Abstract: In some embodiments, an ear-worn device may include adaptive mixing control circuitry configured to control mixing circuitry to mix a speech component of an input audio signal with a noise component of the input audio signal based on a deviation of a short-term level of the noise component of the input audio signal from a long-term level of the noise component of the input audio signal. In some embodiments, an ear-worn device may include beamforming circuitry configured to generate a front audio signal and a back audio signal, and direction-of-arrival circuitry configured to bias an output audio signal based on a difference between the front audio signal and the back audio signal.

Abstract: A method is for setting up a data connection between a terminal device of a telematics system in a vehicle and a central module of a stationary local area network (SLAN). The SLAN covers a depot. The method includes: providing access data for identifying and authenticating the terminal device in the SLAN, the access data being provided via an access network differing from the SLAN; transferring the provided access data to the terminal device in an automated manner using the access network; setting up a connection between the terminal device and the central module of the SLAN in an automated manner when the vehicle having the terminal device is located in range; authenticating the terminal device in an automated manner on the basis of the access data to check authenticity of the terminal device; and, authorizing the terminal device and/or the vehicle automatically if the terminal device is authentic.

Abstract: An apparatus (e.g., an ear-worn device such as a hearing aid) may include neural network circuitry and control circuitry. The neural network circuitry may be configured to implement a neural network system comprising at least a first neural network and a second neural network operating in parallel. The control circuitry may be configured to control the neural network system to receive a first input signal, process the first input signal using the first neural network to produce a first output and using the second neural network to produce a second output, combine the first output and the second output, reset one or more states of the first neural network, and reset one or more states of the second neural network at a different time than when the one or more states of the first neural network are reset.

Abstract: An ear-worn device includes two or more microphones and noise reduction circuitry including neural network circuitry. The neural network circuitry is configured to: receive multiple audio signals wherein at least two of the multiple audio signals each originate from a different one of the two or more microphones and/or at least one of the multiple audio signals is a beamformed audio signal originating from the two or more microphones; and implement one or more neural network layers trained to perform background noise modification and spatial focusing based on the multiple audio signals, such that the neural network circuitry generates, based on the multiple audio signals, one or more neural network outputs. The noise reduction circuitry is configured to output, based on the one or more neural network outputs, an output audio signal comprising a background noise-modified and spatially-focused version of a first audio signal of the multiple audio signals.

Abstract: An apparatus (e.g., an ear-worn device such as a hearing aid) includes neural network circuitry and control circuitry. The neural network circuitry is configured to implement a neural network system comprising at least a first neural network and a second neural network operating in parallel. The control circuitry is configured to control the neural network system to receive a first input signal, process the first input signal using the first neural network to produce a first output and using the second neural network to produce a second output, combine the first output and the second output, reset one or more states of the first neural network, and reset one or more states of the second neural network at a different time than when the one or more states of the first neural network are reset.

Abstract: According to some embodiments, an ear-worn device, e.g., a hearing aid, is provided that operates to enhance audio signals detected by the ear-worn device. In some embodiments, the ear-worn device includes a microphone, a processing circuit coupled to the microphone, and an output signal generator coupled to the processing circuit. In some embodiments, a method for enhancing audio signals includes: detecting an audio signal with the microphone; as the audio signal is being detected, dividing the audio signal into a plurality of segments; enhancing the detected audio signal with the processing circuit of the hearing aid; and outputting the enhanced audio signal with the output signal generator. In some embodiments, enhancing the detected audio signal includes processing one or more of the segments of the detected audio signal with a neural network engine (NNE) of the processing circuit to obtain an output for enhancing the detected audio signal.

