In-Ear Voice Capture Using Generative Audio Enhancement

The patent introduces an external microphone as an intermediary device to capture the speech signal before it enters the ear canal. This external microphone serves as a mediator that records the speech in a cleaner environment, which then compensates for the degradation caused by the in-ear microphone's low-pass filtering and noise. The system combines signals from both microphones, using the external microphone's cleaner capture to offset the in-ear microphone's limitations.

The patent replaces conventional mechanical signal processing methods with deep learning-based neural network processing. Instead of using traditional filtering and enhancement algorithms, the system employs trained neural networks that can automatically learn and adapt to various speech patterns, noise types, and ear canal characteristics. This substitution enables more accurate speech recognition while handling the complex interactions between multiple microphones and noise sources.

The patent merges the functionality of multiple microphones (in-ear and external) into a unified processing system. Rather than treating them as separate components requiring independent processing, the system combines their outputs and uses a joint deep learning model that processes both signals simultaneously. This merging approach leverages the complementary strengths of each microphone while avoiding the complexity of managing them as separate systems.