Hearing assistance device, method, system, storage medium and product

Abstract

The invention discloses hearing assistance equipment, method and system, a storage medium and a product, and belongs to the technical field of hearing assistance. According to the invention, data-driven adaptive hearing aid is realized, and a user does not need to manually debug equipment parameters or switch a hearing aid mode. Wherein the capability release of the signal processing unit is controlled by a dynamic signal processing parameter envelope. The boundary of the parameter envelope is dynamically determined by confidence. In the scheme, the confidence coefficient calculation unit continuously obtains the reference data and calculates the confidence coefficient according to the reference data. Correspondingly, the parameter envelope controller can dynamically adjust the boundary of the parameter envelope according to the real-time value of the confidence coefficient, so that the current feasible parameter domain is determined. On the basis, the signal processing unit can process and output the audio signal in the feasible parameter domain, so that accurate hearing compensation is realized. According to the scheme, the operation cost of the user is reduced, the smooth transition of the hearing aid function is realized, and no function interruption exists in the whole process.

Description

Technical Field

[0001] This application relates to the field of hearing aid technology, and in particular to a hearing aid device, method, system, storage medium and product. Background Technology

[0002] Hearing assistive devices, also known as hearing aids or hearing devices, are often referred to as ear-worn devices because they are usually in the form of portable headphones. Among them, hearing assistive devices, as a type of enhanced device with hearing aid functions, are more suitable for daily wear and use for users with mild hearing loss, both in terms of product experience and cost-effectiveness.

[0003] While wearing hearing aids, users need to manually perform certain operations to optimize the hearing aid effect. For example, they need to manually adjust the device parameters or manually switch hearing aid modes. This passive operation method not only increases the user's operating cost, but the mechanical switching of hearing aid modes can also cause a lack of smooth function transition, and may even interrupt the hearing aid function during operation, seriously affecting the user's continuous use experience. Summary of the Invention

[0004] This application provides a hearing aid device, method, system, storage medium, and product. The technical solution is shown below.

[0005] On the one hand, a hearing aid device is provided, the device comprising: a signal acquisition unit, a signal processing unit, a parameter envelope controller, and a first confidence calculation unit; The signal acquisition unit is used to acquire audio signals; The first confidence calculation unit is used to acquire first reference data, calculate a first confidence level based on the first reference data, and send the first confidence level to the parameter envelope controller; the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; The parameter envelope controller is used to adjust the boundary of the signal processing parameter envelope according to the first confidence level, and send the adjusted signal processing parameter envelope to the signal processing unit; the signal processing parameter envelope is used to limit the adjustment range of each currently available signal processing parameter during hearing compensation. The signal processing unit is used to process the audio signal under the constraint of the adjusted signal processing parameter envelope, and output the processed audio signal.

[0006] In some embodiments, the parameter envelope controller is further configured to: The system receives a second confidence level sent by an external computing device, the external computing device including a second confidence level calculation unit; the second confidence level calculation unit is used to acquire second reference data and calculate the second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; Based on the fused confidence level, the boundary of the signal processing parameter envelope is adjusted, and the adjusted signal processing parameter envelope is sent to the signal processing unit.

[0007] In other embodiments, the external computing device is a smart mobile terminal or cloud server that has established a communication link with the hearing aid.

[0008] In other embodiments, the user behavior data includes real-time records of user adjustments to the signal processing parameters; the first confidence calculation unit is used for: Based on the user behavior data, the magnitude of parameter changes and the frequency of negative interaction events are determined; wherein, the magnitude of parameter changes is used to reflect the magnitude changes of signal processing parameters adjusted by the user; and the negative interaction events are related to hearing discomfort. The first confidence level is determined based on the security gating factor, the magnitude of the parameter change, and the number of occurrences of the target event.

[0009] In other embodiments, the device further includes a second confidence calculation unit; The second confidence calculation unit is used to acquire second reference data, calculate a second confidence level based on the second reference data, and send the second confidence level to the parameter envelope controller; wherein, the second reference data includes clinical validation data in the field of hearing aids; The parameter envelope controller is further configured to fuse the first confidence level and the second confidence level to obtain a fused confidence level; adjust the boundary of the signal processing parameter envelope according to the fused confidence level, and send the adjusted signal processing parameter envelope to the signal processing unit.

[0010] In other embodiments, the second confidence calculation unit is used for: Based on the clinical validation data, the standard parameter configuration of the device is determined; The second confidence level is determined based on the data quality of the clinical validation data and the degree of deviation between the standard parameter configuration and the current parameter configuration of the device.

[0011] In other embodiments, the parameter envelope controller is configured to: The first weight corresponding to the first confidence level is determined based on the number of times the user performs the interaction behavior; The data quality of the clinical validation data is used as the second weight corresponding to the second confidence level; Based on the first weight and the second weight, the first confidence level and the second confidence level are fused to obtain the instantaneous confidence level corresponding to the current moment; The fused confidence level is determined based on the instantaneous confidence level at the current moment and the historical confidence level at the historical moment.

[0012] In other embodiments, the parameter envelope controller is further configured to: Store the initially defined envelope of the signal processing parameters; A mapping function between the confidence level and the boundary of the signal processing parameter envelope is stored; wherein the confidence level and the boundary of the signal processing parameter envelope are positively correlated. Based on the initially defined signal processing parameter envelope, the boundary of the signal processing parameter envelope is expanded using the mapping function according to the fused confidence level.

[0013] In other embodiments, the parameter envelope controller is configured to perform at least one of the following: Increase the maximum acoustic gain limit without exceeding the user's hearing tolerance threshold; Increase the number of independently adjustable frequency bands; Remove restrictions on calling specific nonlinear compression algorithms.

[0014] In other embodiments, the clinical validation data includes standard pure-tone audiograms and speech audiometry data.

[0015] On the other hand, a hearing assistance method is provided, applied to the aforementioned hearing assistance device, the method comprising: Acquire audio signals; First reference data is obtained, and a first confidence level is calculated based on the first reference data; the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; Based on the first confidence level, the boundary of the signal processing parameter envelope is adjusted; the signal processing parameter envelope is used to limit the adjustment range of each currently available signal processing parameter during hearing compensation. The audio signal is processed under the constraints of the adjusted signal processing parameter envelope, and the processed audio signal is output.

[0016] In some embodiments, calculating the first confidence level based on the first reference data includes: Based on the user behavior data, the magnitude of parameter changes and the frequency of negative interaction events are determined; wherein, the magnitude of parameter changes is used to reflect the magnitude changes of signal processing parameters adjusted by the user; and the negative interaction events are related to hearing discomfort. The first confidence level is determined based on the security gating factor, the magnitude of the parameter change, and the number of occurrences of the target event.

[0017] In other embodiments, adjusting the boundary of the signal processing parameter envelope based on the first confidence level includes: The system receives a second confidence level sent by an external computing device, the external computing device including a second confidence level calculation unit; the second confidence level calculation unit is used to acquire second reference data and calculate the second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; The boundaries of the signal processing parameter envelope are adjusted based on the fused confidence level.

[0018] In other embodiments, adjusting the boundary of the signal processing parameter envelope based on the first confidence level includes: Acquire second reference data and calculate a second confidence level based on the second reference data; wherein the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; The boundaries of the signal processing parameter envelope are adjusted based on the fused confidence level.

[0019] In other embodiments, calculating the second confidence level based on the second reference data includes: Based on the clinical validation data, the standard parameter configuration of the device is determined; The second confidence level is determined based on the data quality of the clinical validation data and the degree of deviation between the standard parameter configuration and the current parameter configuration of the device.

[0020] In other embodiments, fusing the first confidence level and the second confidence level to obtain a fused confidence level includes: The first weight corresponding to the first confidence level is determined based on the number of times the user performs the interaction behavior; The data quality of the clinical validation data is used as the second weight corresponding to the second confidence level; Based on the first weight and the second weight, the first confidence level and the second confidence level are fused to obtain the instantaneous confidence level corresponding to the current moment; The fused confidence level is determined based on the instantaneous confidence level at the current moment and the historical confidence level at the historical moment.

