METHOD, HEARING SYSTEM AND COMPUTER READABLE MEDIUM FOR IDENTIFYING AN INTERFERENCE EFFECT

Abstract

A method is specified for identifying an interference effect. The hearing system includes a hearing device, which is worn by a user for sound output to the user. The hearing system is configured to recurrently receive a report from the user such that an interference effect is present in the sound output. If the user reports an interference effect in a present situation, multiple features of the present situation are ascertained and stored as a feature set. An identification unit compares multiple stored feature sets to one another and ascertains those features which correspond in the multiple feature sets and which are then assumed as characteristic features of the interference effect, so that the identification unit identifies the interference effect on the basis of the characteristic features.

Claims

1. A method for identifying an interference effect, which comprises the steps of: providing a hearing system having a hearing device, the hearing device being worn by a user for outputting sound to the user, wherein the hearing system being configured to recurrently receive a report from the user when the interference effect is present in the sound output; ascertaining and storing multiple features of a present situation as a feature set, if the user reports the interference effect in the present situation; and comparing, via an identification unit, multiple stored feature sets to one another and ascertaining the features which correspond in the multiple feature sets and which are then assumed as characteristic features of the interference effect, so that the identification unit identifies the interference effect on a basis of the characteristic features.

2. The method according to claim 1, wherein the identification unit is pretrained using previously known associations of the interference effects with the characteristic features.

3. The method according to claim 1, wherein: the identification unit is pretrained using training data, which contain real training data and artificial training data; the real training data are previously known associations of previously known features with the interference effects; and the artificial training data are generated starting from the real training data in that new features, which are associated with a same said interference effect, are generated from the previously known features for a respective interference effect by modification within a tolerance range.

4. The method according to claim 1, wherein a measure against the interference effect first takes place when a specific minimum number of reports for the interference effect exists.

5. The method according to claim 1, wherein the interference effect is only identified until a specific maximum number of reports is reached for the interference effect.

6. The method according to claim 1, wherein: to differentiate various said interference effects, the feature set is categorized and associated with a group, so that a group of feature sets is associated with each said interference effect; and during an ascertainment of corresponding features, only the feature sets of a single group are compared to one another.

7. The method according to claim 6, wherein a respective feature set of the features sets is automatically categorized in that it is compared to the stored feature sets and associated with the group which contains a most similar feature set thereto.

8. The method according to claim 5, wherein a respective feature set of the feature sets is categorized in that it is inquired of the user whether an associated interference effect has already previously been reported, and in that furthermore the respective feature set is associated with the group having a most similar feature set thereto, if the associated interference effect has already been previously reported, and otherwise with a new group.

9. The method according to claim 1, wherein a setting for the hearing device is ascertained on a basis of the characteristic features, which reduces the interference effect, and which is then set automatically or proposed to the user.

10. The method according to claim 1, wherein the feature sets are collected in a central database, for centralized evaluation and respective association with the interference effect.

11. The method according to claim 1, wherein at least one of the features is an operating parameter of the hearing device in the present situation.

12. The method according to claim 1, wherein at least one of the features is a surroundings parameter, which is measured using a sensor of the hearing system in the present situation.

13. A hearing system for identifying an interference effect, comprising: a hearing device being worn by a user for outputting sound to the user, wherein the hearing system being configured to recurrently receive a report from the user when the interference effect is present in the sound output; and an identification unit; the hearing system programmed to: ascertain and store multiple features of a present situation as a feature set if the user reports the interference effect in the present situation; and compare, via said identification unit, multiple stored feature sets to one another and ascertaining the features which correspond in the multiple feature sets and which are then assumed as characteristic features of the interference effect, so that said identification unit identifies the interference effect on a basis of the characteristic features.

14. A non-transitory computer readable medium having computer executable instructions for automatically executing a method for identifying an interference effect after an installation of a hearing system having a hearing device, the hearing device being worn by a user for outputting sound to the user, wherein the hearing system being configured to recurrently receive a report from the user when an interference effect is present in the sound output, which comprises the steps of: ascertaining and storing multiple features of a present situation as a feature set, if the user reports the interference effect in the present situation; and comparing, via an identification unit, multiple stored feature sets to one another and ascertaining the features which correspond in the multiple feature sets and which are then assumed as characteristic features of the interference effect, so that the identification unit identifies the interference effect on a basis of the characteristic features.

Description

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

[0041] FIG. 1 is an illustration showing a hearing system according to the invention; and

[0042] FIG. 2 is a flow diagram for illustrating a method.

