EP1523219A2 - Procédé pour l'apprentissage et le fonctionnement d'une prothèse auditive et prothèse auditive correspondente - Google Patents

Procédé pour l'apprentissage et le fonctionnement d'une prothèse auditive et prothèse auditive correspondente Download PDF

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Publication number
EP1523219A2
EP1523219A2 EP04022104A EP04022104A EP1523219A2 EP 1523219 A2 EP1523219 A2 EP 1523219A2 EP 04022104 A EP04022104 A EP 04022104A EP 04022104 A EP04022104 A EP 04022104A EP 1523219 A2 EP1523219 A2 EP 1523219A2
Authority
EP
European Patent Office
Prior art keywords
hearing aid
input signal
situation
hearing
acoustic input
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
EP04022104A
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German (de)
English (en)
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EP1523219B1 (fr
EP1523219A3 (fr
Inventor
Matthias Dr. Fröhlich
Thomas Dr. Hies
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Sivantos GmbH
Original Assignee
Siemens Audiologische Technik GmbH
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Application filed by Siemens Audiologische Technik GmbH filed Critical Siemens Audiologische Technik GmbH
Publication of EP1523219A2 publication Critical patent/EP1523219A2/fr
Publication of EP1523219A3 publication Critical patent/EP1523219A3/fr
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Publication of EP1523219B1 publication Critical patent/EP1523219B1/fr
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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/50—Customised settings for obtaining desired overall acoustical characteristics
    • H04R25/505—Customised settings for obtaining desired overall acoustical characteristics using digital signal processing
    • H04R25/507—Customised settings for obtaining desired overall acoustical characteristics using digital signal processing implemented by neural network or fuzzy logic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2225/00—Details of deaf aids covered by H04R25/00, not provided for in any of its subgroups
    • H04R2225/41—Detection or adaptation of hearing aid parameters or programs to listening situation, e.g. pub, forest

