hearing earphone, and includes: acquiring an environmental audio signal; after the environmental audio signal is processed by an analysis filter bank, the environmental audio signal is divided into a plurality of first sub-band parts according to frequency bands; downsampling the environmental audio signal and transforming the environmental audio signal to a frequency domain to obtain a plurality of second sub-band portions, wherein the frequency band intervals of the plurality of second sub-band portions are smaller than or equal to the minimum frequency band intervals of the plurality of first sub-band portions; determining the voice existence probability of each second sub-band part; determining a gain of each second sub-band based on a probability of speech presence of the second sub-band; processing each first sub-band portion based on the gain of each second sub-band portion; and synthesizing each of the processed first sub-band portions. The method can achieve good noise reduction effect while achieving low-delay hearing assistance, and effectively improves the use experience of the hearing assistance earphone.
Description
Technical Field
The present disclosure relates to signal processing technology, and more particularly, to a noise suppression method, apparatus, and hearing aid earphone.
Background
When the existing PSAP earphone amplifies the environmental sound, the voice signal and the environmental noise signal are amplified simultaneously, but sometimes the user has a communication requirement, and at the moment, the external environmental noise can influence the voice intelligibility to prevent normal communication.
The special of the use scene of the auxiliary hearing earphone causes the contradiction between noise reduction and auxiliary hearing, on one hand, the auxiliary hearing earphone needs to enable the sound of a speaker in the environment to pass through the auxiliary hearing earphone and requires low delay, and on the other hand, the auxiliary hearing earphone also needs to enable the noise in the environment to be reduced, so that the noise reduction effect is achieved. In practical use, the noise in the environment and the sound of the speaker are high in probability at the same time, and the noise reduction is very difficult at the moment, and if the noise is not reduced, the user feels that the environmental noise is too large, so that communication is affected.
Disclosure of Invention
The aim is to provide a noise suppression method and device and an auxiliary hearing earphone, so as to realize the noise reduction effect of the auxiliary hearing earphone.
In a first aspect, embodiments of the present disclosure provide a noise suppression method for noise suppression of a hearing aid earphone, the noise suppression method including the steps of: acquiring an environmental audio signal; after the environmental audio signal is processed by an analysis filter bank, dividing the environmental audio signal into a plurality of first sub-band parts according to frequency bands; downsampling the environmental audio signal and transforming the environmental audio signal to a frequency domain to obtain a plurality of second sub-band parts, wherein the frequency band intervals of the plurality of second sub-band parts are smaller than or equal to the minimum frequency band intervals of the plurality of first sub-band parts; determining the voice existence probability of each second sub-band part; determining a gain of each second sub-band based on a probability of speech presence of the second sub-band; processing each first sub-band portion based on the gain of each second sub-band portion; and synthesizing each of the processed first sub-band portions.
In a second aspect, embodiments of the present disclosure also provide a noise suppression apparatus comprising a memory and a processor; the memory is used for storing a computer program, and the processor is used for realizing the steps of the noise suppression method according to each embodiment of the disclosure when the computer program is executed.
In a third aspect, embodiments of the present disclosure also provide a noise suppression component comprising a processor configured to: downsampling an environmental audio signal acquired by a feedforward microphone of the auxiliary hearing earphone and transforming the environmental audio signal into a frequency domain to acquire a plurality of second sub-band parts, wherein the frequency band intervals of the plurality of second sub-band parts are smaller than or equal to the minimum frequency band intervals among the first sub-band parts processed by a first filter bank of the auxiliary hearing earphone; determining the voice existence probability of each second sub-band part; determining a gain of each second sub-band based on a probability of speech presence of the second sub-band; each first subband section is processed based on the gain of each second subband section.
In a fourth aspect, embodiments of the present disclosure further provide a hearing aid earphone including a feedforward microphone, a first filter bank, a second filter bank, and the aforementioned noise suppression component: the feedforward microphone is configured to acquire an environmental audio signal; the first filter bank is configured to divide the environmental audio signal into a plurality of first sub-band parts according to frequency bands; and the second filter bank synthesizes the first sub-band portions processed by the noise suppression component.
