Abstract: A computer implemented method for training a machine learning model for audio compensation includes: receiving 3D models of a plurality of rooms, each of the 3D models comprising at least one sound source and at least one acoustic property; receiving a plurality of impulse responses at a listening position in each of the plurality of rooms, training the machine learning model for audio compensation using at least the plurality of impulse responses as input. Methods and systems using the disclosed computer implemented method and its features are also disclosed.

Abstract: A computer-implemented method for generating a device-specific room impulse response (DSRIR) describing an acoustic characteristic of a device and a room as received by the device includes: generating an at least first device-related transfer function (DRTF), wherein the at least first device related transfer function describes the acoustic characteristic of the device as received by the at least first microphone; generating a spatial room impulse response (SRIR), wherein the spatial room impulse response describes the acoustic characteristic of the room from at least one room sound source in the room and received at an at least one listening point in the room from at least one direction; and generating the device specific room impulse response (DSRIR) by combining the device related transfer function and the spatial room impulse response.

Abstract: A method for generating an impulse response for a listening point in a room includes: receiving a 3D model of the room, the position of at least one sound source in the 3D model, and acoustic properties of at least one boundary in the 3D model; using a wave based solver for determining a wave based impulse response of a wave based propagation of an impulse emitted at the at least one sound source in the 3D model and received at the listening point within a first acoustic frequency range; using a geometrical acoustics based solver for determining a geometrical impulse response of the ray based propagation of an impulse emitted at the at least one sound source in the 3D model and received at the listening point within a second acoustic frequency range; and generating the impulse response by merging the wave impulse response and the geometrical impulse response.

Abstract: A computer implemented method for training a machine learning model for audio compensation includes: receiving 3D models of a plurality of rooms, each of the 3D models comprising at least one sound source and at least one acoustic property; receiving a plurality of impulse responses at a listening position in each of the plurality of rooms, training the machine learning model for audio compensation using at least the plurality of impulse responses as input. Methods and systems using the disclosed computer implemented method and its features are also disclosed.

Abstract: A computer-implemented method for generating a device-specific room impulse response (DSRIR) describing an acoustic characteristic of a device and a room as received by the device includes: generating an at least first device-related transfer function (DRTF), wherein the at least first device related transfer function describes the acoustic characteristic of the device as received by the at least first microphone; generating a spatial room impulse response (SRIR), wherein the spatial room impulse response describes the acoustic characteristic of the room from at least one room sound source in the room and received at an at least one listening point in the room from at least one direction; and generating the device specific room impulse response (DSRIR) by combining the device related transfer function and the spatial room impulse response.

Abstract: A method for generating an impulse response for a listening point in a room includes: receiving a 3D model of the room, the position of at least one sound source in the 3D model, and acoustic properties of at least one boundary in the 3D model; using a wave based solver for determining a wave based impulse response of a wave based propagation of an impulse emitted at the at least one sound source in the 3D model and received at the listening point within a first acoustic frequency range; using a geometrical acoustics based solver for determining a geometrical impulse response of the ray based propagation of an impulse emitted at the at least one sound source in the 3D model and received at the listening point within a second acoustic frequency range; and generating the impulse response by merging the wave impulse response and the geometrical impulse response.

Abstract: A computer implemented method for training a machine learning model for audio compensation includes: receiving 3D models of a plurality of rooms, each of the 3D models comprising at least one sound source and at least one acoustic property; receiving a plurality of impulse responses at a listening position in each of the plurality of rooms, training the machine learning model for audio compensation using at least the plurality of impulse responses as input. Methods and systems using the disclosed computer implemented method and its features are also disclosed.

Abstract: A hearing device, e.g. a hearing aid, having a protection system is disclosed. The device includes an input unit for receiving an acoustic signal from a user's surroundings and providing a corresponding audio signal, and an output unit receiving said audio signal and providing an audible signal to the user, where the hearing device further includes a barrier element for protecting elements of the hearing device. Furthermore, the disclosure relates to a hearing device inlet system.

Abstract: A hearing aid includes a microphone unit arranged in a hearing aid housing. The microphone unit is oriented in the housing relative to a microphone inlet element to cause a pressure equalization that allows acoustic cancellation of vibrations in the microphone unit.

Abstract: A hearing aid includes a microphone unit arranged in a hearing aid housing. The microphone unit is oriented in the housing relative to a microphone inlet element to cause a pressure equalization that allows acoustic cancellation of vibrations in the microphone unit.

Abstract: A hearing device, e.g. a hearing aid, having a protection system is disclosed. The device includes an input unit for receiving an acoustic signal from a user's surroundings and providing a corresponding audio signal, and an output unit receiving said audio signal and providing an audible signal to the user, where the hearing device further includes a barrier element for protecting elements of the hearing device. Furthermore, the disclosure relates to a hearing device inlet system.

Abstract: A hearing aid includes a microphone unit arranged in a hearing aid housing. The microphone unit is oriented in the housing relative to a microphone inlet element to cause a pressure equalization that allows acoustic cancellation of vibrations in the microphone unit.

Abstract: A hearing device, e.g. a hearing aid, having a protection system is disclosed. The device includes an input unit for receiving an acoustic signal from a user's surroundings and providing a corresponding audio signal, and an output unit receiving said audio signal and providing an audible signal to the user, where the hearing device further includes a barrier element for protecting elements of the hearing device. Furthermore, the disclosure relates to a hearing device inlet system.

Abstract: Systems and methods are provided for enlisting single phase commit resources in a two phase commit transaction. An exemplary method includes accessing a global transaction having a plurality of processes requiring single phase commit (1PC) resource and a two phase commit (2PC) resource, initializing a 1PC resource manager for the 1PC resource with a first process of the plurality of processes, wherein the first process requires the 1PC resource, preparing a 2PC resource manager for the 2PC resource with a second process of the plurality of processes, wherein the second process requires the 2PC resource, generating a unique identifier for the 1PC resource, transmitting the unique identifier to the 1PC resource manager, and instructing the 1PC resource manager to commit the first process to the 1PC resource, wherein committing the first process to the 1PC resource comprises recording the unique identifier to the 1PC resource.

Abstract: An electronic device, such as a hearing aid. The electronic device comprising a microphone unit, which are arranged in a hearing aid housing so as to optimize the vibration sensitivity of the microphone unit towards changes in the environment, potentially causing the housing to be influenced by vibrations, is disclosed. Furthermore, a method of arranging a microphone unit in an electronic device is disclosed.

Abstract: A hearing device, e.g. a hearing aid, having a protection system is disclosed. The device includes an input unit for receiving an acoustic signal from a user's surroundings and providing a corresponding audio signal, and an output unit receiving said audio signal and providing an audible signal to the user, where the hearing device further includes a barrier element for protecting elements of the hearing device. Furthermore, the disclosure relates to a hearing device inlet system.

Abstract: Systems and methods are provided for enlisting single phase commit resources in a two phase commit transaction. An exemplary method includes accessing a global transaction having a plurality of processes requiring single phase commit (1PC) resource and a two phase commit (2PC) resource, initializing a 1PC resource manager for the 1PC resource with a first process of the plurality of processes, wherein the first process requires the 1PC resource, preparing a 2PC resource manager for the 2PC resource with a second process of the plurality of processes, wherein the second process requires the 2PC resource, generating a unique identifier for the 1PC resource, transmitting the unique identifier to the 1PC resource manager, and instructing the 1PC resource manager to commit the first process to the 1PC resource, wherein committing the first process to the 1PC resource comprises recording the unique identifier to the 1PC resource.