DETAILED DESCRIPTION OF THE INVENTION

[0043] Referring now to the figures of the drawings in detail and first, particularly to FIG. 1 thereof, there is shown an exemplary embodiment of a hearing system 2 according to the invention. The hearing system 2 includes a hearing device 4, which is worn by a user (not explicitly shown) for sound output to the user. An interference effect possibly occurs during the sound output. A flow chart of an exemplary method for identifying the interference effect is shown in FIG. 2. A core concept here is that the interference effect is identified by a simple report M by the user, without requiring a more precise description or characterization of the interference effect from this user. In the identification, features F of a situation are ascertained in which the user perceives the interference effect, without the user having to describe the interference effect in detail.

[0044] The hearing device 4 shown includes at least one microphone 6, which records sound from the surroundings and generates an electrical input signal. This is supplied for modification to a signal processing unit 8 of the hearing device 4. The signal processing unit 8 is a part of a control unit 10 of the hearing device 4. The hearing device 4 shown is used to care for a hearing-impaired user. The modification is performed for this purpose on the basis of an individual audiogram of the user, which is associated with the hearing device 4, so that an individual hearing deficit of the user is compensated for. The signal processing unit 8 outputs as a result an electrical output signal, which is then converted back into sound via a receiver 12 of the hearing device 2 and is output to the user. The hearing device 4 shown is a binaural hearing device 4, having two individual devices 14, which each include at least one microphone 6 and one receiver 12 and which are worn by the user on different sides of the head, namely once on or in the left ear and once on or in the right ear.

[0045] The method is generally used for operating a hearing system 2, for example, as shown in FIG. 1, and is especially a method for identification of an interference effect. The interference effect is generally an effect audible to the user during the sound output by the hearing device 4. Due to the interference effect, this sound output is perceived by the user in a manner which is subjectively nonoptimal, faulty, inadequate, incorrect, or otherwise deficient.

[0046] The hearing system 2 is configured to recurrently receive a report M from the user such that an interference effect is present in the sound output. The interference effect does not have to be known to the user, rather it is sufficient in the present case that solely the presence of an interference effect can be reported. To receive a report M from the user, i.e., accept it, the hearing system 2 includes an input element 16 here, e.g., a switch, a button, or a microphone for speech input. As shown in FIG. 1, the input element 16 is, for example, a part of the hearing device 4 or a part of an auxiliary device 18 of the hearing system 2. The auxiliary device 18 shown as an example in FIG. 1 is a mobile terminal, especially a smart phone here. By actuating the input element 16, a report M can be generated, which is accepted by the hearing system 2 in a first step S1 of the method, as is recognizable in FIG. 2.

[0047] If the user reports an interference effect in a present situation, multiple features F of the present situation are ascertained by the hearing system 2 in first step S1 and stored as a feature set G. The present situation is the situation which exists at a given time and is characterized by features F of the surroundings and/or the hearing system 2. Such features F are, for example, parameters or properties of the surroundings or the hearing system 2.

[0048] As soon as the hearing system 2 receives a report M, multiple features F of the present situation are stored and form a feature set G, of which it is known on the basis of the report M that an interference effect exists for this feature set G. The features F describe the situation in the chronological and spatial vicinity of the report M, i.e., the features F characterize the surroundings and/or the hearing system 2 at the time of the report M or in a time window around the time of the report M and in hearing range of the user or within a space in which the user is located.

[0049] An identification unit 20 of the hearing system 2 now compares multiple stored feature sets G to one another and ascertains in a second step S2 of the method those features F which correspond in the multiple feature sets G and which are then assumed as characteristic features C of the interference effect, so that the identification unit 20 identifies the interference effect on the basis of the characteristic features C. Multiple reports M of the user are evaluated here, so that it is thus ascertained on the basis of recurring reports M which features F are present recurrently and are thus characteristic for the interference effect, which is identified in this way. In the context of the method, multiple reports M are accordingly typically accepted by the hearing system 2. The two steps S1 and S2 are repeated for each report M. Because the user recurrently reports the interference effect, the characteristic features C are ascertained more and more precisely with time, so that an identification of the interference effect on the basis of the characteristic features C is possible and also becomes more and more accurate with further reports M, without the user having to characterize the interference effect themselves in any way.

[0050] An ascertainment of the characteristic features C for the purpose of identification of the interference effect is carried out automatically by the identification unit 20. The identification unit 20 determines, for example, with which probability a respective one of multiple predefined, i.e., previously known interference effects is present, i.e., which interference effect underlies a respective report M with which probability. The probabilities for a single report M then form a probability set. A respective probability set is also referred to as an error definition, since it specifies which interference effect is probably present and thus defines it by way of the individual probabilities. Each report M thus generates a data pair made up of a feature set G and a probability set. These data pairs are collected by the hearing system 2 and the identification unit 20 ascertains therefrom, also in the second step S2, the most probable interference effect, so that it is identified. For example, upon each report M, the probabilities are simply added to each previously known interference effect and then the interference effect is identified as the one of the previously known interference effects which has the highest probability. In another suitable embodiment, upon each report, a counter for the one of the previously known interference effects is simply increased which has the highest probability and then the interference effect is identified as the one of the previously known interference effects which has the highest counter.