By utilizing the noise suppression method, the device and the hearing aid earphone according to the various embodiments of the present disclosure, the gains of the second sub-band portions are determined by determining the voice existence probabilities of the plurality of the second sub-band portions in the frequency domain, so that the gains of the second sub-band portions are determined, the gains of the first sub-band portions corresponding to the hardware loop of the hearing aid earphone are adjusted by utilizing the gains of the second sub-band portions, a good noise reduction effect is achieved while hearing aid is achieved, and the use experience of the hearing aid earphone is effectively improved.
Drawings
In the drawings, which are not necessarily drawn to scale, like numerals may describe similar components in different views. The same reference numerals with letter suffixes or different letter suffixes may represent different instances of similar components. The accompanying drawings illustrate various embodiments by way of example in general and not by way of limitation, and together with the description and claims serve to explain the disclosed embodiments. Such embodiments are illustrative and not intended to be exhaustive or exclusive of the present apparatus or method.
Fig. 1 shows a signal processing flow diagram of a PSAP earpiece in accordance with the present disclosure;
FIG. 2 illustrates a basic flow diagram of a noise suppression method according to the present disclosure;
FIG. 3 shows a schematic diagram of a signal processing flow according to the noise suppression method of the present disclosure;
fig. 4 shows a flowchart of determining the gain of each first subband according to the noise suppression methods of the present disclosure.
Detailed Description
In order to better understand the technical solutions of the present disclosure, the following detailed description of the present disclosure is provided with reference to the accompanying drawings and the specific embodiments. Embodiments of the present disclosure will be described in further detail below with reference to the drawings and specific embodiments, but not by way of limitation of the present disclosure.
The terms "first," "second," and the like, as used in this disclosure, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises" and the like means that elements preceding the word encompass the elements recited after the word, and not exclude the possibility of also encompassing other elements.
The embodiment of the disclosure proposes a noise suppression method for a hearing-aid PSAP earphone, fig. 1 shows a signal processing schematic diagram of the PSAP earphone, as shown in fig. 1, after an environmental audio signal x (n) passes through an analysis filter bank of the hearing-aid earphone, the environmental audio signal x (n) is divided into a plurality of sub-band portions according to frequency bands, the sub-band portions may respectively correspond to a subsequent multiplier (Gain 0-GainN), for example, one multiplier may correspondingly process a frequency band, the signal after being processed by the multiplier enters a corresponding dynamic range control DRC, as shown in fig. 1, the dynamic range control (DRC 0-DRCN) is included, and finally, the synthesized signal y (n) is output after passing through a synthesis filter bank. Because the noise analysis module has higher calculation complexity and larger circuit scale, the noise reduction of the hearing aid earphone is very difficult to directly realize on a hardware structure, and the noise reduction method of adding the noise analysis module into the hardware structure can add a data buffer structure on the existing path so as to introduce more extra processing delay, thereby influencing the user experience, so that the noise reduction method cannot be applied to the scene requiring low delay for hearing aid. As shown in fig. 2, the noise suppression method proposed in the present disclosure starts with step S201, where an environmental audio signal is acquired, for example, the environmental audio signal may include a speech signal and an environmental noise signal. After the environmental audio signal is subjected to the processing of the analysis filter bank in step S202, it is divided into a plurality of first subband parts by frequency band. I.e. the analysis filter bank of the PSAP earpiece hardware loop can be directly utilized to divide the ambient audio signal into a plurality of first sub-band parts according to the frequency band.