[0021] In other embodiments, the method further includes: Store the initially defined envelope of the signal processing parameters; A mapping function between the confidence level and the boundary of the signal processing parameter envelope is stored; wherein the confidence level and the boundary of the signal processing parameter envelope are positively correlated. The step of adjusting the boundary of the signal processing parameter envelope based on the fused confidence level includes: Based on the initially defined signal processing parameter envelope, the boundary of the signal processing parameter envelope is expanded using the mapping function according to the fused confidence level.

[0022] In other embodiments, extending the boundary of the signal processing parameter envelope includes at least one of the following: Increase the maximum acoustic gain limit without exceeding the user's hearing tolerance threshold; Increase the number of independently adjustable frequency bands; Remove restrictions on calling specific nonlinear compression algorithms.

[0023] On the other hand, a hearing assistance system is provided, the system comprising: The system includes hearing aids and an external computing device; The hearing aid device is used to collect audio signals; acquire first reference data, and calculate a first confidence level based on the first reference data; wherein, the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; The external computing device is used to acquire second reference data and calculate a second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The hearing aid device is further configured to fuse the first confidence level and the second confidence level to obtain a fused confidence level; adjust the boundary of the signal processing parameter envelope based on the fused confidence level; process the audio signal under the constraint of the adjusted signal processing parameter envelope, and output the processed audio signal.

[0024] On the other hand, a hearing assistance system is provided, the system comprising: The system includes a hearing aid, which is used to perform the following operations: Acquire audio signals; A first reference data is obtained, and a first confidence level is calculated based on the first reference data; wherein, the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; Obtain second reference data and calculate a second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; Based on the fused confidence level, adjust the boundary of the signal processing parameter envelope; The audio signal is processed under the constraints of the adjusted signal processing parameter envelope, and the processed audio signal is output.

[0025] On the other hand, a computer-readable storage medium is provided, wherein computer program code is stored in the storage medium, the computer program code being loaded and executed by the processor of a hearing aid device to implement the above-described hearing aid method.

[0026] On the other hand, a computer program product is provided, the computer program product including computer program code stored in a computer-readable storage medium, a processor of a hearing aid device reading the computer program code from the computer-readable storage medium, the processor executing the computer program code, causing the hearing aid device to perform the above-described hearing aid method.

[0027] The hearing aids, methods, systems, storage media, and products provided in this application embodiment realize data-driven adaptive hearing aids, automatically optimizing hearing aid effects without requiring users to manually adjust device parameters or switch hearing aid modes. Specifically, the signal processing unit, as the core of the hearing aid device, controls its capabilities through a dynamic signal processing parameter envelope. The boundary of this parameter envelope is dynamically determined by a confidence level characterizing the reliability of the device's current parameter configuration. In this solution, the confidence level calculation unit continuously acquires reference data and calculates the confidence level accordingly. Correspondingly, the parameter envelope controller dynamically adjusts the boundary of the parameter envelope based on the real-time confidence level, thereby determining the current feasible parameter domain. Based on this, the signal processing unit can process the audio signal acquired by the signal acquisition unit within this feasible parameter domain and output the processed audio signal, achieving precise hearing compensation. This active hearing compensation mechanism not only reduces the user's operating costs but also achieves a smooth transition of hearing aid functions without interruption, ensuring a continuous user experience for hearing-impaired users. In addition, since this solution continuously acquires reference data and applies it to the hearing compensation process, it can also respond to the gradual changes in users' hearing needs over time or changes caused by different environments. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a schematic diagram of the structure of a hearing aid 110 provided in an embodiment of this application; Figure 2 This is a schematic diagram illustrating how the boundary of a signal processing parameter envelope gradually evolves with changes in confidence, as provided in an embodiment of this application. Figure 3 This is a schematic diagram of another hearing aid device 110 provided in this application embodiment; Figure 4 This is a flowchart of a hearing assistance method provided in an embodiment of this application; Figure 5 This is a flowchart of another hearing assistance method provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of a hearing assistance system 100 provided in an embodiment of this application; Figure 7 This is a schematic diagram of another hearing assistance system 100 provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of a terminal 800 provided in an embodiment of this application; Figure 9 This is a schematic diagram of the structure of a cloud server 900 provided in an embodiment of this application. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0031] In this application, the terms "first," "second," etc., are used to distinguish identical or similar items that have essentially the same function. It should be understood that there is no logical or temporal dependency between "first," "second," and "nth," nor does it limit the quantity or execution order. It should also be understood that although the following description uses the terms "first," "second," etc., to describe various elements, these elements should not be limited by the terms.

[0032] These terms are simply used to distinguish one element from another. For example, without departing from the various examples, the first element can be referred to as the second element, and similarly, the second element can be referred to as the first element. Both the first and second elements can be elements, and in some cases, they can be separate and distinct elements.

[0033] "At least one" refers to one or more elements. For example, at least one element can be one element, two elements, three elements, or any integer number of elements greater than or equal to one. "Multiple" refers to two or more elements. For example, multiple elements can be two elements, three elements, or any integer number of elements greater than or equal to two.

[0034] In this article, "and / or" indicates that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0035] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant regions.

[0036] In related technologies, hearing aids (such as ear-worn devices with hearing enhancement functions) are typically designed based on a static "mode division." Some devices are manufactured in a limited, over-the-counter mode, while others are fitted through a professional fitting process to a prescription mode with specific parameter configurations. That is, the over-the-counter mode requires no professional fitting and provides only basic hearing enhancement, meeting simple hearing compensation needs—essentially a "basic" model. The prescription mode, on the other hand, requires professional fitting and parameter adjustments to be tailored to the user's specific hearing loss problem—essentially a "customized" model.

[0037] Furthermore, while related technologies attempt to integrate both modes simultaneously on a single hardware platform, their implementation mechanisms generally rely on mechanized "binary state switching." That is, the mode switching method is highly mechanical, requiring external authorization commands, specific physical operations, or software triggers to explicitly switch between "basic" and "customized" modes. In other words, although hearing aids that support both over-the-counter and prescription modes are currently available, hearing-impaired users still need to manually trigger specific operations (such as physical button presses or clicking on app function entries) to switch between the two modes.

[0038] However, this technical architecture based on discrete state switching has the following significant drawbacks: First, it lacks dynamic adaptability. That is, it cannot respond to the gradual changes in users' hearing needs over time. To elaborate, users' hearing needs are not static. For example, some users' hearing loss may gradually worsen, while others may have increasingly higher expectations for the effectiveness of their hearing aids as they use the device. However, the over-the-counter and prescription modes of existing devices are either pre-set at the factory or during fitting, and do not automatically adjust based on user data. Therefore, the devices cannot become increasingly suitable with continued use.

[0039] Secondly, the hearing aid experience is interrupted. The transition from the "basic" to the "customized" model requires explicit external intervention, disrupting the user's natural usage process. This passive approach not only increases the user's operational costs but also causes temporary malfunctions of the hearing aid function during the process, affecting the user's continuous experience.

[0040] Third, the failure to fully utilize the data generated during device operation and the failure to effectively leverage the powerful computing capabilities of external computing platforms (such as smart mobile terminals or cloud servers) for complex hearing status assessments limit the evolution of hearing aids. In other words, hearing aids cannot achieve functional upgrades through data and computing power, and their potential is completely limited.

[0041] In summary, the embodiments of this application provide a data-driven progressive adaptive hearing assistance solution. This solution, through a data-driven approach, enables hearing assistance devices to evolve continuously, autonomously, and intelligently from "basic hearing compensation capability" to "deep hearing compensation capability," without causing a break in the user's hearing assistance experience, and effectively utilizing the data generated during device operation.

[0042] In detail, this solution abandons the discrete mode-switching architecture of related technologies and instead adopts a single dynamic evolution architecture. In the embodiments of this application, the operation of the hearing aid is no longer limited to a preset fixed mode. The hearing aid possesses a potentially full-capacity signal processing unit (also known as the signal processing core), whose current actual processing capability is controlled by a dynamically adjusted signal processing parameter envelope. The boundary of this envelope is not determined by an external switch, but dynamically by the system confidence level.

