A method for preparing an audiogram of a test subject by use of a hearing instrument. A sound signal is recorded in an auditory canal of the test subject at least partially closed by the hearing instrument by a first electroacoustic input transducer of the hearing instrument. A first input signal is generated therefrom. A test sound is generated by an electroacoustic output transducer of the hearing instrument and output into the auditory canal of the test subject at least partially closed by the hearing instrument. A hearing threshold of the test subject at at least one test frequency is ascertained on a basis of a reaction of the test subject to the test sound and by use of the first input signal.

A hearing system configured to be located at or in the head of a user, comprises a) at least two microphones providing at least two electric input signals, b) an own voice detector, c) access to a database (O.sub.l, H.sub.l) comprising c1) relative or absolute own voice transfer function(s), and corresponding c2) absolute or relative acoustic transfer functions for a multitude of test-persons, d) a processor connectable to the at least two microphones, to the own voice detector, and to the database. The processor is configured A) to estimate an own voice relative transfer function for sound from the user's mouth to at least one of the at least two microphones, and B) to estimate personalized relative or absolute head related acoustic transfer functions from at least one spatial location other than the user's mouth to at least one of the microphones of the hearing system in dependence of the estimated own voice relative transfer function(s) and the database (O.sub.l, H.sub.l). The hearing system further comprises e) a beamformer configured to receive the at least two electric input signals, or processed versions thereof, and to determine personalized beamformer weights based on the personalized relative or absolute head related acoustic transfer functions or impulse responses. A method of determining personalized beamformer coefficients (w.sub.k) is further disclosed.

A system creates an audio profile. The audio profile may be stored in a database. For example, the audio profile may be securely stored in a database of a social network and associated with a user account. The audio profile may contain data describing the way in which the specific user hears and interprets sounds. Systems and applications which present sounds to the user may access the audio profile and modify the sounds presented to the user based on the data in the audio profile to enhance the audio experience for the user.

A fitting agent for a hearing device and related method is disclosed, wherein the fitting agent is configured to initialize a user model comprising a user preference function; obtain a primary test setting for the hearing device; obtain a secondary test setting for the hearing device; present the primary test setting and the secondary test setting to a user; detect a user input of a preferred test setting indicative of a preference for either the primary test setting or the secondary test setting; and update the user model based on hearing device parameters of the preferred test setting, wherein to obtain the secondary test setting comprises: obtain a candidate set of candidate test settings; determine an uncertainty parameter for each candidate test setting; and select the secondary test setting from the candidate set of candidate test settings based on the uncertainty parameters of the candidate test settings.

The present disclosure relates to methods and devices for a hearing system. A method, performed by a hearing device of a hearing system comprising a hearing device system and an external device, the hearing device system comprising the hearing device and a user accessory device with a user application installed thereon is disclosed, the method comprising receiving, from the user accessory device, secure hearing system data, the secure hearing system data comprising a data type identifier; determining a data type of the secure hearing system data based on the data type identifier; determining hearing system data by applying a security scheme to the secure hearing system data based on the data type; and operating the hearing device according to the hearing system data.

A method for correcting a synthesized speech set for hearing aid according to an aspect of the present invention includes the steps of outputting first synthesized speech for testing on the basis of first synthesized speech data for testing correlated with a first phoneme label in a synthesized speech set for testing, accepting a first answer selected by a user, outputting second synthesized speech for testing on the basis of second synthesized speech data for testing correlated with a second phoneme label in the synthesized speech set for testing, accepting a second answer selected by the user, and correlating first synthesized speech data for hearing aid with the second phoneme label instead of second synthesized speech data for hearing aid in a synthesized speech set for hearing aid, in a case in which the first answer matches the second phoneme label and also the second answer does not match the second phoneme label.

Systems and methods may be used to predict an applicable a hearing assistance device shell or model. For example, a method may include obtaining patient information, determining, using a machine learning trained model, a correlation between an input vector and each of a plurality of feature vectors corresponding to a plurality of hearing assistance device models, and ranking the plurality of hearing assistance device models based on respective correlations to the input vector. Information corresponding to a highest ranked hearing assistance device model may be output.

A hearing system includes a processing device, a hearing aid adapted to be worn by a user, and a data logger. The hearing aid includes an input transducer providing an electric input signal representing sound in the environment of the user, and a hearing aid processor executing a processing algorithm in dependence of a specific parameter setting. The data logger stores time segments of said electric input signal, and data representing a corresponding user intent. The processing device comprises a simulation model of the hearing aid. The simulation model is based on a learning algorithm configured to provide a specific parameter setting optimized to the user's needs in dependence of a hearing profile of the user, the logged data, and a cost function. A method of determining a parameter setting for a hearing aid is further disclosed.

A method fits a digital hearing aid having an input transducer, a signal processing device and an output transducer. The signal processing device is configured to form an evaluation unit, a comparator unit, and a pre-amplification unit. An acoustic test signal is generated by an external testing device while the hearing aid is worn by a hearing-aid wearer. A digital test input signal is generated by the input transducer on the basis of the acoustic test signal. A sound pressure-dependent test quantity is determined on the basis of the digital test input signal by the evaluation unit. A deviation between the sound pressure-dependent test quantity and a reference quantity stored in the signal processing device is determined by the comparator unit. A pre-amplification by the pre-amplification unit is adjusted on the basis of the determined deviation.

A method for fitting a hearing device comprises: receiving an audio signal in the hearing device; providing a user interface for inputting at least one modifier value into the fitting device, the modifier value indicating, how a sound property of the audio signal should be modified by the hearing device; processing the audio signal with a sound processor of the hearing device in dependence of the at least one modifier value, thus providing a processed audio signal; outputting the processed audio signal to a user of the hearing device; determining an modifier effectiveness value based on the audio signal, the modifier effectiveness value indicating how much a change of the at least one modifier value results in a perceptible change of the processed audio signal output to the user; and restricting the inputting of the at least modifier value in dependence of the modifier effectiveness value.