Then in step S203, the environmental audio signal is downsampled and transformed to the frequency domain, so as to obtain a plurality of second subband parts, where the frequency band intervals of the plurality of second subband parts are smaller than or equal to the minimum frequency band intervals of the plurality of first subband parts. As shown in fig. 3, the downsampling and transforming the environmental audio signal into the frequency domain may be performed by a software algorithm, for example, FFT transforming the environmental audio signal, where the frequency band interval of the downsampled second subband is smaller than or equal to the minimum frequency band interval of the first subband, and by this arrangement, it is ensured that the second subband can be completely mapped onto the first subband, so that any environmental audio signal is not omitted, and the integrity of the signal is ensured.
The voice presence probability of each second subband part is determined in step S204, and the voice presence probability of each frequency band may be determined based on the second subband part of each frequency band, for example. The second sub-band portion of each frequency band may uniquely determine a corresponding voice existence probability.
The gain of each second subband is determined based on the probability of speech presence of the second subband in step S205. For example, the gain of the second sub-band part with the voice existence probability of 0 can be set to be 0, so that noise in the frequency band can be directly filtered, the gain of the second sub-band part can be correspondingly set according to the voice existence probability of other frequency bands with voices, and by adopting the setting mode, voice components in each second sub-band part can be effectively highlighted, and meanwhile, environmental noise components are reduced, so that the purpose of noise reduction is achieved.
Finally, in step S206, each of the first sub-band portions is processed based on the gain of each of the second sub-band portions; and synthesizing each of the processed first sub-band portions. According to the method, the gain determined by the software algorithm can be mapped into a hardware loop, noise reduction can be achieved through a multiplier in the hardware loop, and a noise-reduced signal is output after synthesis through a subsequent synthesis filter.
In some embodiments, after the frequency band is divided into a plurality of first sub-band parts by the processing of the analysis filter, and each sub-band gain adjustment is performed, DRC processing is completed by the synthesis processing of the synthesis filter through a hardware channel of the hearing aid earphone, and the sampling frequency of the hardware channel is greater than or equal to 96kHz. Reference is also made to 3 for specific hardware paths, which may include analysis filters, multipliers (Gain 0-GainN), dynamic range control (DRC 0-DRCN), and synthesis filters, e.g., multipliers having the function of performing Gain adjustments for each subband Gain obtained according to a software algorithm. By setting the hardware path of the hearing aid earphone to operate in a high sampling rate (96 kHz) mode, path delay caused by the fact that a downsampling filter is required to be introduced because of data downsampling is avoided. And because the hardware path does not need to be participated by software, other data buffer structures which can introduce delay are not existed on the hardware path, the delay of the hearing aid earphone is greatly reduced by the mode.
In some embodiments, as shown in fig. 4, processing each first subband section based on the gain of each second subband section may specifically include: in step S401, a first frequency band of each first sub-band portion is determined, and a second frequency band of each second sub-band portion is determined. For example, in fig. 3, the first frequency band of the environmental audio signal divided into the plurality of first sub-band parts by the analysis filter bank of the hardware loop is 500, 1000,2000,4000 …, and the second frequency band of the second sub-band part after the FFT of the software algorithm may be 125, 250, 375, 500, 625, 750, 875, 1000, 1125, …, which is just an example, and a specific sampling frequency band may be set according to practical needs.
In step S402, the selectable gain of each first subband section is determined based on the gain of each second subband section and the inclusion relationship between each second frequency band and each first frequency band. For example, in one example, the second sub-band portion 125, 250, 375, 500 has a correspondence with the first sub-band portion 500, and then the gain of the first sub-band portion 500 may be used as the selectable gain of the first sub-band portion 500 according to the gain of the second sub-band portion 125, 250, 375, 500.
The gain of each first sub-band portion is determined in step S403 based on the selectable gain of that first sub-band portion. For example, a gain of one band may be selected from among selectable gains of 125, 250, 375, 500 bands as the gain of 500 bands of the first sub-band portion. The gain of each frequency band in the hardware loop can be determined in such a way, so that the purpose of noise reduction is further realized through the gain of each first frequency band in the process of signal processing.