[0051] The identification unit 20 is a part of the hearing device 2 or a part of an auxiliary device 18 of the hearing system 2 or is distributed thereon. The auxiliary device 18 is, for example, the mobile terminal shown in FIG. 1 or, as explicitly shown here, a server 22, which is connected via a network for data exchange to the hearing device 4 and/or a mobile terminal of the hearing system 2, the auxiliary device 18 here.

[0052] The identification unit 20 is a type of intelligent classifier for interference effects. Features F are supplied as input parameters to the identification unit 20 and the identification unit 20 then outputs an interference effect as the output parameter. In the exemplary embodiment shown, the identification unit 20 is an artificial intelligence and includes for this purpose, for example, a neural network or a cluster analysis unit. The features F of a respective feature set G are then input parameters for the identification unit 20 and the identified interference effect is an output parameter of the identification unit 20. The identification unit 20 shown here is pretrained using previously known associations of interference effects with characteristic features C. This takes place beforehand by means of a pretraining, which is not necessarily a part of the method described here. The associations are, for example, training data, which were generated beforehand to train the identification unit 20.

[0053] It is fundamentally conceivable that the identification of the interference effect is not possible or is not uniquely possible, i.e., does not have a unique result, but rather multiple interference effects come into consideration. In the present case, the method is therefore run through multiple times, for example until a specific probability is reached for one of multiple possible interference effects. In the present case, a measure against the interference effect in step S3 only takes place when a specific minimum number Amin of reports M is present for this interference effect. In addition, in the present case the interference effect is only identified until a specific maximum number Amax of reports M is reached for this interference effect and then each further report M is ignored. Instead, the user is notified to contact a technician to identify and/or remedy the interference effect.

[0054] Optionally, to differentiate various interference effects, a respective feature set G is categorized and associated with a group for this purpose, so that a group of feature sets G is associated with each interference effect. Only the feature sets G of a single group are then compared to one another upon the ascertainment of corresponding features F. The method shown in FIG. 2 shows only one group and then is carried out more or less multiple times in parallel for multiple groups for each of multiple interference effects, so that multiple different interference effects can be identified. A categorization of the feature sets G takes place, with the goal of grouping the feature sets G into groups, which each at least probably characterize the same interference effect. The feature sets G are associated, for example, on the basis of their similarity to one another with various groups, so that similar feature sets G are associated with the same group, since they probably characterize the same interference effect, and different feature sets G are associated with different groups, since they probably characterize different interference effects.

[0055] The categorization is carried out automatically by the hearing system and/or manually by the user. For example, a respective feature set G is automatically characterized in that it is compared to already stored feature sets G and associated with the group which contains the most similar feature set G thereto. A manual categorization is performed, for example, in that it is inquired of the user at the time of the report M or later whether the associated interference effect has already previously been reported, and in that furthermore the respective feature set G is associated with the group having the most similar feature set G thereto, if the associated interference effect has already been previously reported, and otherwise with a new group.

[0056] On the basis of the characteristic features C, in the present case in step S3, a setting for the hearing device 4 is ascertained as a measure in reaction to the interference effect, which reduces the associated interference effect, and which is then also automatically set or proposed to the user in the present case in step S3. Since the interference effect is now identified on the basis of the characteristic features C, a setting is looked up in a corresponding database 24 for this interference effect or calculated on the basis of a computing rule, for example.

[0057] The feature sets G are collected in the present case in a central database 26, for centralized evaluation and respective association with an interference effect. In the present case, the feature sets G of multiple hearing systems 2 are collected in the database 26 and thus combined for joint evaluation. The settings are then transmitted from the database 26 to a respective hearing system 2 or requested thereby to react accordingly upon identification of a specific interference effect.

[0058] The following is a summary list of reference numerals and the corresponding structure used in the above description of the invention: [0059] 2 hearing system [0060] 4 hearing device [0061] 6 microphone [0062] 8 signal processing unit [0063] 10 control unit [0064] 12 receiver [0065] 14 individual device [0066] 16 input element [0067] 18 auxiliary device [0068] 20 identification unit [0069] 22 server [0070] 24 database [0071] 26 central database [0072] Amax maximum number [0073] Amin minimum number [0074] C characteristic feature [0075] F feature [0076] G feature set [0077] M report [0078] S1 first step [0079] S2 second step [0080] S3 third step