Sonova Ag

Aliaksei Tsitovich

Harald Krueger

Andreas Breitenmoser

Daniel Schmid

Philipp Schneider

Filip Wojcieszyn

Peter Derleth

A method for collecting and storing sensor data () of a hearing system () comprises: receiving the sensor data () of at least one sensor () of a hearing device () of the hearing system (), wherein the hearing device () is worn by a user; detecting a situation () of interest by classifying at least a part of the sensor data () with a classifier () implemented in the hearing system (); collecting the sensor data (), when the hearing system () is in a situation () of interest; and sending the collected sensor data () to a storage system () in data communication with the hearing system ().

Selectively collecting and storing sensor data of a hearing system

The disclosed technology relates to securely sharing data between a hearing care professional (HCP) and a hearing device user. For example, the disclosed technology relates to securely accessing fitting data for a hearing device. The disclosed technology includes a hearing device that has a memory, where the memory stores a key that can be used for encryption and decryption. The key can be a symmetrical key. In addition to storing a key, the hearing device can store a uniform resource indicator (URI) in its memory.

Securely sharing data between a hearing device, hearing device user, and data storage

The disclosed technology relates to training a neural network and using that training to design a filter for the hearing device. The training can include training a generative adversarial network (GAN) to determine whether a signal includes intelligible speech, wherein the GAN includes a generator and discriminator. The generator can provide a mixed noise and speech signal to the discriminator can output a signal that reduces noise in the mixed signal. The technology can then determine whether the output signal is intelligible based on a speech metric function or based on feedback from a hearing care expert. The generator and the discriminator can continue to train based on this feedback. And then the trained network can use the settings of the discriminator or information from the design of the discriminator to generate a noise filter for a hearing device.

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Stäfa, Switzerland

Aliaksei Tsitovich