Determining the gain of each first sub-band portion based on the selectable gain of that first sub-band portion specifically includes: the maximum value of the selectable gains of each first subband section is determined as the gain of that first subband section. As a specific manner of determining the gain, a maximum value of the selectable gains corresponding to the second frequency band may be determined as the gain of the first subband, for example, assuming that the second frequency band of the FFT is: 125, 250, 375, 500, 625, 750, 875, 1000, 1125, 1250,...,8000. The gains corresponding to the second frequency bands are as follows: g0 G1, G2, G3, G4, G5, G6, G7, G8, G9, &. The first frequency band of each first sub-band portion is: 500, 1000,2000,4000, 8000. The gains of the first sub-band portions are G '0, G '1, G '2, G '3, G '4, then:
G’0＝max{G0，G1，G2，G3}；
G’1＝max{G4，G5，G6，G7}；
G’2＝max{G8，G9，G10，G11，G12，G13，G14，G15}；
G’3＝max{G16，G13，G14，G15，...，G31}；
G’4＝max{G32，G33，G34，G35，...，G63}。
the maximum value is selected, so that the first sub-band portions can achieve the best voice definition retention effect and the proper filtering effect on the environmental noise, and the purpose of noise reduction is achieved while hearing assistance is achieved. The software algorithm utilized by the method can obtain the effect of low delay even under the condition of higher sampling rate, thereby overcoming the defect of high delay and complexity caused by noise reduction realized by a hardware or software method. The noise reduction method is particularly suitable for PSAP earphones, on one hand, low delay can be brought, on the other hand, good noise reduction and filtering effects can be achieved through the method, and the use experience of the hearing aid earphone is improved.
In some embodiments, the speech presence probability of each second sub-band portion is a posterior speech presence probability, and determining the speech presence probability of each second sub-band portion specifically includes: the posterior speech presence probability is determined based on the prior speech presence probability, the prior signal-to-noise ratio and the intermediate variable represented by the prior signal-to-noise ratio and the posterior signal-to-noise ratio of each second subband portion such that the posterior speech presence probability increases with an increase in the prior signal-to-noise ratio and/or the intermediate variable.
For example, as a specific example, the speech presence probability p (k) of each second subband part satisfies:
where q (k) represents a priori speech presence probability, typically with a value of 0.5, ζ (k) represents a priori signal-to-noise ratio of frequency bin k, and v (k) represents an intermediate variable that, in some embodiments, increases with increasing a priori signal-to-noise ratio and/or a posterior signal-to-noise ratio. For example, v (k) =γ (k) ζ (k)/(ζ (k) +1), and γ (k) represents a posterior signal-to-noise ratio. ζ (k) =α p G 2 (k,l-1)|Y(k,l-1)| 2 +(1-α p ) max { gamma (k, l) -1,0}, l represents the current frame, l-1 represents the last frame, alpha p A constant between 0 and 1.Represents the posterior signal-to-noise ratio of band k, |Y (k) | 2 Represents signal power, and λ (k) represents noise power.
An exemplary noise power λ (k) iterative calculation satisfies:
λ(k,l)＝α pow λ(k,l-1)+(1-α pow )(1-p(k))|Y(k,l)| 2
α pow with a constant between 0 and 1, l represents the current frame and l-1 represents the previous frame.
In some embodiments, determining the gain of each second subband based on the probability of speech presence of the second subband specifically comprises: the gain of each second sub-band is determined based on the posterior speech presence probability, the intermediate spectral gain, and the lower gain limit when speech is absent, so that the gain increases with the posterior speech presence probability and the intermediate spectral gain of the second sub-band. For example, the gain of each frequency band is determined, and the calculation method satisfies:
wherein G is min Is a constant, and represents the lower limit of noise reduction gain when no voice exists, and the minimum is 0. Alpha is a constant and typically takes on a value of 1/2.Representing the intermediate spectral gain.
The method meets the following conditions:
wherein,for chi-square distribution function, < >>Is a confluent super-geometric function.
