PREDICTING GAIN MARGIN IN A HEARING DEVICE USING A NEURAL NETWORK

    公开(公告)号:US20230388724A1

    公开(公告)日:2023-11-30

    申请号:US18204014

    申请日:2023-05-31

    CPC classification number: H04R25/507 H04R25/453 H04R25/604 H04R2430/01

    Abstract: A hearing device includes a microphone that produces an audio input signal and a loudspeaker that outputs an amplified audio signal into an ear canal. A signal processing path is coupled to the microphone and the loudspeaker. The signal processing path includes a deep neural network configured to predict an instantaneous gain margin of the hearing device based on a set of inputs. The set of inputs includes a first parameter of the audio input signal, a second parameter of the amplified audio signal, and a gain of the signal processing path. A feedback reduction module of the device receives the predicted instantaneous gain margin and adjusts feedback reduction parameters to reduce an onset of feedback in the hearing device

    VOICE CLASSIFICATION IN HEARING AID

    公开(公告)号:US20250063312A1

    公开(公告)日:2025-02-20

    申请号:US18797361

    申请日:2024-08-07

    Abstract: A processing system may receive reference audio data representing one or more voices and may generate, using a first machine learning (ML) model, an embedding of the reference audio data. The processing system receives live audio data representing sound detected by one or more microphones of a hearing instrument and may generate an input spectrogram of the live audio data. The processing system may use a second ML model to generate a masked spectrogram based on the embedding and the input spectrogram. The masked spectrogram represents a version of the live audio data in which portions of the live audio data spoken in the voices represented by the reference audio data are enhanced. The processing system may cause one or more receivers of the hearing instrument to output sound based on the masked spectrogram.

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