WO2019079948A1

WO2019079948A1 - Earphone and method for performing an adaptively self-tuning for an earphone

Info

Publication number: WO2019079948A1
Application number: PCT/CN2017/107362
Authority: WO
Inventors: SuneLonbaek OLSEN; Andras Palfi; David Meijer; Torben JUULREJKJAER; Morten BIRKMOSESONDERGAARD; Sebastien CURDY
Original assignee: Goertek Inc.
Priority date: 2017-10-23
Filing date: 2017-10-23
Publication date: 2019-05-02
Also published as: CN207652638U; CN107948785A; CN107948785B

Abstract

An earphone and a method for performing an adaptively self-tuning for an earphone are disclosed. The earphone comprises: a pre-processing filter, performing a pre-processing on the first audio signal to output a second audio signal; a speaker, playing the second audio signal as an acoustic wave into a user's ear; a microphone, converting the acoustic wave into a third audio signal; and an adaptive algorithm unit, performing an adaptive algorithm on a first signal component and a second signal component to update filter coefficients for the pre-processing filter, wherein the first signal component includes at least one portion of the third audio signal and the second signal component includes at least one portion of the second audio signal which corresponds to said at least one portion of the third audio signal.

Description

EARPHONE AND METHOD FOR PERFORMING AN ADAPTIVELY SELF-TUNING FOR AN EARPHONE

FIELD OF THE INVENTION

The present invention relates to the technical field of earphone, and more specifically, to an earphone and a method for performing an adaptively self-tuning for an earphone.

BACKGROUND OF THE INVENTION

Generally, when a user listens to a music song via an earphone, the amount of bass perceived by the user depends on how much the earphone mechanically seals the user’s ear. The more the earphone seals the ear canal, the larger amount of bass will be perceived. If there are leaks between the ear canal and the earphone, the perceived bass will decrease. Since it is impossible to provide a consistent bass response across all users with one mechanical design, how to address this perception discrepancy presents a challenge for an earphone developer.

Similar situations may be applied to any other frequency range which may also vary from person to person.

The earphone may include a headset, an in-ear headphone such as an earbud, and so on.

In the prior art, a test signal is used to calibrate the response of an earphone in advance. This will not work or will be not convenient if a user adjusts his wearing of an earphone during playing a music song, for example.

In addition, a prior art real-time calibration solution uses a predicted output of a speaker, which may not be accurate and may be complicated. In such a solution, a frequency domain adaptive algorithm shall be used, which adds complexity to the design of an earphone.

Therefore, there is a demand in the art that a new solution for an earphone shall be proposed to address at least one of the problems in the prior art.

SUMMARY OF THE INVENTION

One object of this invention is to provide a new technical solution for adaptive pre-processing for an earphone.

According to a first aspect of the present invention, an earphone is provided, comprising: a pre-processing filter, which receives a first audio signal and performs a pre-processing on the first audio signal to output a second audio signal； a speaker, which receives the second audio signal and plays it as an acoustic wave into a user’s ear； a microphone, which receives the acoustic wave and converts it into a third audio signal； and an adaptive algorithm unit, which receives a first signal component and a second signal component, and performs an adaptive algorithm on the first signal component and the second signal component to update filter coefficients for the pre-processing filter, wherein the first signal component includes at least one portion of the third audio signal and the second signal component includes at least one portion of the second audio signal which corresponds to said at least one portion of the third audio signal.

Alternatively or optionally, the pre-processing filter is a pre-equalization filter and performs pre-equalization on the first audio signal.

Alternatively or optionally, the first audio signal is a content audio signal from an audio source.

Alternatively or optionally, the earphone further comprises: a first filter, wherein the third audio signal is coupled to the input of the first filter and the first filter produces the first signal component； and a second filter, wherein the second audio signal is coupled to the input of the second filter and the second filter produces the second signal component.

Alternatively or optionally, the earphone further comprises: a target filter, wherein the second audio signal is coupled to the input of the second filter via the target filter, and the target filter performs a filtering processing on the second audio signal based on a desired target frequency response and outputs a filtered second audio signal to the second filter.

Alternatively or optionally, the first and second filters have identical frequency responses.

Alternatively or optionally, the first and second filters are low-pass filters.

Alternatively or optionally, the earphone further comprises: a correlation unit, which calculates a correlation between the first signal component and the second signal component, and produces a stop command by determining that the correlation is below a preset threshold； wherein the stop command is sent to the adaptive algorithm unit to stop the performing of adaptive algorithm.