The above noise reduction gain calculation method is just one embodiment of the present application, and the specific noise reduction gain calculation method may also be obtained by using various single-channel or multi-channel microphone noise reduction schemes, such as a single-channel-based DNN method, an OMLSA method, a smooth noise estimation-based MMSE noise reduction method, and a multi-channel-based MVDR, DNN method.
If a general processing means is adopted, a noise reduction module is added in front of the PSAP path, and the PSAP earphone is sent into the PSAP path after noise reduction processing, so that the path delay is greatly increased, and the naturalness of the hearing aid effect is affected. But if noise is not reduced, the user feels that the environmental noise is too large, and communication is affected. The noise suppression method disclosed by the application can estimate the noise in the incoming data of the external environment in real time under the low sampling rate, analyze the noise distribution condition and determine the gain of the frequency band, thereby controlling the gain of each sub-band on the PSAP hardware channel (on the high sampling rate) in real time, reducing the noise and ensuring that a user can have good use experience under different scenes.
The embodiment of the disclosure also provides a noise suppression device, which comprises a memory and a processor; the memory is used for storing a computer program, and the processor is used for realizing the steps of the noise suppression method according to each embodiment of the disclosure when the computer program is executed.
Embodiments of the present disclosure also provide a noise suppression component comprising a processor configured to: downsampling an environmental audio signal acquired by a feedforward microphone of the auxiliary hearing earphone and transforming the environmental audio signal into a frequency domain to acquire a plurality of second sub-band parts, wherein the frequency band intervals of the plurality of second sub-band parts are smaller than or equal to the minimum frequency band intervals among the first sub-band parts processed by a first filter bank of the auxiliary hearing earphone; determining the voice existence probability of each second sub-band part; determining a gain of each second sub-band based on a probability of speech presence of the second sub-band; each first subband section is processed based on the gain of each second subband section. A processor may be a processing device in some embodiments that includes one or more general-purpose processing devices, such as a microprocessor, central Processing Unit (CPU), graphics Processing Unit (GPU), or the like. More specifically, the processor may be a Complex Instruction Set Computing (CISC) microprocessor, a Reduced Instruction Set Computing (RISC) microprocessor, a Very Long Instruction Word (VLIW) microprocessor, a processor running other instruction sets, or a processor running a combination of instruction sets. A processor may also be one or more special-purpose processing devices such as an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), a system on a chip (SoC), or the like. As will be appreciated by those skilled in the art, in some embodiments, the processor may be a special purpose processor, rather than a general purpose processor. The processor may include one or more known processing devices such as a Pentium (TM), core (TM), xeon (TM) or Itanium (TM) series of microprocessors manufactured by Intel corporation, turion (TM), athlon (TM), sempron (TM), opteron (TM), FX manufactured by AMD corporation TM 、Phenom TM Any of a variety of processors manufactured by a family of microprocessors or solar Microsystems (Sun Microsystems). The processor may also include a graphics processing unit, such as those manufactured by Nvidia corporationA series of GPUs, a GMA manufactured by intel (TM), an Iris (TM) series of GPUs, or a Radeon (TM) series of GPUs manufactured by AMD corporation. The processor may also include an accelerated processing unit such as the desktop A-4 (6, 8) series manufactured by AMD corporation, the Xeon Phi TM series manufactured by Intel corporation. The disclosed embodiments are not limited to any type of processor or processor circuit that is otherwise configured to satisfy processing of an ambient audio signal. In addition, the term "processor" or "image processor" may include more than one processor, for example, a multi-core design or a plurality of processors, each of the plurality of processors having a multi-core design.
In some embodiments, the processor is further configured to determine a first frequency band for each first sub-band portion and to determine a second frequency band for each second sub-band portion; determining the selectable gain of each first sub-band portion based on the gain of each second sub-band portion and the inclusion relationship between each second frequency band and each first frequency band; the gain of each first sub-band portion is determined based on the selectable gain of that first sub-band portion.
In some embodiments, the processor is further configured to determine a maximum value of the selectable gains for each first subband as the gain for that first subband.