Definitions

  • the present invention relates to a method for exercising at night a hearing aid by providing an acoustic Input signal, providing a plurality of listening situation identifiers and assigning the acoustic input signal to a the Hörsituationskenneptungen by a hearing aid wearer. Moreover, the present invention relates to a corresponding Hearing aid, which is nachtrainierbar, and a method for operating such a hearing aid after a Retraining.
  • Classifiers are found in hearing aids for detecting different Situations use.
  • the default parameters for the appropriate situations in an individual hearing aid wearer not necessarily be optimal.
  • the detection rate regarding the individual framework conditions are increased. This is especially true for the situation of the performance of the own voice of great importance.
  • the classifier on certain noise situations typical of the acoustic environment of the hearing aid wearer are optimally adjusted become.
  • the document EP 0 681 411 A1 a programmable hearing aid known that independently adapts to changing environmental situations.
  • the hearing aid parameters be continuously connected to the present Ambient noise adjusted, with "blurred” inputs from Hearing aid wearers in addition to the measured input signals can be used.
  • the objective here is the parameters to optimize directly, taking into account the listening situation is not explicitly stated.
  • the document EP 0 814 634 A1 further describes a method described with which the hearing aid wearer the hearing aid optimally adjusts itself by a caused by the hearing aid wearer Night training is performed.
  • the hearing aid wearer gets a lot of predefined parameter sets for that one Listening situation, which he tells the hearing aid to choose from. Out this limited set of parameter sets, each one Hearing aid preset, it selects the one he feels as optimal for himself.
  • the appropriate hearing aid setting is learned from a set of rules, so that for a similar acoustic input signal, the same hearing aid setting he follows. This means that the rules a picture of the acoustic input variables on the optimal Hearing aid parameter set.
  • the object of the present invention is therefore to the night training of a hearing aid for the hearing aid wearer Simplify and operate the hearing aid accordingly improve.
  • this object is achieved by a method for training a hearing aid by providing a Acoustic input signal, providing multiple Hörsituationskennache and assigning the acoustic input signal to one of the Hörsituationskennache by a hearing aid wearer as well as automatic learning of the assignment of the acoustic Input signal to the one of the Hörsituationskennache.
  • the invention provides a hearing aid with a Recording device for recording an acoustic input signal, a memory device for storing a plurality of Listening situation identifiers and an input device for assigning the acoustic input signal to one of the Hörsituationskennonne by a hearing aid wearer and a learning device to automatically learn the assignment of the acoustic Input signal to the one of the Hörsituationskennonne through the input device.
  • the above object is achieved by a method for operating a hearing aid by receiving a hearing aid acoustic input signal, automatic assignment of a a hearing situation characterizing Hörsituationskennung to the acoustic input signal and automatic setting of the Hearing aid as a function of Hörsituationskennung.
  • the invention is based on the knowledge that for the hearing aid wearer although the differentiation between different Parameter sets is difficult, whereas calling a acoustic situation that is currently occurring, e.g. For example, the situation "own voice” or “entertainment in the car", in the Most cases very reliable by the hearing aid wearer is possible. These situations go beyond the conventional ones Hearing aids used hearing situations such as “speech at rest” and “speech in noise”. Ie. the more differentiated Listening situations can turn on for signal processing relevant aspects of these "classic” situations Respectively.
  • the acoustic representations that this novel, may be based on more diverse situations simple manner individually trained by specific naming become.
  • the sound of your own Voice or the specific sound of your own car from the hearing aid for example, be learned by a neural network.
  • the neural network thus takes in contrast to the mentioned Prior art according to EP 0 813 634 A1 an illustration the acoustic input variables do not affect the resulting Overall setting (parameter set) of the hearing aid, but on the internal situation representation (hearing situation identification) in front. This will then be based on audiological Expert knowledge of the hearing aid parameter set to be used derived or the relevant parameters varied and / or supplemented. In particular, the adaptive algorithms reuse this information without the hearing aid wearer evaluate the result.
  • a specific embodiment according to the invention can one of the listening situations of the performance of one 's own voice Hearing aid wearer, so after the automatic Learning your own voice can be recognized. This is in many situations, for example, for the directional microphone setting of great importance.
  • the automatic learning of the at least one Hörellaeinstellparameters for the assigned listening situation on the Basis of automatic evaluation can be during (online) or after (offline) the presentation of the acoustic input signal respectively.
  • online night training the acoustic Input signal can not be completely saved, however
  • the hearing aid requires more computing power to the night training perform. There is no need for offline night training this additional computing needs in the hearing aid, however, is a Memory device for the acoustic input signal needed.
  • the online evaluation avoids the time-consuming reading, Processing and reprogramming the data or the Hearing aid.
  • the input device for assigning the acoustic input signal An auditory situation can also be used to start and stop of the night training. This will be the Handling the hearing aid or carrying out the night training simplified for the hearing aid wearer.
  • the input device may consist of one in the Hearing aid integrated receiver and an external remote control consist.
  • the remote control can be for wired or wireless be designed wireless communication with the hearing aid. It is also conceivable that the remote control exclusively is used for the night training of the hearing aid. alternative can the remote control as a multifunction device, for example as a mobile phone or portable computer with radio interface speed, be designed.
  • the input device may also include a programmable arithmetic unit, in particular, include a PC, so that the operation via an appropriate programming software.
  • a programmable arithmetic unit in particular, include a PC, so that the operation via an appropriate programming software.
  • the input device at a special Embodiment verbal and in particular by means of one or several keywords be operable. This will be the operation the hearing aid for the hearing aid wearer even more comfortable designed.