[0043] To accurately and efficiently calculate this metric, this application introduces a data acquisition and confidence assessment engine that can be flexibly deployed locally or distributed between the device and the cloud. That is, the architecture can be deployed entirely locally on the device to meet low power consumption and offline usage requirements, or distributed between the earpiece and external computing devices to meet high performance and in-depth analysis requirements. By coordinating the real-time data processing capabilities on the device side and the in-depth analysis capabilities on the cloud side, this solution can more accurately assess the confidence level of the device's current parameter configuration, thereby driving a smooth and continuous evolution of the signal processing parameter envelope.

[0044] In other words, through a data acquisition and confidence assessment engine, this solution continuously acquires reference data streams (such as user behavior data, acoustic characteristics of the current environment, or clinical validation data), and calculates a system confidence level based on these data streams to reflect the reliability of the device's current parameter configuration. It's important to note that as the system confidence level accumulates and increases, the boundary of the signal processing parameter envelope automatically and continuously expands outward, enabling a smooth evolution of the device from basic safety assistance to professional and precise compensation. This mechanism ensures that the device's capabilities are entirely determined by a data-driven confidence assessment mechanism. Furthermore, this solution supports both edge-cloud collaborative computing modes and independent edge computing modes, providing users with a continuous and personalized hearing aid experience.

[0045] In summary, the embodiments of this application provide a hearing assistance scheme that abandons discrete operation mode and can continuously optimize itself and autonomously expand signal processing capabilities based on multi-source reference data by utilizing local and / or external computing resources. This scheme provides a data-driven progressive adaptive hearing assistance device, method, and system. The embodiments of this application will be described in detail below through the following implementation methods.

[0046] Figure 1 This is a schematic diagram of the structure of a hearing aid 110 provided in an embodiment of this application. See also... Figure 1 The hearing aid 110 includes: a signal acquisition unit 111, a signal processing unit 112, a parameter envelope controller 113, and a first confidence calculation unit 114.

[0047] The signal acquisition unit 111, also known as the acoustic front end, is used to acquire audio signals and convert the acquired audio signals into digital signals before inputting them into the signal processing unit 112.

[0048] The hearing aid device 110 incorporates a signal processing unit 112 with full hearing compensation potential. The signal processing unit 112 executes signal processing algorithms on the digital signals transmitted by the signal acquisition unit 111 to achieve hearing compensation. Exemplarily, the signal processing algorithms include, but are not limited to, multi-channel dynamic range compression, noise reduction algorithms based on deep neural networks, etc., and this application does not limit them.

[0049] In this embodiment, a dynamically adjustable signal processing parameter envelope is defined to limit the adjustment range of each available signal processing parameter during hearing compensation. Initially, the signal processing parameter envelope is in an initial convergence state, limiting the signal processing unit 112 to operate only within a preset safety range. In other words, the actual operating parameters of the signal processing unit 112 are not fixed but are controlled by the parameter envelope controller 113. The parameter envelope controller 113 is used to define the parameter operating boundaries of the signal processing unit 112, and it stores and manages the aforementioned signal processing parameter envelope.

[0050] For example, the signal processing parameter envelope described above is used to limit the threshold values ​​of core parameters that are allowed to be used at the current moment, including maximum acoustic gain, maximum sound pressure level, compression inflection point, number of independently adjustable frequency bands, etc., which are not limited in this application.

[0051] It should be noted that the core control logic of this solution lies in the data ingestion and confidence assessment engine.

[0052] In this embodiment, the data ingestion and confidence assessment engine continuously acquires a reference data stream and uses computing resources to evaluate the acquired reference data stream to calculate and update the system confidence score. The system confidence score characterizes the degree to which the device's current parameter configuration matches the user's hearing needs.

[0053] As an example, such as Figure 1As shown, the engine employs a distributed architecture, including a first confidence calculation unit (also known as an end-side assessment unit) 114 located inside the hearing aid device 110 and a second confidence calculation unit 121 located in an external computing device 120.

[0054] Furthermore, the external computing device 120 can be either a smart mobile terminal that has established a communication link with the hearing aid device 110, or a cloud server that has established a communication link with the hearing aid device 110; this application does not limit this. Therefore, the second confidence calculation unit 121 can be either an edge-side evaluation unit or a cloud-side evaluation unit.

[0055] As an example, the aforementioned reference data stream includes, but is not limited to, the following types of data: user behavior data (from the hearing aid device 110), acoustic characteristics of the current environment (from the hearing aid device 110), and clinical validation data (from external input). This application does not limit the scope of such data. In addition, the aforementioned reference data stream may also include long-term data, such as complex soundscape adaptation data recorded by the device over a long period of time. This application does not limit the scope of such data.

[0056] The user behavior data reflects the real-time interactive behavior performed by the user on the hearing aid device 110. For example, the user behavior data includes real-time adjustment records of signal processing parameters, such as real-time fine-tuning records of device gain (including acoustic gain) or frequency response parameters; this application does not limit this. Additionally, clinical validation data includes, but is not limited to, standard pure-tone audiograms and speech audiometry data; this application also does not limit this.

[0057] In this embodiment, the step of calculating and updating the system confidence level is executed using a distributed computing architecture. Specifically, the first confidence level calculation unit 114 is used to calculate and update the first confidence level (also referred to as the basic confidence level component) in real time, and the second confidence level calculation unit 121 is used to calculate and update the second confidence level (also referred to as the advanced confidence level component). The calculation process of the system confidence level is described in detail below.

[0058] First, we will introduce the calculation process of the basic confidence component.

[0059] In this embodiment of the application, the first confidence calculation unit 114 uses local computing resources to calculate the first confidence based on the first reference data and sends the first confidence to the parameter envelope controller 113.

[0060] The first reference data refers to data in the reference data stream that has high real-time requirements. In other words, the first confidence calculation unit 114 is responsible for processing "fast data" with high frequency and low latency requirements, and calculating the basic confidence component accordingly to assess whether the current parameter configuration of the device is suitable for the user's hearing needs in the short term. That is, the basic confidence component is a quantitative indicator used to assess whether the current parameter configuration of the device is reasonable and stable. For example, the first reference data includes at least one of user behavior data or acoustic characteristics of the current environment, which is not limited in this application.

[0061] In some embodiments, the first confidence calculation unit 114 is used to continuously calculate and update the basic confidence components in real time in the following manner.

[0062] 1. Based on user behavior data, the parameter change amplitude A is determined using the following formula 1. Here, the parameter change amplitude A reflects the amplitude change of the signal processing parameters adjusted by the user, and may reflect the frequency or drasticness of parameter adjustments made by the user over a period of time.

[0063] Formula 1:

[0064] Where W refers to the time sliding window, and t refers to any time within the time sliding window. This refers to the user-adjusted parameters at time t. This refers to the user-adjusted parameters at time t. It refers to time t and t The norm of the parameter at time 1 represents the magnitude of a single parameter adjustment.

[0065] 2. Based on user behavior data, obtain the number of occurrences n of negative interaction events. neg .

[0066] Among these, negative interactive events are related to hearing discomfort, such as users repeatedly adjusting parameters, volume, or removing the device; this application does not limit this to such events. Additionally, n neg The larger the value, the more uncomfortable the user feels about the current parameter configuration of the device, that is, the less reasonable the current parameter configuration is.

[0067] 3. Based on security gating factors The magnitude of parameter change A and the number of times the target event occurs n neg The first confidence level is determined by the following formula 2.

[0068] Formula 2:

[0069] in, This refers to the baseline confidence component; and This is the adjustment coefficient; When parameter adjustments may exceed safety boundaries, the safety gating factor... This will lower the confidence level and avoid the risk of hearing loss caused by parameter adjustments.