Alternatively or optionally, the adaptive algorithm performed by the adaptive algorithm unit is a time-domain adaptive algorithm.

Alternatively or optionally, the microphone is mounted on the earphone between the speaker and the eardrum of the user’s ear when the earphone is worn by the user.

According to a second aspect of the present invention, a method for performing an adaptively self-tuning for an earphone is provided, and the method comprises: receiving a first audio signal to be processed； performing a pre-processing on the first audio signal to output a second audio signal； playing the second audio signal as an acoustic wave into a user’s ear； collecting the acoustic wave in the user’s ear and converting the collected signal into a third audio signal； obtaining a first signal component from at least one portion of the third audio signal, and obtaining the second signal component from at least one portion of the second audio signal which corresponds to said at least one portion of the third audio signal； and performing an adaptive algorithm on the first signal component and the second signal component to update filter coefficients for the pre-processing so as to perform the pre-processing on the first audio signal using the updated filter coefficients.

Alternatively or optionally, the pre-processing is pre-equalization.

Alternatively or optionally, the method further comprises: receiving a content audio signal from an audio source as the first audio signal.

Alternatively or optionally, the method further comprises: filtering the third audio signal to obtain the first signal component and filtering the second audio signal to obtain the second signal component, wherein the two filters have identical frequency responses.

Alternatively or optionally, the two filters with identical frequency responses are low-pass filters.

Alternatively or optionally, the method further comprises: selecting a desired target frequency response； and before filtering the second audio signal to obtain the second signal component, the method further comprising: performing filtering on the second audio signal based on the desired target frequency response.

Alternatively or optionally, the method further comprises: calculating a correlation between the first signal component and the second signal component； producing a stop command by determining that the correlation is below a preset threshold； and sending the stop command to stop the performing of adaptive algorithm.

Alternatively or optionally, the adaptive algorithm is a time-domain adaptive algorithm.

According to an embodiment of this disclosure, a new solution of pre-processing for an earphone is proposed.

Further features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments according to the present invention with reference to the attached drawings.

BRIEF DISCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description thereof, serve to explain the principles of the invention.

Fig. 1 is a schematic block diagram of an earphone according to an embodiment of this disclosure.

Fig. 2 is a schematic block diagram of an earphone according to another embodiment of this disclosure.

Fig. 3 is a schematic block diagram of an earphone according to still another embodiment of this disclosure.

Fig. 4 is a schematic flow chart of a method for performing an adaptively self-tuning for an earphone according to another embodiment of this disclosure.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Various exemplary embodiments of the present invention will now be described in detail with reference to the drawings. It should be noted that the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

Techniques, methods and apparatus as known by one of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

In all of the examples illustrated and discussed herein, any specific values should be interpreted to be illustrative only and non-limiting. Thus, other examples of the exemplary embodiments could have different values.

Notice that similar reference numerals and letters refer to similar items in the following figures, and thus once an item is defined in one figure, it is possible that it need not be further discussed for following figures.

Embodiments and examples will be described with reference to the accompanying figure.

As shown in Fig. 1, the earphone comprises: a pre-processing filter 2, a speaker 3, a microphone 4 and an adaptive algorithm unit 6.

The pre-processing filter 2 receives a first audio signal and performs a pre-processing on the first audio signal to output a second audio signal. For example, the pre-processing filter 2 is a pre-equalization filter and performs pre-equalization on the first audio signal.

For example, the first audio signal is produced in the audio source 1. Here, the first audio signal is a content audio signal from the audio source 1. The audio source 1 may be an input unit of the earphone. In an example, audio data such like musical data is stored locally in the earphone. In such a case, the audio source 1 may be a player including memory, codec and so on.

The speaker 3 receives the second audio signal and plays the second audio signal as an acoustic wave into a user’s ear. The speaker 3 may include a dynamic speaker, an electrostatic speaker and so on. Optionally, it can include a MEMS speaker.

The microphone 4 receives the acoustic wave and converts the acoustic wave into a third audio signal. The microphone 4 may include a dynamic microphone, a condenser microphone and so on. Optionally, it can include a MEMS microphone. As would be understood by a person skilled in the art under the teaching of this disclosure, the microphone 4 is mounted between the eardrum of a user and the speaker. The microphone 4 can capture the acoustic wave played inside the ear.

The adaptive algorithm unit 6 receives a first signal component and a second signal component, performs an adaptive algorithm on the first signal component and the second signal component to produce filter coefficients for the pre-processing filter 2, and sends the filter coefficients to the pre-processing filter 2.

