A method of audio signal processing comprising Hybrid Expansive Frequency Compression (hEFC) via a digital signal processor, wherein the method includes: classifying an audio signal input, wherein the audio signal input includes frication high-frequency speech energy, into two or more speech sound classes followed by selecting a form of input-dependent frequency remapping function; and performing hEFC including, re-coding of one or more input frequencies of the speech sound via the input-dependent frequency remapping function to generate an audio output signal, wherein the output signal is a representation of the audio signal input having a lower sound frequency.

A hearing aid is configured to be worn in and/or at an ear of a user, and comprises a) an input transducer for converting an input sound to an electric input signal representing sound, h) an output transducer for converting a processed electric output signal to an output sound, c) a signal processor operationally coupled to the input and output transducers and configured to apply a forward gain to the electric input signal or a signal originating therefrom, wherein the input transducer, the signal processor and the output transducer forming part of a forward path of the hearing aid. The hearing aid further comprises d) a feedback control system for compensating for acoustic or mechanical feedback of an external feedback path from the output transducer to the input transducer, wherein the feedback control system comprises i) a feedback estimation unit for providing a feedback estimate signal of said external feedback path, ii) a combination unit located in the forward path for combining the electric input signal or a signal derived therefrom and the feedback signal detected by said estimation unit, to provide a resulting feedback corrected signal, iii) a correlation detection unit configured to determine a correlation measure between said feedback corrected signal and said output signal, said correlation detection unit further configured to provide a processed version of said correlation measure.

A bone conduction device located at the deaf ear of a recipient suffering from single-sided deafness is configured to receive sound signals within a spatial region proximate to the deaf ear of the recipient. The bone conduction device is configured to generate and deliver, based on the sound signals received within the spatial region, sound vibrations to the recipient. The sound vibrations are configured to evoke perception of the received sound signals at a cochlea of a second ear of the recipient. The bone conduction device is also configured to generate and deliver tactile vibrations to the recipient contemporaneously with the sound vibrations. The tactile vibrations generate a vibro-tactile sensation proximate to the deaf ear of the recipient, but the vibro-tactile sensation is non-perceivable (not heard) at the cochlea of the second ear of the recipient

The present disclosure relates to compact hearing aids, components thereof, and support systems therefor, as well as methods of insertion and removal thereof. The compact hearing aids generally include a sensor, such as a microphone, an actuation mass, an energy source for providing power to the compact hearing aid, a processor, and an actuator enclosed in a housing that is designed to be inserted through the tympanic membrane during a minimally-invasive outpatient procedure. In operation, the microphone receives sound waves and converts the sound waves into electrical signals. A processor then modifies the electrical signals and provides the electrical signals to the actuator. The actuator converts the electrical signals into mechanical motion, which actuates the actuation mass to modulate the velocity or the position of the tympanic membrane.

Disclosed herein are method, system, and computer program product embodiments for performing the continuous and autonomous selective tuning of received audio input from an earpiece, according to a variety of user-based tuning profiles and autonomous determination mechanisms for selecting any one of the tuning profiles, using logistic regression, multi-layered ensemble classifiers incorporating machine learning techniques, etc, for an optimal in-ear hearing experience for a user.

A method for compensating hearing deficiencies with a hearing device includes receiving a sound signal; attenuating an output sound pressure level of the sound signal dependent on an input sound pressure level of the sound signal; and outputting the attenuated sound signal with a loudspeaker of the hearing device; wherein the output sound pressure level is attenuated, when the input sound pressure level is above an upper speech recognition kneepoint of a user, which upper speech recognition kneepoint is stored in the hearing device and which has been selected dependent on a sound pressure level dependent speech recognition ability of the user.

Provided a robot for assisting hearing of a user, while minimizing an influence on the surroundings. The robot includes a speaker, a microphone configured to recognize a voice, a processor configured to acquire a position of a user's face when a hearing aid command is acquired on the basis of the voice recognized through the microphone, and a driving unit configured to cause the speaker to be moved toward the position of the user's face, wherein the processor acquires a sound which is a target of hearing aid, generates an assistant sound by amplifying a predetermined frequency band of the sound or converting the predetermined frequency band of the sound into a different frequency band, and outputs the assistant sound through the speaker.

A hearing device, including: a device body; a receiver, configured to emit an audio signal, the audio signal being reflected to form a feedback signal, and the proximal end of the device body being proximate to an ear canal; an in-ear microphone, arranged at a proximal end of the device body and configured to receive the feedback signal; and a signal analyzing module, connected to the in-ear microphone and configured to analyze the feedback signal to obtain an analysis result.

A hearing device is disclosed, comprising a main microphone, M auxiliary microphones, a transform circuit, a processor, a memory and a post-processing circuit. The transform circuit transforms first sample values in current frames of a main audio signal and M auxiliary audio signals from the microphones into a main and M auxiliary spectral representations. The memory includes instructions to be executed by the processor to perform operations comprising: performing ANC over the first sample values using an end-to-end neural network to generate second sample values; and, performing audio signal processing over the main and the M auxiliary spectral representations using the end-to-end neural network to generate a compensation mask. The post-processing circuit modifies the main spectral representation with the compensation mask to generate a compensated spectral representation, and generates an output audio signal according to the second sample values and the compensated spectral representation.

Methods and systems are described herein for improving audio for hearing impaired content consumers. An example method may comprise determining a content asset. Closed caption data associated with the content asset may be determined. At least a portion of the closed caption data may be determined based on a user setting associated with a hearing impairment. Compensating audio comprising a frequency translation associated with at least the portion of the closed caption data may be generated. The content asset may be caused to be output with audio content comprising the compensating audio and the original audio.