[0070] For example, when a user repeatedly fine-tunes the volume or noise reduction level in a specific noisy environment, the first confidence calculation unit 114 captures this statistically consistent behavior, calculates a baseline confidence component, and sends the calculated baseline confidence component to the parameter envelope controller 113 in real time. This enables the device to respond quickly to the user's immediate feedback, making small adjustments to the parameter envelope and providing the user with real-time auditory optimization.

[0071] The calculation process of the advanced confidence component will be introduced next.

[0072] In this embodiment, the second confidence calculation unit 121, located in the external computing device 120, calculates a second confidence level based on the second reference data and sends the second confidence level to the parameter envelope controller 113. The second reference data refers to data in the reference data stream that has high computing power requirements or requires external database verification. In other words, the second confidence calculation unit 121 is responsible for processing "slow data" with low frequency and high computing power requirements, and calculates a high-level confidence component accordingly to evaluate the reliability and consistency of the device's current parameter configuration at the professional fitting and long-term use levels. That is, the high-level confidence component is a quantitative indicator used to evaluate whether the device's current parameter configuration is reliable and consistent at the professional fitting and long-term use levels.

[0073] In some embodiments, the second confidence calculation unit 121 is used to calculate and update the advanced confidence component in the following manner.

[0074] 1. Based on clinical validation data, determine the standard parameter configuration of the device (in the hearing compensation scenario) and determine the degree of deviation between the standard parameter configuration and the current parameter configuration of the device.

[0075] Taking the standard parameter configuration as the target gain curve obtained based on the standard pure tone audiometry test chart, and the current parameter configuration of the device as the gain curve currently used by the device, the degree of deviation between the two is determined by the following formula 3.

[0076] Formula 3:

[0077] Where f refers to frequency; This refers to the weighting of different frequencies (for example, for users with severe high-frequency hearing loss, high frequencies have a higher weighting). It refers to the target gain curve obtained based on the standard pure-tone audiogram; This refers to the gain curve currently used by the equipment. The larger the value of E, the greater the difference between the current parameter configuration of the equipment and the ideal parameters after professional fitting, and the lower the rationality.

[0078] 2. Data quality based on clinical validation data The degree of deviation E between the standard parameter configuration and the current parameter configuration of the equipment is used to determine the second confidence level.

[0079] in, Used to measure the target gain curve The reliability of the corresponding clinical validation data (such as standard pure-tone audiograms), including whether the data was collected by a professional institution and whether it is up-to-date. Higher data quality... The closer the value is to 1.

[0080] As an example, based on data quality The degree of bias E is determined by the following formula 4 to establish the second confidence level.

[0081] Formula 4:

[0082] in, This refers to the high-confidence component; This is the adjustment coefficient.

[0083] For example, a user uploads a standard pure-tone audiogram or long-term data through an application used with the hearing aid 110. This uploaded data is then transmitted to an external computing device 120. Accordingly, the second confidence calculation unit 121 utilizes its more powerful computing capabilities and available external database resources to perform in-depth analysis and verification of this data, thereby calculating a high-level confidence component and transmitting it to the parameter envelope controller 113.

[0084] Next, we will introduce the fusion process of the basic confidence component and the high-level confidence component.

[0085] In this embodiment, the parameter envelope controller 113 receives the high-level confidence component and fuses it with the basic confidence component to obtain the system confidence, i.e., the fused confidence.

[0086] System confidence score is used to comprehensively characterize the overall degree of match between the current device's parameter configuration and the user's hearing needs. System confidence score is a comprehensive indicator that integrates basic confidence score and advanced confidence score. Its function is to uniformly measure whether the current parameter configuration of the device is suitable for the user's actual hearing needs from two dimensions: real-time experience and professional standards. This is to achieve both taking into account the user's current usage experience and meeting long-term professional compensation standards.

[0087] In some embodiments, the parameter envelope controller 113 is used to fuse the base confidence component and the high confidence component in the following manner.

[0088] 1. Based on the number of times the user performs an interaction, determine the first weight R corresponding to the first confidence level using the following formula 5. b .

[0089] Formula 5:

[0090] in, The adjustment coefficient, N, refers to the number of times the user performs the interactive action. For example, N could be the number of times the user has recently adjusted the parameters, but this application does not limit this.

[0091] 2. Improve the data quality of clinical validation data. The second weight R corresponding to the second confidence level a .

[0092] 3. Based on the first weight R b Second weight R a The first confidence level and the second confidence level are fused using the following formula 6 to obtain the instantaneous confidence level corresponding to the current moment.

[0093] Formula 6:

[0094] in, It is an integer with a very small value. It refers to the instantaneous confidence level at the current time t.

[0095] 4. Based on the instantaneous confidence level at the current moment and the historical confidence level at the historical moment, the fused confidence level is determined using the following formula 7.

[0096] Formula 7:

[0097] in, It refers to the historical confidence level corresponding to a historical moment, such as the system confidence level at the previous moment; This is a smoothing coefficient, with a value between 0 and 1. This step helps prevent drastic changes in the metric due to single data fluctuations, resulting in more stable output.

[0098] In this embodiment, the system confidence level is the final decision basis for the parameter envelope controller 113 to dynamically adjust the signal processing parameter envelope. Specifically, the parameter envelope controller 113 adjusts the boundary of the signal processing parameter envelope based on the fused confidence level and sends the adjusted signal processing parameter envelope to the signal processing unit 112. Correspondingly, the signal processing unit 112 processes the digital audio signal output by the signal acquisition unit 111 under the constraint of the adjusted signal processing parameter envelope and outputs the processed audio signal.

[0099] It should be noted that the parameter envelope controller 113 is also used to store the initially defined signal processing parameter envelope, and to store the mapping function between the confidence level and the boundary of the signal processing parameter envelope. Accordingly, the parameter envelope controller 113 is used to expand the boundary of the signal processing parameter envelope based on the initially defined signal processing parameter envelope and according to the fused confidence level through the mapping function between the two.

[0100] in, Figure 2 This is a schematic diagram illustrating the gradual evolution of the boundary of a signal processing parameter envelope as confidence level changes, according to an embodiment of this application. Figure 2 As shown, the confidence level is positively correlated with the boundary of the signal processing parameter envelope, and the boundary of the signal processing parameter envelope is a continuous function of the confidence level.

[0101] See Figure 2 In the initial state (corresponding to stage one), due to a lack of sufficient data support, the confidence level is low. The parameter envelope controller 113 limits the signal processing parameter envelope to a narrow range that conforms to basic safety specifications (e.g., limiting the maximum peak gain to below 25 dB) to ensure user safety. In other words, in the initial state, the signal processing parameter envelope is in a basic convergent state, limiting the signal processing unit 112 to operate only within a preset safety range. With user use and data accumulation, especially when externally validated clinical data is received, the confidence level significantly increases. As the confidence level accumulates, the parameter envelope controller 113 autonomously and continuously expands the boundaries of the signal processing parameter envelope, thereby gradually releasing the hearing compensation capability of the signal processing unit 112. That is, according to... Figure 2 The positive correlation mapping shown smoothly or abruptly expands the boundary of the signal processing parameter envelope (corresponding to stage two and stage three).

[0102] In some embodiments, the parameter envelope controller 113 is configured to perform at least one of the following to extend the boundaries of the signal processing parameter envelope: Increase the maximum acoustic gain limit without exceeding the user's hearing tolerance threshold; Increase the number of independently adjustable frequency bands; Remove restrictions on calling specific nonlinear compression algorithms.

[0103] In summary, the hearing aid device provided in this application embodiment achieves data-driven adaptive hearing assistance, automatically optimizing the hearing aid effect without requiring users to manually adjust device parameters or switch hearing aid modes. Specifically, the signal processing unit, as the core of the hearing aid device, controls its capabilities through a dynamic signal processing parameter envelope. The boundary of this parameter envelope is dynamically determined by a confidence level characterizing the reliability of the device's current parameter configuration. In this solution, the confidence level calculation unit continuously acquires reference data and calculates the confidence level accordingly. Correspondingly, the parameter envelope controller dynamically adjusts the boundary of the parameter envelope based on the real-time confidence level, thereby determining the current feasible parameter domain. Based on this, the signal processing unit can process the audio signal acquired by the signal acquisition unit within this feasible parameter domain and output the processed audio signal, achieving precise hearing compensation. This proactive hearing compensation mechanism not only reduces the user's operating costs but also achieves a smooth transition of hearing aid functionality without any functional interruption, ensuring a continuous user experience for hearing-impaired users.