The first signal component includes at least one portion of the third audio signal. The second signal component includes at least one portion of the second audio signal which corresponds to the at least one portion of the third audio signal. In this regard, the first and second signal component may have the same frequency range. It will be appreciated by a person skilled in the art that the term “corresponding” mean the portions correspond with each other in a certain aspect (such as frequency range) but the contents thereof may be different.

For example, according to a design demand, the first signal component may include just one portion of the third audio signal or the whole third audio signal. Accordingly, the second signal component may include just one portion of the second audio signal or the whole second audio signal. The inputs of the adaptive algorithm unit 6 can be coupled to the second and third audio signals. It would be understood by a person skilled in the art that “couple” includes a direct connection or an indirect connection, i.e. when A is coupled to B, A is connected to B directly or indirectly.

For example, the adaptive algorithm performed by the adaptive algorithm unit 6 is a time-domain adaptive algorithm. For the design of pre-processing in this disclosure, the time-domain adaption is sufficient and is much simpler than a frequency-domain adaption.

Here, a new solution of pre-processing is proposed, which can use the output of a pre-processing filter and the played acoustic wave to calculate the coefficients for the pre-processing filter. It can adaptively tune the response of the earphone constantly during a content audio signal such as a music song is being played. Furthermore, compared with the prior art, instead of using a predicted output of a speaker, the actual output of the pre-processing filter is used in this solution, which is much simpler in structure and is more efficient.

The adaptive algorithm unit 6 can receive the second and third audio signals directly, for example, as shown in Fig. 1. Alternatively, it can be coupled to the second and third audio signals via intermediate components.

Fig. 2 is a schematic block diagram of an earphone according to another embodiment of this disclosure. The components with identical reference signs can be the same as those in Fig. 1 and thus the explanation thereof will be omitted.

As shown in Fig. 2, the earphone further comprises a first filter 5 and a second filter 8. The third audio signal is coupled to the input of the first filter 5 and the first filter 5 produces the first signal component. The first signal component is sent to the adaptive algorithm unit 6. The second audio signal is coupled to the input of the second filter 8 and the second filter 8 produces the second signal component. The second signal component is sent to the adaptive algorithm unit 6.For example, the first and

second filters

5, 8 have identical frequency responses.

By using the first and

second filters

5, 8, a desired portion of the second and third audio signal can be obtained for producing coefficients for the pre-processing filter 2.

Here, the bass band performance is what is of concern as explained. So, the first and second filters are low-pass filters to obtain the first and second signal component.

In another example, the earphone further comprises a target filter 7. The second audio signal is coupled to the input of the second filter 8 via the target filter 7. The target filter 7 performs a filtering processing on the second audio signal based on a desired target frequency response and outputs a filtered second audio signal to the second filter 8.

By the target filter 7, a desired ideal response can be selected and/or controlled by a designer. For example, the ideal response is chosen by the designer and can be defined either objectively, based on literature studies, or subjectively, e.g. with the help of a Golden Ears. Optionally, a user of the earphone can choose an ideal response during playing a content. For example, a control unit (not shown) for the target filter 7 can be provided and a user can adjust the target filter 7 through the control unit during playing a content audio signal such as a music song.

The pre-processing solution in this disclosure has the ability to adaptively self-tune the response such as a bass response to an ideal response. It will provide any user with similar target sound quality regardless of his ear shape and size. The self-tuning is adapted constantly to a target curve based on the content such as a music song being played through the earphone. Even if the earphone seal changes over time, such as when a user wearing the earphone is running, the adaptation can be achieved without user interaction. This ensures that the sound quality is consistent across user’s movements regardless of the mechanical seal.

In this embodiment, filters 5, 7, 8 are separated modules relative to the adaptive algorithm unit 6. It is also understood that in other embodiments at least part of the functions of

filters

5, 7, 8 can be incorporated with the adaptive algorithm unit 6.

Fig. 3 is a schematic block diagram of an earphone according to another embodiment of this disclosure.

The components with identical reference signs can be the same as those in Fig. 1 or 2 and thus the explanation thereof will be omitted.

In the embodiment of Fig. 3, the earphone further comprises correlation unit 10.

The correlation unit 10 calculates a correlation between the first signal component and the second signal component, and produces a stop command by determining that the correlation is below a preset threshold.

In an example, the stop command is further sent to the adaptive algorithm unit 6 to stop the performing of adaptive algorithm.