In some embodiments, the speech presence probability of each second sub-band portion is a posterior speech presence probability, and determining the speech presence probability of each second sub-band portion specifically includes: the posterior speech presence probability is determined based on the prior speech presence probability, the prior signal-to-noise ratio and the intermediate variable represented by the prior signal-to-noise ratio and the posterior signal-to-noise ratio of each second subband portion such that the posterior speech presence probability increases with an increase in the prior signal-to-noise ratio and/or the intermediate variable.
In some embodiments, the intermediate variable increases with an increase in the a priori signal to noise ratio and/or the a posteriori signal to noise ratio.
The embodiment of the disclosure also provides a hearing-aid earphone, which comprises a feedforward microphone, a first filter bank, a second filter bank and the noise suppression component: the feedforward microphone is configured to acquire an environmental audio signal; the first filter bank is configured to divide the environmental audio signal into a plurality of first sub-band parts according to frequency bands; and the second filter bank synthesizes the first sub-band portions processed by the noise suppression component. Wherein the first filter bank may be an analysis filter bank of the PSAP headset hardware loop and the second filter bank may be a synthesis filter bank of the PSAP headset hardware loop. The hearing aid earphone can map the gain determined by the software algorithm into the hardware loop, further can realize noise reduction processing through a multiplier in the hardware loop, outputs a noise-reduced signal after synthesis through a subsequent synthesis filter, has high response speed, can meet hearing assistance, plays a low-delay effect, and can effectively improve the use experience of a user.
In this document, the terms "a" or "an" are used, as is common in patent documents, to include one or more than one, independent of any other instance or usage of "at least one" or "one or more". In this document, unless otherwise indicated, the term "or" is used to refer to non-exclusivity, or such that "a or B" includes "a but not B", "B but not a" and "a and B". In this document, the terms "include" and "wherein (in white)" are used as popular English equivalents of the respective terms "include" and "wherein (white)". Moreover, in the following claims, the terms "include" and "comprise" are open-ended, i.e., a device, system, apparatus, article, composition, formula, or process that comprises elements other than those listed after the term in the claim, also is contemplated as falling within the scope of the claim. Furthermore, in the following claims, the terms "first," "second," and "third," etc. are used merely as labels, and are not intended to impose numerical requirements on their objects.
The exemplary methods described herein may be at least partially machine or computer implemented. Some examples may include a computer-readable medium or machine-readable medium encoded with instructions operable to configure an electronic device to perform a method as described in the examples above. Implementations of such methods may include software code, such as microcode, assembly language code, higher-level language code, or the like. Various programs or program modules may be created using various software programming techniques. For example, program segments or program modules may be designed using Java, python, C, C ++, assembly language, or any known programming language. One or more such software portions or modules may be integrated into a computer system and/or computer readable medium. Such software code may include computer readable instructions for performing various methods. The software code may form part of a computer program product or a computer program module. Moreover, in one example, the software code can be tangibly stored on one or more volatile, non-transitory, or non-volatile tangible computer-readable media, such as during execution or at other times. Examples of such tangible computer-readable media may include, but are not limited to, hard disks, removable magnetic disks, removable optical disks (e.g., optical disks and digital video disks), magnetic cassettes, memory cards or sticks, random Access Memories (RAMs), read Only Memories (ROMs), and the like.
Furthermore, although exemplary embodiments have been described herein, the scope thereof includes any and all embodiments having equivalent elements, modifications, omissions, combinations (e.g., of the various embodiments across schemes), adaptations or alterations based on the present disclosure. The elements in the claims are to be construed broadly based on the language employed in the claims and are not limited to examples described in the present specification or during the practice of the application, which examples are to be construed as non-exclusive. It is intended, therefore, that the specification and examples be considered as exemplary only, with a true scope and spirit being indicated by the following claims and their full scope of equivalents.