Abstract: An ear-worn device may include two or more microphones configured to generate time-domain audio signals, each of the two or more microphones configured to generate one of the time-domain audio signals; processing circuitry comprising analog processing circuitry, digital processing circuitry, beamforming circuitry, and short-time Fourier transformation (STFT) circuitry, the processing circuitry configured to generate, from the time-domain audio signals, one or more frequency-domain non-beamformed audio signals and one or more frequency-domain beamformed signals; and enhancement circuitry comprising neural network circuitry configured to receive multiple frequency-domain input audio signals originating from the one or more frequency-domain non-beamformed audio signals and the one or more frequency-domain beamformed signals, and implement a single neural network trained to generate, based on the multiple frequency-domain input audio signals, a noise-reduced and spatially-focused output audio signal or an output

Abstract: An ear-worn device includes two or more microphones and noise reduction circuitry including neural network circuitry. The neural network circuitry is configured to: receive multiple audio signals wherein at least two of the multiple audio signals each originate from a different one of the two or more microphones and/or at least one of the multiple audio signals is a beamformed audio signal originating from the two or more microphones; and implement one or more neural network layers trained to perform background noise modification and spatial focusing based on the multiple audio signals, such that the neural network circuitry generates, based on the multiple audio signals, one or more neural network outputs. The noise reduction circuitry is configured to output, based on the one or more neural network outputs, an output audio signal comprising a background noise-modified and spatially-focused version of a first audio signal of the multiple audio signals.

Abstract: Packaging that is meant to store and protect sterile catheter and guidewire assemblies for acute stroke treatment and other sterile vascular procedures. One end includes an access port for appropriately trained medical staff to expel gas, or “room air”, from the packaging under limited pressure, including catheter and guidewire assemblies, in a sterile fashion using a biocompatible liquid. Then, the medical personnel can release the catheter and guidewire assemblies from the packaging. With mild traction, the catheter and guidewire assemblies can be removed from the packaging in a slidable manner from another end of the packaging for immediate use in treatment of a hospitalized patient.

Abstract: Method for an electrically drivable vehicle, in particular a utility vehicle, with an energy storage device and an electric drive capable of regenerative braking, wherein the energy storage device can be charged during regenerative braking and the energy storage device can be charged at a vehicle-external charging station, the method including the steps: determining a state of charge, wherein the state of charge includes information about whether the energy storage device is being charged by the vehicle-external charging station; detecting, depending on the state of charge, vehicle information concerning the vehicle, in particular the utility vehicle, and position information concerning the position of the vehicle, in particular the utility vehicle; transmitting the vehicle information and the position information to an external server; and receiving a target state of charge from the vehicle-external server.

Abstract: The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal.

Abstract: The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal.

Abstract: The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal.

Abstract: The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal.

Abstract: The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal.

Abstract: An ear-worn device may include two or more microphones configured to generate time-domain audio signals, each of the two or more microphones configured to generate one of the time-domain audio signals; processing circuitry comprising analog processing circuitry, digital processing circuitry, beamforming circuitry, and short-time Fourier transformation (STFT) circuitry, the processing circuitry configured to generate, from the time-domain audio signals, one or more frequency-domain non-beamformed audio signals and one or more frequency-domain beamformed signals; and enhancement circuitry comprising neural network circuitry configured to receive multiple frequency-domain input audio signals originating from the one or more frequency-domain non-beamformed audio signals and the one or more frequency-domain beamformed signals, and implement a single neural network trained to generate, based on the multiple frequency-domain input audio signals, a noise-reduced and spatially-focused output audio signal or an output

Abstract: The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal.

Abstract: A system that includes first circuitries to operate at a first clock frequency, second circuitries to operate at a second clock frequency, and circuitry to adjust the first and second clock frequencies. In some examples, the circuitry is to selectively adjust the first and second clock frequencies provided to the respective first circuitries and the second circuitries according to a target ratio based on temperature and power consumption of the first circuitries and the second circuitries, wherein the target ratio is based on clock frequencies of the first circuitries and the second circuitries, stall time of the first circuitries, and dynamic capacitance of the first circuitries and the second circuitries.

Abstract: The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal.

Abstract: The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal.