Binaural data sharing in ear-worn devices using neural networks

Abstract

Described herein is binaural data sharing technology for ear-worn devices to improve audio processing performance. Different embodiments may include sharing of various data types, such as processed microphone signals, beamformed signals, neural network products (e.g., masks), and environmental metrics. For beamforming, devices may combine signals from both ears for improved directional selectivity or process separate beamformed signals independently. Devices may be configured to generate identical masks or average mask magnitude portions while preserving device-specific phase components. Neural networks may be trained to handle mixed-latency data, processing current local data with 'stale' data from the other device. Environmental metrics like signal-to-noise ratios may be shared for coordinated responses to acoustic conditions. The technology may also apply to integrated devices like eyeglasses.