This technology is an auditory device that utilizes deep neural network models to augment the processing and amplification of desired sounds in multi-source environments for individuals with impaired auditory directionality processing.
Currently, those who suffer from central auditory processing disorders (CAPD) that make it difficult to focus on desired sounds in multi-source environments have limited options to augment their hearing. Standard multi-directional hearing aids and beamformers either lack sufficient signal-to-noise augmentation to adequately amplify desired sounds and cancel undesired noise or suffer a tradeoff with correctly identifying the desired sound source. Thus, many CAPD patients struggle to achieve normal speech understanding in day-to-day life.
This technology utilizes deep neural network models and automatic speech separation algorithms to determine the source of desired sounds in multi-source environments. It further implements a brain-computer interface to decode the user’s neural activity and amplify the signal of the desired sound. It has been successfully utilized to decode the varying attention of human users when presented with multi-speaker audio and is capable of significant signal-to-noise amplification.
Patent Issued (US 11,961,533)
IR CU16343, CU17276
Licensing Contact: Kristin Neuman
