Abstract: System and methods are presented for detecting an authentic copy of a deep neural network in a device without reverse engineering the device. For example, the device can be a hearing device. A method is presented that includes providing audio signals to a deep neural network located in a hearing device, receiving signals from the deep neural network that are triggered by the transmitted audio signals, and determining whether the received signals were the expected signals. Specifically, the system can determine that an unauthorized entity embedded an unauthorized copy of the deep neural network in a hearing device.

Abstract: A hearing device arrangement includes two hearing devices which are connected to each other in a data transmitting manner. Each hearing device includes an audio input unit for obtaining an input audio signal, a processing unit for audio signal processing of the input audio signal to obtain an output audio signal, a neural network which, when executed by the processing unit performs a processing step of the audio signal processing, and an audio output unit for outputting the output audio signal. The hearing device arrangement is configured to transmit neural network data of the neural network of at least one of the hearing devices to the respective other hearing device to be used in the audio signal processing by the processing unit of the respective other hearing device.

Abstract: Methods, hearing systems and neural networks for audio signal processing are described. A hearing system comprises a neural network. An input audio signal is processed into an output audio signal at least partially by means of a processing unit of the hearing system. The audio signal processing of the input audio signal includes executing audio signal processing by the neural network for performing a step of the audio signal processing, determining a confidence parameter resembling the reliability of the audio signal processing by the neural network and steering the audio signal processing in dependence of the confidence parameter. A particularly suitable neural network is configured to solve a regression-based acoustic processing task and additionally determining the confidence parameter.