The above description is intended to be illustrative and not restrictive. For example, the above-described examples (or one or more aspects thereof) may be used in combination with each other. For example, other embodiments may be used by those of ordinary skill in the art upon reading the above description. In addition, in the above detailed description, various features may be grouped together to streamline the disclosure. This is not to be interpreted as an intention that the disclosed features not being claimed are essential to any claim. Rather, the disclosed subject matter may include less than all of the features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the detailed description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that these embodiments may be combined with one another in various combinations or permutations. The scope of the application should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.
The above embodiments are only exemplary embodiments of the present disclosure, and are not intended to limit the present application, the scope of which is defined by the claims. Various modifications and equivalent arrangements of parts may be made by those skilled in the art, which modifications and equivalents are intended to be within the spirit and scope of the present disclosure.
Claims (7)
1. A noise suppression method for noise suppression of a hearing aid earphone, the noise suppression method comprising the steps of:
acquiring an environmental audio signal;
after the environmental audio signal is processed by an analysis filter bank, dividing the environmental audio signal into a plurality of first sub-band parts according to frequency bands;
downsampling the environmental audio signal and transforming the environmental audio signal to a frequency domain to obtain a plurality of second sub-band parts, wherein the frequency band intervals of the plurality of second sub-band parts are smaller than or equal to the minimum frequency band intervals of the plurality of first sub-band parts;
determining the voice existence probability of each second sub-band part;
determining a gain of each second sub-band based on a probability of speech presence of the second sub-band;
processing each first sub-band portion based on the gain of each second sub-band portion; and
synthesizing the processed first sub-band parts,
processing each first sub-band portion based on the gain of each second sub-band portion specifically includes:
determining a first frequency band of each first sub-band part and a second frequency band of each second sub-band part;
determining the selectable gain of each first sub-band portion based on the gain of each second sub-band portion and the inclusion relationship between each second frequency band and each first frequency band;
the gain of each first sub-band portion is determined based on the selectable gain of that first sub-band portion,
determining the gain of each first sub-band portion based on the selectable gain of that first sub-band portion specifically includes: the maximum value of the selectable gains of each first subband section is determined as the gain of that first subband section.
2. The noise suppression method according to claim 1, wherein the speech presence probability of each second subband section is a posterior speech presence probability, and determining the speech presence probability of each second subband section specifically includes: the posterior speech presence probability is determined based on the prior speech presence probability, the prior signal-to-noise ratio and the intermediate variable represented by the prior signal-to-noise ratio and the posterior signal-to-noise ratio of each second subband portion such that the posterior speech presence probability increases with an increase in the prior signal-to-noise ratio and/or the intermediate variable.
3. The noise suppression method of claim 2, wherein the intermediate variable increases with an increase in the a priori signal to noise ratio and/or the a posteriori signal to noise ratio.
4. The noise suppression method according to claim 1, wherein after being divided into a plurality of first subband parts by the processing of the analysis filter according to the frequency band and performing the gain adjustment of each subband, the DRC processing is completed by the synthesizing processing of the synthesizing filter through the hardware path of the hearing aid earphone, and the sampling frequency of the hardware path operation is greater than or equal to 96kHz.
5. A noise suppression apparatus comprising a memory and a processor; wherein the memory is configured to store a computer program, and the processor is configured to implement the steps of the noise suppression method according to any one of claims 1 to 4 when the computer program is executed.
6. A noise suppression assembly comprising a processor configured to:
downsampling an environmental audio signal acquired by a feedforward microphone of the auxiliary hearing earphone and transforming the environmental audio signal into a frequency domain to acquire a plurality of second sub-band parts, wherein the frequency band intervals of the plurality of second sub-band parts are smaller than or equal to the minimum frequency band intervals among the first sub-band parts processed by a first filter bank of the auxiliary hearing earphone;
determining the voice existence probability of each second sub-band part;
determining a gain of each second sub-band based on a probability of speech presence of the second sub-band;
processing each first sub-band portion based on the gain of each second sub-band portion; and
synthesizing the processed first sub-band parts,
processing each first sub-band portion based on the gain of each second sub-band portion specifically includes:
determining a first frequency band of each first sub-band part and a second frequency band of each second sub-band part;
determining the selectable gain of each first sub-band portion based on the gain of each second sub-band portion and the inclusion relationship between each second frequency band and each first frequency band;
the gain of each first sub-band portion is determined based on the selectable gain of that first sub-band portion,
determining the gain of each first sub-band portion based on the selectable gain of that first sub-band portion specifically includes: the maximum value of the selectable gains of each first subband section is determined as the gain of that first subband section.