  • the acoustic input signal can be a manual or automatically processed speech signal. That's it possible to train the classifier very specific.
  • a parameter of the parameter set is varied by the automatic assignment and / or supplemented. This makes it possible for that acoustic input signal of a complex signal processing is subjected based on expert knowledge when the neural Net a learned hearing situation, z. B. your own Voice, recognizes. This is the currently used in the hearing aid Parameter set modified accordingly or equivalent Filtering performed.
  • the hearing aid wearer or user 1 is located, as in FIG. 1 shown in a special acoustic situation, in the hearing aid an acoustic input signal 2 available stands. Since the hearing aid for the hearing aid wearer 1 is subjective not optimally adjusted, he takes a night training in front. He classifies the noise and tells the hearing aid the corresponding very general hearing situation or hearing situation identification, z. As "speech in noise", with. everyone Each of these listening situations 3 is a plurality of parameter sets 4 assigned. Due to the selected listening situation 3, the hearing aid wearer 1 has, for example, seven parameter sets to select. He can now choose the parameter set 4 with which the hearing aid is set, that in this acoustic situation the subjectively best Sound produced.
  • a neural network 5 learns the desired parameter set 4 for the applied acoustic input signal 2, so it this parameter set 4 also for a similar acoustic situation will choose again after the training phase.
  • the hearing aid wearer or user 1 receives the acoustic Input signal 2.
  • the hearing aid wearer 1 receives the acoustic situation, in which he is currently, only one of a variety of predetermined, specific listening situations 3 'assign.
  • the number of specific listening situations 3 ' is usually larger in the case of the present invention as the number of general listening situations 3 according to FIG. 1, because they should be differentiated from the beginning.
  • the general listening situation "Speech in noise" for example, the specific hearing situation "own voice” includes.
  • the neural network 5 does not learn the assignment of a Parameter set to the acoustic input signal 2, but the assignment of a differentiated hearing situation or one Hörsituationskennung 3 'to the acoustic input signal. 2 (see arrows with solid lines in FIG. This means, that the neural network in contrast to the prior art learns at a higher level.
  • the neural network in contrast to the prior art learns at a higher level.
  • this complex situation a fixed parameter set starting, for example, from assigned to the parameter set group "Language in noise”. Because only a number of parameter sets are available for selection Hearing aid wearer for such situations "speech in noise" is meaningful, certainly none of the available standing parameter sets for own voice and additionally optimized for your own car.
  • These listening situations each have a specific influence the complex signal processing.
  • a specific reinforcement possibly coupled with a special setting of Directivity of the hearing aid, and in the situation “in his own Auto "again a very specific noise reduction caused in the hearing aid.
  • the neural network 5 is an acoustic input signal 2 one or assign a plurality of specific listening situation identifiers 3 ', so that the currently valid parameter set 4 '(including Filter parameter) is influenced accordingly.
  • a complex Signal processing unit 6 z. B. with adaptive directional microphone is the signal processing based on the influenced Carry out parameter set 4 '. If the neural network according to the example above, the input signal "own Voice in your own car ", it shows this to both the Listening situation identification "own voice” as well as the Hörsituationskennung "in your own car” too, so the current parameter set for example, in terms of specific reinforcement for your own voice and specific Filtering to suppress the noise of your own car varied or supplemented.
  • Example 1 An adaptive directional microphone is aimed at the Direction from which the maximum useful sound, z. B. a Speech signal, is incident. Entertains the hearing aid wearer with a person walking beside him, that should be Set directional microphone on the conversation partner, d. H. on a maximum gain at an angle of about 90 °. As soon as However, the hearing aid itself speaks, comes the useful sound signal from the own mouth, d. H. from an angle of 0 °. The own language thus draws the directional microphone characteristic away from the actual caller and usually with a certain delay.
  • Example 2 A noise canceling method may specifically be used trained on a complex, time-varying noise become. This noise is then optimally suppressed, although it may have similar spectral components or a Modulation spectrum such as speech, which further processed as a useful signal should be, has.
  • the noise reduction method automatically optimally adjusted by, for example special weighting factors for single spectral Tapes are set or the dynamic behavior optimally adapted to the noise characteristic. Also in this case are the differences between the settings dynamic noise canceling only difficult to assess directly, but the situation is very reliable.
  • the night training as it is for the hearing aid wearer, will now be explained in more detail with reference to FIGS 3 and 4.
  • the remote control 12 has a button 13 as a control on.
  • an acoustic signal here your own voice
  • the hearing aid wearer must now the hearing aid 10 announce the beginning and the end of the training phase. This is done by holding down the button 13 while he speaks himself. This means that he steps for both use only a single control element 13 of the training got to. If there are many hearing situation identifications, you can another design be more user-friendly, for B. with a Display and a slider (slider, trackball, etc.), with which the corresponding situation can be selected quickly can.
  • the actual night training of the hearing aid 10 may be during the performance of the acoustic signal 14 take place.
  • the acoustic signal 14 is recorded in the hearing aid and evaluated after the recording or the selected listening situation due to characteristic acoustic properties assigned.
  • online night training is one permanent or temporary storage of the acoustic signal 14 not necessary.
  • the hearing aid 10 Since the hearing aid 10 only the information about the current situation must be communicated, unlike the state the technique according to EP 0 814 634 A1 an external operating unit not necessary. It can, however, according to the 3 and 4 are used for example for reasons of comfort. However, it can also be a recording button on the hearing aid itself to be appropriate.
  • the recognition rate of the Classifier for certain situations clearly opposite Increase the presetting, so that the hearing aid more reliable to adjust to this situation.
  • the independent Starting and ending the night training phase by the Hearing aid wearers can also reliably relieve situations because the hearing aid wearer decides when the signal can be assigned to the situation.