In this embodiment, the adaptive algorithm for the pre-processing is controlled by determining the correlation. In such a manner, the power consumption may be saved if no content signal is input. Specifically, the correlation unit is used to stop the adaptation whenever it is determined that the signal captured by the microphone is contaminated by other sounds than the music played into the ear and reflected by the ear, which can be white noise and/or any other noise in the surroundings, such as other person’s talking nearby, or talking of the user of the earbud, coughing and so on. If the stop command from the correlation unit was not used, this would in most cases result in sudden losses of bass content, whenever the user starts talking and/or coughing, or if external noise is present. With the correlation unit, the speaker’s response stays consistent in these noisy periods.

It would be appreciated by a person skilled in the art that a normal processing of the adaptive algorithm could be performed when the correlation is above the preset threshold.

It will be understood by a person skilled in the prior art that a software is equivalent to a hardware except for some of the mechanical components such a speaker, a microphone and so on. In this regard, a person skilled in the art can conceive, under the teaching of this disclosure, that the modules except for the speaker 3 and the microphone 4 shown in Figs. 1 and 2 can be carried out through a hardware manner, a software manner and/or a combination thereof. For example, at least one of the

modules

1, 2, 5, 6, 7, 8, 9 and 10 can be carried out through discrete devices, a programmable device such PLD, DSP, FPGA. Alternatively, at least one of the

modules

1, 2, 5, 6, 7, 8, 9 and 10 can be implemented in a combination of a computing device such as a CPU or a MPU and a memory, wherein instructions are stored in the memory and are used to control the computing device to performing corresponding operations during the running of the earphone. In this regard, this disclosure will not limit the implementation manners of the modules. A person skilled in the art can choose the implementation manners under the teaching of this disclosure in consideration of the cost, the market availability and so on.

Fig. 4 is a schematic flow chart of a method for performing an adaptively self-tuning for an earphone according to another embodiment of this disclosure. The earphone may comprise a pre-processing filter, a speaker, a microphone and an adaptive algorithm unit as shown in Fig. 1, 2 or 3.

As shown in Step S1100, a first audio signal to be processed is received.

As shown in Step S1200, a pre-processing on the first audio signal is performed to output a second audio signal. For example, the pre-processing is pre-equalization.

As shown in Step S1300, the second audio signal is played as an acoustic wave into a user’s ear. For example, it is played by the microphone 4 mounted on the earphone between the eardrum of the user and the speaker when the earphone is worn by the user.

As shown in Step S1400, the acoustic wave in the user’s ear is collected and the collected signal is converted into a third audio signal.

As shown in Step S1500, a first signal component is obtained from at least one portion of the third audio signal, and a second signal component is obtained from at least one portion of the second audio signal which corresponds to said at least one portion of the third audio signal.

As shown in Step S1600, an adaptive algorithm is performed on the first signal component and the second signal component to update filter coefficients for the pre-processing so as to perform the pre-processing on the first audio signal using the updated filter coefficients. For example, the adaptive algorithm is a time-domain adaptive algorithm.

For example, the first audio signal is a content audio signal received from an audio source.

In an example, the method may further comprise: filtering the third audio signal to obtain the first signal component and filtering the second audio signal to obtain the second signal component, where both filters have an identical frequency response.

Further, this embodiment allows a user of the earphone to choose an ideal response during playing a content. For example, the method may further comprises: selecting a desired target frequency response； and before filtering the second audio signal to obtain the second signal component, the method further comprises: performing a filtering processing on the second audio signal based on a desired target frequency response.

For example, the identical frequency response may be a low-pass frequency response.

In another example, the method may further comprises: calculating a correlation between the first signal component and the second signal component； producing a stop command by determining whether the correlation is below a preset threshold； and sending the stop command to stop the performing of adaptive algorithm.

An example for an earphone will be described. The earphone can be that shown in Fig. 1, 2 or 3. For example, the earphone is an earbud.

In this example, the pre-processing filter will pre-equalizes the low-frequency component of a musical signal before it is played into a user’s ear. Initially, the pre-processing filter can be initialized to be a pass-through filter, leaving the musical signal unaltered. The acoustic wave in the user’s ear canal is captured by a microphone as a response signal. The microphone is built into the front cavity of the earphone. An adaptive algorithm can be used to continuously update the coefficients of the pre-processing filter based on the deviation between this response signal and a previously determined target signal. For example, the target signal can be acquired by passing the music signal through a target filter, which may have an ideal response defined by a designer.

Specifically, the musical signal is sent into the pre-processing filter. The pre-processing filter filters the musical signal based on the current filter coefficients. Initially, the pre-processing filter is set to be a pass-through filter, leaving the musical signal unaltered.

The output of the pre-processing filter is sent to the speaker, and then is played into a user’s ear.

