Dual-Path Neural Network Hearing Aid for Real-Time Speech Separation
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Solution Overview
Problem
Traditional hearing aids struggle to effectively separate speech from background noise in noisy environments due to limitations in computational power and the impracticality of incorporating neural networks, leading to suboptimal user experiences for individuals with hearing loss.
Innovation Solution
A hearing aid system that integrates a neural network engine (NNE) with a dual-path signal processing chain, allowing selective engagement of neural network-based audio enhancement and digital signal processing, dynamically adjusting to user preferences and environmental conditions to optimize signal-to-noise ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neural network algorithms are incorporated into the hearing aid to separate speech from background noise, then speech intelligibility in noisy environments is improved, but power consumption increases and battery life is reduced
Solution Approach 1:
The patent divides the neural network processing into multiple stages: a first neural network performs initial speech enhancement on the raw audio signal, and a second neural network further processes the output to separate speech from background noise. This segmentation allows the system to achieve high speech intelligibility while managing computational load and power consumption by distributing processing tasks across multiple specialized networks rather than using a single resource-intensive model.
2Measurement precision
If powerful neural network algorithms are used for real-time speech separation, then speech intelligibility is improved, but processing speed and real-time performance deteriorate due to computational complexity
Solution Approach 1:
The patent implements dynamic processing where the hearing aid continuously adapts to changing acoustic environments by adjusting the processing parameters and selecting appropriate processing paths in real-time. The system monitors environmental conditions and dynamically switches between different processing modes (e.g., aggressive noise reduction vs. minimal processing) to maintain both high speech separation accuracy and real-time performance based on current computational requirements and environmental conditions.
3Device complexity
If traditional signal processing techniques are used to increase signal-to-noise ratio, then computational simplicity is maintained, but speech intelligibility in noisy environments remains insufficient
Solution Approach 1:
The patent introduces intermediate processing stages between the raw audio input and final output, where a first neural network performs preliminary speech enhancement and a second neural network performs detailed speech separation. These intermediate processing steps act as mediators that progressively improve speech intelligibility while breaking down the complex task into manageable stages, achieving better performance than traditional single-stage processing without requiring excessively complex algorithms.
Data Source
AI summary
The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.