[0104] Furthermore, because this solution continuously acquires reference data and applies it to the hearing compensation process, it can also respond to gradual changes in users' hearing needs over time or changes due to different environments. Additionally, by employing a distributed computing architecture to calculate and update the system confidence level, the computational burden on hearing aids is reduced.

[0105] Furthermore, in this scheme, since the confidence level and the boundary of the signal processing parameters are positively correlated, the parameter envelope controller will autonomously and continuously expand the boundary of the signal processing parameter envelope as the confidence level accumulates, thereby achieving a gradual release of the hearing compensation capability of the signal processing unit. It should be noted that the entire adjustment process is completed based on a single dynamic evolution architecture, without discrete hearing aid mode switching operations. The improvement of the device's hearing compensation capability is entirely dominated by a data-driven confidence assessment mechanism, enabling a continuous and smooth transition from basic hearing aids to professional hearing compensation.

[0106] Figure 3 This is a schematic diagram of another hearing aid device provided in an embodiment of this application. See also... Figure 3 The device includes: a signal acquisition unit 111, a signal processing unit 112, a parameter envelope controller 113, a first confidence calculation unit 114, and a second confidence unit 115.

[0107] In this embodiment, the signal acquisition unit 111 is used to acquire audio signals; the first confidence calculation unit 114 is used to acquire first reference data, calculate a first confidence level based on the first reference data, and send a second confidence level to the parameter envelope controller 113; the second confidence unit 115 is used to acquire second reference data, calculate a second confidence level based on the second reference data, and send the second confidence level to the parameter envelope controller 113; the parameter envelope controller 113 is used to fuse the first confidence level and the second confidence level to obtain a fused confidence level; adjust the boundary of the signal processing parameter envelope according to the fused confidence level, and send the adjusted signal processing parameter envelope to the signal processing unit 112; the signal processing unit 112 is used to process the acquired audio signals under the constraints of the adjusted signal processing parameter envelope, and output the processed audio signals.

[0108] It should be noted that for the introduction of each of the above units, please refer to... Figure 1 The corresponding implementation examples will not be described in detail here.

[0109] In summary, the hearing aid device provided in this application embodiment achieves data-driven adaptive hearing assistance, automatically optimizing the hearing aid effect without requiring users to manually adjust device parameters or switch hearing aid modes. Specifically, the signal processing unit, as the core of the hearing aid device, controls its capabilities through a dynamic signal processing parameter envelope. The boundary of this parameter envelope is dynamically determined by a confidence level characterizing the reliability of the device's current parameter configuration. In this solution, the confidence level calculation unit continuously acquires reference data and calculates the confidence level accordingly. Correspondingly, the parameter envelope controller dynamically adjusts the boundary of the parameter envelope based on the real-time confidence level, thereby determining the current feasible parameter domain. Based on this, the signal processing unit can process the audio signal acquired by the signal acquisition unit within this feasible parameter domain and output the processed audio signal, achieving precise hearing compensation. This proactive hearing compensation mechanism not only reduces the user's operating costs but also achieves a smooth transition of hearing aid functionality without any functional interruption, ensuring a continuous user experience for hearing-impaired users.

[0110] Furthermore, because this solution continuously acquires reference data and applies it to the hearing compensation process, it can also respond to gradual changes in users' hearing needs over time or changes due to different environments. Additionally, by independently calculating and updating the system confidence level on the device side, data processing efficiency is improved.

[0111] Furthermore, in this scheme, since the confidence level and the boundary of the signal processing parameters are positively correlated, the parameter envelope controller will autonomously and continuously expand the boundary of the signal processing parameter envelope as the confidence level accumulates, thereby achieving a gradual release of the hearing compensation capability of the signal processing unit. It should be noted that the entire adjustment process is completed based on a single dynamic evolution architecture, without discrete hearing aid mode switching operations. The improvement of the device's hearing compensation capability is entirely dominated by a data-driven confidence assessment mechanism, enabling a continuous and smooth transition from basic hearing aids to professional hearing compensation.

[0112] It should be noted that the hearing aid device provided in the above embodiments is only illustrated by the division of the above functional modules when providing hearing assistance. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0113] Figure 4 This is a flowchart of a hearing assistance method provided in an embodiment of this application. This method is applied to, for example... Figure 1 The hearing aid shown. See also Figure 4 The method includes the following steps.

[0114] 401. Hearing aids collect audio signals.

[0115] This step can be referred to in the previous description of the signal acquisition unit, and will not be repeated here.

[0116] 402. The hearing aid device acquires first reference data and calculates a first confidence level based on the first reference data.

[0117] For example, the first reference data includes at least one of user behavior data or acoustic characteristics of the current environment, wherein the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device.

[0118] In some embodiments, calculating a first confidence level based on first reference data includes: Based on user behavior data, the magnitude of parameter changes and the frequency of negative interaction events were determined; among them, the magnitude of parameter changes was used to reflect the magnitude changes of signal processing parameters adjusted by the user; negative interaction events were related to hearing discomfort. The first confidence level is determined based on the security gating factor, the magnitude of parameter changes, and the frequency of occurrence of the target event.

[0119] 403. A hearing aid device receives a second confidence level sent by an external computing device; wherein the external computing device includes a second confidence level calculation unit, which is used to acquire second reference data and calculate the second confidence level based on the second reference data.

[0120] For example, the second reference data includes clinical validation data in the field of hearing aids.

[0121] In some embodiments, the second confidence calculation unit of the external computing device calculates the second confidence level based on the second reference data in the following manner: Based on clinical validation data, the standard parameter configuration of the device is determined; based on the data quality of the clinical validation data and the degree of deviation between the standard parameter configuration and the current parameter configuration of the device, the second confidence level is determined.

[0122] 404. The hearing aid device fuses the first confidence level and the second confidence level to obtain the fused confidence level.

[0123] In some embodiments, the first confidence level and the second confidence level are fused to obtain a fused confidence level, including: The first weight corresponding to the first confidence level is determined based on the number of times the user performs an interaction. The quality of clinical validation data is used as the second weight corresponding to the second confidence level; Based on the first weight and the second weight, the first confidence level and the second confidence level are fused to obtain the instantaneous confidence level corresponding to the current moment; The confidence level after fusion is determined based on the instantaneous confidence level at the current moment and the historical confidence level at historical moments.

[0124] 405. Hearing aids adjust the boundaries of the signal processing parameter envelope based on the fused confidence level.

[0125] The signal processing parameter envelope is used to limit the adjustment range of each available signal processing parameter during hearing compensation. Furthermore, the range of allowed values ​​for the parameters defined by the adjusted signal processing parameter envelope corresponds to... Figure 2 The feasible parameter range is shown. In other words, the feasible parameter range is the range of parameters that the signal processing unit 112 can currently use safely and effectively; it is the actual usable interval obtained after dynamically adjusting the envelope of the signal processing parameters.

[0126] In some embodiments, the method further includes: Store the initially defined envelope of signal processing parameters; Store the mapping function between the confidence level and the boundary of the signal processing parameter envelope; wherein the confidence level and the boundary of the signal processing parameter envelope are positively correlated.

[0127] Accordingly, the boundary of the signal processing parameter envelope is adjusted based on the fused confidence level, including: based on the initially defined signal processing parameter envelope, the boundary of the signal processing parameter envelope is expanded using a mapping function according to the fused confidence level.

[0128] In other embodiments, extending the boundary of the signal processing parameter envelope includes at least one of the following: Increase the maximum acoustic gain limit without exceeding the user's hearing tolerance threshold; Increase the number of independently adjustable frequency bands; Remove restrictions on calling specific nonlinear compression algorithms.