The acoustic wave in the user’s ear canal is captured as a response signal by the microphone mounted in the front cavity of the earphone.

The response signal is filtered through a first filter as a first signal component, which includes only the frequency range to be adapted to. The first filter can be either a band-pass filter or a low-pass filter based on the frequency range of interest.

Simultaneously, the output of the pre-processing filter is also passed through a target filter which is based on a desired target frequency response. The target filter outputs a target signal. The target signal is filtered through a second filter. The second filter and the first filter have identical frequency responses.

Then, the adaptive algorithm unit updates the filter coefficients for the pre-processing filter and sends them back to the pre-processing filter.

The above process can be repeated during the playing of the musical signal.

Although some specific embodiments of the present invention have been demonstrated in detail with examples, it should be understood by a person skilled in the art that the above examples are only intended to be illustrative but not to limit the scope of the present invention.

Claims

An earphone, comprising:

a pre-processing filter, which receives a first audio signal and performs a pre-processing on the first audio signal to output a second audio signal；

a speaker, which receives the second audio signal and plays it as an acoustic wave into a user’s ear；

a microphone, which receives the acoustic wave and converts it into a third audio signal； and

an adaptive algorithm unit, which receives a first signal component and a second signal component, and performs an adaptive algorithm on the first signal component and the second signal component to update filter coefficients for the pre-processing filter, wherein the first signal component includes at least one portion of the third audio signal and the second signal component includes at least one portion of the second audio signal which corresponds to said at least one portion of the third audio signal.
The earphone according to claim 1, wherein the pre-processing filter is a pre-equalization filter and performs pre-equalization on the first audio signal.
The earphone according to claim 1 or 2, wherein the first audio signal is a content audio signal from an audio source.
The earphone according to claim 1 or 2, further comprising:

a first filter, wherein the third audio signal is coupled to the input of the first filter and the first filter produces the first signal component； and

a second filter, wherein the second audio signal is coupled to the input of the second filter and the second filter produces the second signal component.
The earphone according to claim 4, further comprising:

a target filter, wherein the second audio signal is coupled to the input of the second filter via the target filter, and the target filter performs a filtering processing on the second audio signal based on a desired target frequency response and outputs a filtered second audio signal to the second filter.
The earphone according to claim 4, wherein the first and second filters have identical frequency responses.
The earphone according to claim 6, wherein the first and second filters are low-pass filters.
The earphone according to claim 4, further comprising:

a correlation unit, which calculates a correlation between the first signal component and the second signal component, and produces a stop command by determining that the correlation is below a preset threshold；

wherein the stop command is sent to the adaptive algorithm unit to stop the performing of adaptive algorithm.
The earphone according to claim 1 or 2, wherein the adaptive algorithm performed by the adaptive algorithm unit is a time-domain adaptive algorithm.
The earphone according to claim 1 or 2, wherein the microphone is mounted on the earphone between an eardrum of the user and the speaker when the earphone is worn by the user.
A method an adaptively self-tuning for an earphone, and the method comprises:

receiving a first audio signal to be processed；

performing a pre-processing on the first audio signal to output a second audio signal；

playing the second audio signal as an acoustic wave into a user’s ear；

collecting the acoustic wave in the user’s ear and converting the collected signal into a third audio signal；

obtaining a first signal component from at least one portion of the third audio signal, and obtaining a second signal component from at least one portion of the second audio signal which corresponds to said at least one portion of the third audio signal； and

performing an adaptive algorithm on the first signal component and the second signal component to update filter coefficients for the pre-processing so as to perform the pre-processing on the first audio signal using the updated filter coefficients.
The method according to claim 12, wherein the pre-processing is pre-equalization.
The method according to claim 11 or 12, further comprising: receiving a content audio signal from an audio source as the first audio signal.
The method according to any of claims 11-12, further comprising:

filtering the third audio signal to obtain the first signal component and filtering the second audio signal to obtain the second signal component, wherein the two filters have identical frequency responses.
The method according to claim 14, further comprising:

selecting a desired target frequency response；

before filtering the second audio signal to obtain the second signal component, the method further comprising:

performing a filtering processing on the second audio signal based on the desired target frequency response.
The method according to claim 14, wherein the identical frequency response is a low-pass frequency response.
The method according to claim 14, further comprising:

calculating a correlation between the first signal component and the second signal component；

producing a stop command by determining that the correlation is below a preset threshold； and

sending the stop command to stop the performing of adaptive algorithm.
The method according to any of claims 11-12 wherein the adaptive algorithm is a time-domain adaptive algorithm.