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Evolutionary Computation (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Automation & Control Theory (AREA)
  • Neurosurgery (AREA)
  • Otolaryngology (AREA)
  • Acoustics & Sound (AREA)
  • Signal Processing (AREA)
  • Electrically Operated Instructional Devices (AREA)
  • Circuit For Audible Band Transducer (AREA)
  • Filters That Use Time-Delay Elements (AREA)
EP04022104A 2003-10-10 2004-09-16 Procédé pour l'apprentissage et le fonctionnement d'une prothèse auditive et prothèse auditive correspondente Revoked EP1523219B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE10347211 2003-10-10
DE10347211A DE10347211A1 (de) 2003-10-10 2003-10-10 Verfahren zum Nachtrainieren und Betreiben eines Hörgeräts und entsprechendes Hörgerät

Publications (3)

Publication Number Publication Date
EP1523219A2 true EP1523219A2 (fr) 2005-04-13
EP1523219A3 EP1523219A3 (fr) 2007-08-08
EP1523219B1 EP1523219B1 (fr) 2008-08-20

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US (1) US7742612B2 (fr)
EP (1) EP1523219B1 (fr)
AT (1) ATE406073T1 (fr)
AU (1) AU2004218632B2 (fr)
DE (2) DE10347211A1 (fr)
DK (1) DK1523219T3 (fr)

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EP1670285A3 (fr) * 2004-12-09 2008-08-20 Phonak Ag Methode pour régler les paramètres d'une fonction de transfert d'une prothèse auditive et prothèse auditive correspondante
EP1744589A3 (fr) * 2005-07-11 2010-01-20 Siemens Audiologische Technik GmbH Appareil auditif et procédé correspondant pour la détection de voix-propres
EP1744589A2 (fr) 2005-07-11 2007-01-17 Siemens Audiologische Technik GmbH Appareil auditif et procédé correspondant pour la détection de voix-propres
US9351087B2 (en) 2006-03-24 2016-05-24 Gn Resound A/S Learning control of hearing aid parameter settings
WO2007110073A1 (fr) * 2006-03-24 2007-10-04 Gn Resound A/S Commande autodidacte de réglages de paramètres d'aide auditive
US9408002B2 (en) 2006-03-24 2016-08-02 Gn Resound A/S Learning control of hearing aid parameter settings
EP2063663A1 (fr) * 2007-11-22 2009-05-27 myWORLDofHEARING e.K. Procédé destiné à l'adaptation individuelle d'un appareil auditif
US8477972B2 (en) 2008-03-27 2013-07-02 Phonak Ag Method for operating a hearing device
WO2008084116A3 (fr) * 2008-03-27 2009-03-12 Phonak Ag Procédé pour faire fonctionner une prothèse auditive
WO2020007478A1 (fr) 2018-07-05 2020-01-09 Sonova Ag Classes sonores supplémentaires pour ajuster un dispositif auditif
US11284207B2 (en) 2018-07-05 2022-03-22 Sonova Ag Supplementary sound classes for adjusting a hearing device
CN112911478A (zh) * 2019-12-03 2021-06-04 西万拓私人有限公司 用于训练听力设备的听力情形分类器的方法
CN112911478B (zh) * 2019-12-03 2022-10-21 西万拓私人有限公司 用于训练听力设备的听力情形分类器的方法

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EP1523219B1 (fr) 2008-08-20
AU2004218632B2 (en) 2009-04-09
EP1523219A3 (fr) 2007-08-08
DE10347211A1 (de) 2005-05-25
DK1523219T3 (da) 2009-01-05
AU2004218632A1 (en) 2005-04-28
US20050105750A1 (en) 2005-05-19
DE502004007878D1 (de) 2008-10-02
ATE406073T1 (de) 2008-09-15
US7742612B2 (en) 2010-06-22

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