[0129] 406. Under the constraints of the adjusted signal processing parameter envelope, the hearing aid device processes the acquired audio signal and outputs the processed audio signal.

[0130] This step can be referred to in the previous description of the signal processing unit, and will not be repeated here.

[0131] It should be noted that all the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0132] In summary, the hearing assistance method provided in this application embodiment achieves data-driven adaptive hearing assistance, automatically optimizing the hearing aid effect without requiring users to manually adjust device parameters or switch hearing aid modes. Specifically, the signal processing unit, as the core of the hearing assistance device, controls its capabilities through a dynamic signal processing parameter envelope. The boundary of this parameter envelope is dynamically determined by the confidence level, which characterizes the reliability of the device's current parameter configuration. In this solution, the confidence level calculation unit continuously acquires reference data and calculates the confidence level accordingly. Correspondingly, the parameter envelope controller dynamically adjusts the boundary of the parameter envelope based on the real-time confidence level, thereby determining the current feasible parameter domain. Based on this, the signal processing unit can process the audio signal acquired by the signal acquisition unit within this feasible parameter domain and output the processed audio signal, achieving precise hearing compensation. This proactive hearing compensation mechanism not only reduces the user's operating costs but also achieves a smooth transition of hearing aid functionality without any functional interruption, ensuring a continuous user experience for hearing-impaired users.

[0133] Furthermore, because this solution continuously acquires reference data and applies it to the hearing compensation process, it can also respond to gradual changes in users' hearing needs over time or changes due to different environments. Additionally, by employing a distributed computing architecture to calculate and update the system confidence level, the computational burden on hearing aids is reduced.

[0134] Furthermore, in this scheme, since the confidence level and the boundary of the signal processing parameters are positively correlated, the parameter envelope controller will autonomously and continuously expand the boundary of the signal processing parameter envelope as the confidence level accumulates, thereby achieving a gradual release of the hearing compensation capability of the signal processing unit. It should be noted that the entire adjustment process is completed based on a single dynamic evolution architecture, without discrete hearing aid mode switching operations. The improvement of the device's hearing compensation capability is entirely dominated by a data-driven confidence assessment mechanism, enabling a continuous and smooth transition from basic hearing aids to professional hearing compensation.

[0135] Figure 5 This is a flowchart of a hearing assistance method provided in an embodiment of this application. This method is applied to, for example... Figure 2 The hearing aid shown. See also Figure 5 The method includes the following steps.

[0136] 501. Hearing aids collect audio signals.

[0137] This step can be referred to in the previous description of the signal acquisition unit, and will not be repeated here.

[0138] 502. The hearing aid device acquires first reference data and calculates a first confidence level based on the first reference data.

[0139] This step can be referred to in the previous description of the first confidence calculation unit, and will not be repeated here.

[0140] 503. The hearing aid device acquires second reference data and calculates a second confidence level based on the second reference data.

[0141] This step can be referred to in the previous description of the first confidence calculation unit, and will not be repeated here.

[0142] 504. The hearing aid device fuses the first confidence level and the second confidence level to obtain the fused confidence level.

[0143] This step can be referred to in the previous description of the parameter envelope controller, and will not be repeated here.

[0144] 505. Hearing aids adjust the boundaries of the signal processing parameter envelope based on the fused confidence level.

[0145] This step can be referred to in the previous description of the parameter envelope controller, and will not be repeated here.

[0146] 506. Under the constraints of the adjusted signal processing parameter envelope, the hearing aid device processes the acquired audio signal and outputs the processed audio signal.

[0147] This step can be referred to in the previous description of the signal processing unit, and will not be repeated here.

[0148] In summary, the hearing assistance method provided in this application embodiment achieves data-driven adaptive hearing assistance, automatically optimizing the hearing aid effect without requiring users to manually adjust device parameters or switch hearing aid modes. Specifically, the signal processing unit, as the core of the hearing assistance device, controls its capabilities through a dynamic signal processing parameter envelope. The boundary of this parameter envelope is dynamically determined by the confidence level, which characterizes the reliability of the device's current parameter configuration. In this solution, the confidence level calculation unit continuously acquires reference data and calculates the confidence level accordingly. Correspondingly, the parameter envelope controller dynamically adjusts the boundary of the parameter envelope based on the real-time confidence level, thereby determining the current feasible parameter domain. Based on this, the signal processing unit can process the audio signal acquired by the signal acquisition unit within this feasible parameter domain and output the processed audio signal, achieving precise hearing compensation. This proactive hearing compensation mechanism not only reduces the user's operating costs but also achieves a smooth transition of hearing aid functionality without any functional interruption, ensuring a continuous user experience for hearing-impaired users.

[0149] Furthermore, because this solution continuously acquires reference data and applies it to the hearing compensation process, it can also respond to gradual changes in users' hearing needs over time or changes due to different environments. Additionally, by independently calculating and updating the system confidence level on the device side, data processing efficiency is improved.

[0150] Furthermore, in this scheme, since the confidence level and the boundary of the signal processing parameters are positively correlated, the parameter envelope controller will autonomously and continuously expand the boundary of the signal processing parameter envelope as the confidence level accumulates, thereby achieving a gradual release of the hearing compensation capability of the signal processing unit. It should be noted that the entire adjustment process is completed based on a single dynamic evolution architecture, without discrete hearing aid mode switching operations. The improvement of the device's hearing compensation capability is entirely dominated by a data-driven confidence assessment mechanism, enabling a continuous and smooth transition from basic hearing aids to professional hearing compensation.

[0151] Figure 6 This is a schematic diagram of the structure of a hearing aid system provided in an embodiment of this application. See also... Figure 6 The system includes a hearing aid 110 and an external computing device 120.

[0152] The hearing aid device 110 is used to collect audio signals; acquire first reference data, and calculate a first confidence level based on the first reference data; wherein the first reference data includes at least one of user behavior data or acoustic characteristics of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; An external computing device 120 is used to acquire second reference data and calculate a second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The hearing aid device 110 is also used to fuse the first confidence level and the second confidence level to obtain the fused confidence level; adjust the boundary of the signal processing parameter envelope according to the fused confidence level; process the acquired audio signal under the constraint of the adjusted signal processing parameter envelope, and output the processed audio signal.

[0153] The hearing assistance system provided in this application embodiment realizes data-driven adaptive hearing assistance, automatically optimizing the hearing aid effect without requiring users to manually adjust device parameters or manually switch hearing aid modes. Specifically, the signal processing unit, as the core of the hearing assistance device, has its capabilities controlled by a dynamic signal processing parameter envelope. The boundary of this parameter envelope is dynamically determined by a confidence level characterizing the reliability of the device's current parameter configuration. In this solution, the confidence level calculation unit continuously acquires reference data and calculates the confidence level accordingly. Correspondingly, the parameter envelope controller dynamically adjusts the boundary of the parameter envelope based on the real-time confidence level value, thereby determining the current feasible parameter domain. Based on this, the signal processing unit can process the audio signal acquired by the signal acquisition unit within this feasible parameter domain and output the processed audio signal, achieving precise hearing compensation. This active hearing compensation mechanism not only reduces the user's operating costs but also achieves a smooth transition of hearing aid function without any functional interruption, ensuring a continuous user experience for hearing-impaired users.

[0154] Furthermore, because this solution continuously acquires reference data and applies it to the hearing compensation process, it can also respond to gradual changes in users' hearing needs over time or changes due to different environments. Additionally, by employing a distributed computing architecture to calculate and update the system confidence level, the computational burden on hearing aids is reduced.

[0155] Furthermore, in this scheme, since the confidence level and the boundary of the signal processing parameters are positively correlated, the parameter envelope controller will autonomously and continuously expand the boundary of the signal processing parameter envelope as the confidence level accumulates, thereby achieving a gradual release of the hearing compensation capability of the signal processing unit. It should be noted that the entire adjustment process is completed based on a single dynamic evolution architecture, without discrete hearing aid mode switching operations. The improvement of the device's hearing compensation capability is entirely dominated by a data-driven confidence assessment mechanism, enabling a continuous and smooth transition from basic hearing aids to professional hearing compensation.