7. A hearing aid earphone comprising a feedforward microphone, a first filter bank, a second filter bank, and a noise suppression component as recited in claim 6:
the feedforward microphone is configured to acquire an environmental audio signal;
the first filter bank is configured to divide the environmental audio signal into a plurality of first sub-band parts according to frequency bands;
and the second filter bank synthesizes the first sub-band portions processed by the noise suppression component.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101510426A (en) * | 2009-03-23 | 2009-08-19 | 北京中星微电子有限公司 | Method and system for eliminating noise |
| CN105845150A (en) * | 2016-03-21 | 2016-08-10 | 福州瑞芯微电子股份有限公司 | Voice enhancement method and system adopting cepstrum to correct |
| CN108831499A (en) * | 2018-05-25 | 2018-11-16 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Utilize the sound enhancement method of voice existing probability |
| CN109979478A (en) * | 2019-04-08 | 2019-07-05 | 网易（杭州）网络有限公司 | Voice de-noising method and device, storage medium and electronic equipment |
| CN110164467A (en) * | 2018-12-18 | 2019-08-23 | 腾讯科技（深圳）有限公司 | The method and apparatus of voice de-noising calculate equipment and computer readable storage medium |
| CN111292761A (en) * | 2019-05-10 | 2020-06-16 | 展讯通信(天津)有限公司 | Voice enhancement method and device |
| CN113270106A (en) * | 2021-05-07 | 2021-08-17 | 深圳市友杰智新科技有限公司 | Method, device and equipment for inhibiting wind noise of double microphones and storage medium |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2473267A (en) * | 2009-09-07 | 2011-03-09 | Nokia Corp | Processing audio signals to reduce noise |
| US20120245927A1 (en) * | 2011-03-21 | 2012-09-27 | On Semiconductor Trading Ltd. | System and method for monaural audio processing based preserving speech information |
| US10432434B2 (en) * | 2016-07-20 | 2019-10-01 | Tektronix, Inc. | Multi-band noise reduction systems and methods |
-
2021
- 2021-10-26 CN CN202111249997.0A patent/CN113973250B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101510426A (en) * | 2009-03-23 | 2009-08-19 | 北京中星微电子有限公司 | Method and system for eliminating noise |
| CN105845150A (en) * | 2016-03-21 | 2016-08-10 | 福州瑞芯微电子股份有限公司 | Voice enhancement method and system adopting cepstrum to correct |
| CN108831499A (en) * | 2018-05-25 | 2018-11-16 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Utilize the sound enhancement method of voice existing probability |
| CN110164467A (en) * | 2018-12-18 | 2019-08-23 | 腾讯科技（深圳）有限公司 | The method and apparatus of voice de-noising calculate equipment and computer readable storage medium |
| CN109979478A (en) * | 2019-04-08 | 2019-07-05 | 网易（杭州）网络有限公司 | Voice de-noising method and device, storage medium and electronic equipment |
| CN111292761A (en) * | 2019-05-10 | 2020-06-16 | 展讯通信(天津)有限公司 | Voice enhancement method and device |
| CN113270106A (en) * | 2021-05-07 | 2021-08-17 | 深圳市友杰智新科技有限公司 | Method, device and equipment for inhibiting wind noise of double microphones and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 实时多通道数字助听器降噪算法;梁瑞宇,赵力,王青云,邹采荣,荆丽;东南大学学报(自然科学版);第第46卷卷(第第1期期);13-17 * |
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