[0156] Figure 7 This is a schematic diagram of another hearing aid system provided in an embodiment of this application. See also... Figure 7 The system includes a hearing aid device 110. In this embodiment, the hearing aid device 110 is used to perform the following operations: Acquire audio signals; Acquire first reference data and calculate a first confidence level based on the first reference data; wherein, the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; Obtain second reference data and calculate a second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; Adjust the boundaries of the signal processing parameter envelope based on the fused confidence level; Under the constraints of the adjusted signal processing parameter envelope, the acquired audio signal is processed and the processed audio signal is output.

[0157] The hearing assistance system provided in this application embodiment realizes data-driven adaptive hearing assistance, automatically optimizing the hearing aid effect without requiring users to manually adjust device parameters or manually switch hearing aid modes. Specifically, the signal processing unit, as the core of the hearing assistance device, has its capabilities controlled by a dynamic signal processing parameter envelope. The boundary of this parameter envelope is dynamically determined by a confidence level characterizing the reliability of the device's current parameter configuration. In this solution, the confidence level calculation unit continuously acquires reference data and calculates the confidence level accordingly. Correspondingly, the parameter envelope controller dynamically adjusts the boundary of the parameter envelope based on the real-time confidence level value, thereby determining the current feasible parameter domain. Based on this, the signal processing unit can process the audio signal acquired by the signal acquisition unit within this feasible parameter domain and output the processed audio signal, achieving precise hearing compensation. This active hearing compensation mechanism not only reduces the user's operating costs but also achieves a smooth transition of hearing aid function without any functional interruption, ensuring a continuous user experience for hearing-impaired users.

[0158] Furthermore, because this solution continuously acquires reference data and applies it to the hearing compensation process, it can also respond to gradual changes in users' hearing needs over time or changes due to different environments. Additionally, by independently calculating and updating the system confidence level on the device side, data processing efficiency is improved.

[0159] Furthermore, in this scheme, since the confidence level and the boundary of the signal processing parameters are positively correlated, the parameter envelope controller will autonomously and continuously expand the boundary of the signal processing parameter envelope as the confidence level accumulates, thereby achieving a gradual release of the hearing compensation capability of the signal processing unit. It should be noted that the entire adjustment process is completed based on a single dynamic evolution architecture, without discrete hearing aid mode switching operations. The improvement of the device's hearing compensation capability is entirely dominated by a data-driven confidence assessment mechanism, enabling a continuous and smooth transition from basic hearing aids to professional hearing compensation.

[0160] Taking an external computing device as an example of a smart mobile terminal, Figure 8 This is a schematic diagram of the structure of a terminal 800 provided in an embodiment of this application.

[0161] Typically, terminal 800 includes a processor 801 and a memory 802.

[0162] Processor 801 includes one or more processing cores, such as a quad-core processor or an octa-core processor. Processor 801 is implemented using at least one of the following hardware forms: DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Alternatively, processor 801 includes a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state.

[0163] In some embodiments, the processor 801 integrates a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content that the display screen needs to show.

[0164] In some embodiments, processor 801 further includes an AI (Artificial Intelligence) processor for processing computational operations related to machine learning.

[0165] The memory 802 includes one or more computer-readable storage media that are non-transitory. The memory 802 also includes high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices.

[0166] In some embodiments, the non-transitory computer-readable storage medium in memory 802 is used to store computer program code, which is executed by processor 801 to implement the method steps performed by an external computing device in the hearing assistance method provided in this application embodiment.

[0167] In some embodiments, the terminal 800 further includes a peripheral device interface 803 and at least one peripheral device. The processor 801, memory 802, and peripheral device interface 803 are connected via a bus or signal line. Each peripheral device is connected to the peripheral device interface 803 via a bus, signal line, or circuit board. The peripheral device includes at least one of a radio frequency circuit 804, a display screen 805, a camera assembly 806, an audio circuit 807, and a power supply 808.

[0168] Peripheral device interface 803 is used to connect at least one I / O (Input / Output) related peripheral device to processor 801 and memory 802. In some embodiments, processor 801, memory 802, and peripheral device interface 803 are integrated on the same chip or circuit board. In other embodiments, any one or two of processor 801, memory 802, and peripheral device interface 803 are implemented on separate chips or circuit boards, which is not limited in this application.

[0169] The radio frequency (RF) circuit 804 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 804 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 804 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. In some embodiments, the RF circuit 804 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 804 communicates with other terminals via at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 804 also includes circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0170] Display screen 805 is used to display a UI (User Interface). This UI includes graphics, text, icons, videos, and any combination thereof. When display screen 805 is a touch display, it also has the ability to collect touch signals on or above its surface. These touch signals are input as control signals to processor 801 for processing. In this case, display screen 805 also provides virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there is one display screen 805, disposed on the front panel of terminal 800; in other embodiments, there are at least two display screens 805, disposed on different surfaces of terminal 800 or in a folded design. In other embodiments, display screen 805 is a flexible display screen, disposed on a curved or folded surface of terminal 800. Alternatively, display screen 805 may be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. Display screen 805 is made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0171] The camera assembly 806 is used to acquire images or videos. In some embodiments, the camera assembly 806 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the terminal, and the rear-facing camera is located on the back of the terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In other embodiments, the camera assembly 806 also includes a flash. The flash is a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm-light flash and a cool-light flash, used for light compensation at different color temperatures.

[0172] The audio circuit 807 includes a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting them into electrical signals that are input to the processor 801 for processing, or to the radio frequency circuit 804 for voice communication. Multiple microphones are used for stereo sound acquisition or noise reduction, each located at a different part of the terminal 800. Alternatively, the microphones may be array microphones or omnidirectional microphones. The speaker is used to convert electrical signals from the processor 801 or the radio frequency circuit 804 into sound waves. The speaker may be a conventional thin-film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 807 also includes a headphone jack.

[0173] Power supply 808 is used to power the various components in terminal 800. Power supply 808 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. If power supply 808 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is charged via a wired line, while a wireless rechargeable battery is charged via a wireless coil. The rechargeable battery also supports fast charging technology.

[0174] Those skilled in the art will understand that Figure 8 The structure shown does not constitute a limitation on terminal 800 and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0175] Taking cloud servers as an example of external computing devices, Figure 9 This is a schematic diagram of a cloud server structure provided in an embodiment of this application. The cloud server 900 can vary significantly due to differences in configuration or performance, including one or more Central Processing Units (CPUs) 901 and one or more memories 902. The memories 902 store computer program code, which is loaded and executed by the processors 901 to implement the method steps performed by the external computing device in the aforementioned hearing assistance method. Of course, the cloud server 900 may also include other components for implementing its functions, which will not be elaborated upon here.

[0176] In some embodiments, this application also provides a computer-readable storage medium, such as a memory including computer program code, which can be executed by a processor in a hearing aid device to perform the aforementioned hearing aid method. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0177] In some embodiments, this application also provides a computer program product, which includes computer program code stored in a computer-readable storage medium. The processor of the hearing aid device reads the computer program code from the computer-readable storage medium and executes the computer program code, causing the hearing aid device to perform the above-described hearing aid method.

[0178] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0179] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A hearing aid, characterized in that, The device includes: a signal acquisition unit, a signal processing unit, a parameter envelope controller, and a first confidence calculation unit; The signal acquisition unit is used to acquire audio signals; The first confidence calculation unit is used to acquire first reference data, calculate a first confidence level based on the first reference data, and send the first confidence level to the parameter envelope controller; the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; The parameter envelope controller is used to adjust the boundary of the signal processing parameter envelope according to the first confidence level, and send the adjusted signal processing parameter envelope to the signal processing unit; the signal processing parameter envelope is used to limit the adjustment range of each currently available signal processing parameter during hearing compensation. The signal processing unit is used to process the audio signal under the constraint of the adjusted signal processing parameter envelope, and output the processed audio signal.

2. The device according to claim 1, characterized in that, The parameter envelope controller is also used for: The system receives a second confidence level sent by an external computing device, the external computing device including a second confidence level calculation unit; the second confidence level calculation unit is used to acquire second reference data and calculate the second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; Based on the fused confidence level, the boundary of the signal processing parameter envelope is adjusted, and the adjusted signal processing parameter envelope is sent to the signal processing unit.

3. The device according to claim 2, wherein the external computing device is a smart mobile terminal or cloud server that has established a communication link with the hearing aid device.

4. The device according to claim 1, characterized in that, The user behavior data includes real-time records of user adjustments to the signal processing parameters; the first confidence calculation unit is used for: Based on the user behavior data, the magnitude of parameter changes and the frequency of negative interaction events are determined; wherein, the magnitude of parameter changes is used to reflect the magnitude changes of signal processing parameters adjusted by the user; and the negative interaction events are related to hearing discomfort. The first confidence level is determined based on the security gating factor, the magnitude of the parameter change, and the number of occurrences of the target event.

5. The device according to claim 1, characterized in that, The device also includes a second confidence calculation unit; The second confidence calculation unit is used to acquire second reference data, calculate a second confidence level based on the second reference data, and send the second confidence level to the parameter envelope controller; wherein, the second reference data includes clinical validation data in the field of hearing aids; The parameter envelope controller is further configured to fuse the first confidence level and the second confidence level to obtain a fused confidence level; adjust the boundary of the signal processing parameter envelope according to the fused confidence level, and send the adjusted signal processing parameter envelope to the signal processing unit.

6. The device according to claim 5, characterized in that, The second confidence calculation unit is used for: Based on the clinical validation data, the standard parameter configuration of the device is determined; The second confidence level is determined based on the data quality of the clinical validation data and the degree of deviation between the standard parameter configuration and the current parameter configuration of the device.

7. The device according to claim 5, characterized in that, The parameter envelope controller is used for: The first weight corresponding to the first confidence level is determined based on the number of times the user performs the interaction behavior; The data quality of the clinical validation data is used as the second weight corresponding to the second confidence level; Based on the first weight and the second weight, the first confidence level and the second confidence level are fused to obtain the instantaneous confidence level corresponding to the current moment; The fused confidence level is determined based on the instantaneous confidence level at the current moment and the historical confidence level at the historical moment.

8. The device according to claim 2 or 5, characterized in that, The parameter envelope controller is also used for: Store the initially defined envelope of the signal processing parameters; A mapping function between the confidence level and the boundary of the signal processing parameter envelope is stored; wherein the confidence level and the boundary of the signal processing parameter envelope are positively correlated. Based on the initially defined signal processing parameter envelope, the boundary of the signal processing parameter envelope is expanded using the mapping function according to the fused confidence level.

9. The device according to claim 8, characterized in that, The parameter envelope controller is configured to perform at least one of the following: Increase the maximum acoustic gain limit without exceeding the user's hearing tolerance threshold; Increase the number of independently adjustable frequency bands; Remove restrictions on calling specific nonlinear compression algorithms.

10. The device according to claim 2 or 5, characterized in that, The clinical validation data included standard pure-tone audiograms and speech audiometry data.

11. A hearing aid method, characterized in that, The method, applied to any one of the hearing aids as described in claims 1 to 10, comprises: Acquire audio signals; First reference data is obtained, and a first confidence level is calculated based on the first reference data; the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; Based on the first confidence level, the boundary of the signal processing parameter envelope is adjusted; the signal processing parameter envelope is used to limit the adjustment range of each currently available signal processing parameter during hearing compensation. The audio signal is processed under the constraints of the adjusted signal processing parameter envelope, and the processed audio signal is output.

12. The method according to claim 11, characterized in that, The calculation of the first confidence level based on the first reference data includes: Based on the user behavior data, the magnitude of parameter changes and the frequency of negative interaction events are determined; wherein, the magnitude of parameter changes is used to reflect the magnitude changes of signal processing parameters adjusted by the user; and the negative interaction events are related to hearing discomfort. The first confidence level is determined based on the security gating factor, the magnitude of the parameter change, and the number of occurrences of the target event.

13. The method according to claim 11, characterized in that, The step of adjusting the boundary of the signal processing parameter envelope based on the first confidence level includes: The system receives a second confidence level sent by an external computing device, the external computing device including a second confidence level calculation unit; the second confidence level calculation unit is used to acquire second reference data and calculate the second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; The boundaries of the signal processing parameter envelope are adjusted based on the fused confidence level.

14. The method according to claim 11, characterized in that, The step of adjusting the boundary of the signal processing parameter envelope based on the first confidence level includes: Acquire second reference data and calculate a second confidence level based on the second reference data; wherein the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; The boundaries of the signal processing parameter envelope are adjusted based on the fused confidence level.

15. The method according to claim 14, characterized in that, The calculation of the second confidence level based on the second reference data includes: Based on the clinical validation data, the standard parameter configuration of the device is determined; The second confidence level is determined based on the data quality of the clinical validation data and the degree of deviation between the standard parameter configuration and the current parameter configuration of the device.

16. The method according to claim 14, characterized in that, The process of fusing the first confidence level and the second confidence level to obtain the fused confidence level includes: The first weight corresponding to the first confidence level is determined based on the number of times the user performs the interaction behavior; The data quality of the clinical validation data is used as the second weight corresponding to the second confidence level; Based on the first weight and the second weight, the first confidence level and the second confidence level are fused to obtain the instantaneous confidence level corresponding to the current moment; The fused confidence level is determined based on the instantaneous confidence level at the current moment and the historical confidence level at the historical moment.

17. The method according to claim 13 or 14, characterized in that, The method further includes: Store the initially defined envelope of the signal processing parameters; A mapping function between the confidence level and the boundary of the signal processing parameter envelope is stored; wherein the confidence level and the boundary of the signal processing parameter envelope are positively correlated. The step of adjusting the boundary of the signal processing parameter envelope based on the fused confidence level includes: Based on the initially defined signal processing parameter envelope, the boundary of the signal processing parameter envelope is expanded using the mapping function according to the fused confidence level.

18. The method according to claim 17, characterized in that, The extension of the boundary of the signal processing parameter envelope includes at least one of the following: Increase the maximum acoustic gain limit without exceeding the user's hearing tolerance threshold; Increase the number of independently adjustable frequency bands; Remove restrictions on calling specific nonlinear compression algorithms.

19. A hearing aid system, characterized in that, The system includes hearing aids and an external computing device; The hearing aid device is used to collect audio signals; acquire first reference data, and calculate a first confidence level based on the first reference data; wherein, the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; The external computing device is used to acquire second reference data and calculate a second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The hearing aid device is further configured to fuse the first confidence level and the second confidence level to obtain a fused confidence level; adjust the boundary of the signal processing parameter envelope based on the fused confidence level; process the audio signal under the constraint of the adjusted signal processing parameter envelope, and output the processed audio signal.

20. A hearing aid system, characterized in that, The system includes a hearing aid device, which is used to perform the following operations: Acquire audio signals; A first reference data is obtained, and a first confidence level is calculated based on the first reference data; wherein, the first reference data includes at least one of user behavior data or acoustic features of the current environment; the user behavior data is used to reflect the interactive behavior performed by the user on the hearing aid device; Obtain second reference data and calculate a second confidence level based on the second reference data; wherein, the second reference data includes clinical validation data in the field of hearing aids; The first confidence level and the second confidence level are fused to obtain the fused confidence level; Based on the fused confidence level, adjust the boundary of the signal processing parameter envelope; The audio signal is processed under the constraints of the adjusted signal processing parameter envelope, and the processed audio signal is output.

21. A computer-readable storage medium, characterized in that, The storage medium stores computer program code, which is loaded and executed by the processor of the hearing aid device to implement the hearing aid method as described in any one of claims 11 to 18.

22. A computer program product, characterized in that, The computer program product includes computer program code stored in a computer-readable storage medium. The processor of the hearing aid device reads the computer program code from the computer-readable storage medium and executes the computer program code, causing the hearing aid device to perform the hearing aid method as described in any one of claims 11 to 18.

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