Wrist Wearable Audio Extraction Using Dual-Stage Noise Cancellation
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Solution Overview
Problem
Existing acoustic systems in wrist wearable devices face challenges in effectively reducing noise from both stationary and non-stationary sources, leading to degraded audio quality and increased error rates in speech recognition applications, especially in noisy environments where traditional noise cancellation methods like Spectral Subtraction and Voice Activity Detection fail.
Innovation Solution
A dual-stage noise reduction architecture that combines multi-channel noise cancellation with single-channel noise cancellation, utilizing auto-balancing and adaptive filtering to extract desired audio signals, and employs multiple microphones with different orientations and directivity patterns to enhance signal-to-noise ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional noise cancellation methods (Spectral Subtraction, Voice Activity Detection) are used, then device complexity is reduced, but noise reduction effectiveness deteriorates in high-noise environments
Solution Approach 1:
The noise cancellation system is divided into two independent stages: multi-channel noise cancellation (first stage) and single-channel noise cancellation (second stage). Each stage processes the signal independently with different algorithms optimized for specific noise conditions, allowing the system to handle both stationary and non-stationary noise effectively without requiring a single complex algorithm
Solution Approach 2:
The system dynamically switches between different noise cancellation strategies based on the noise characteristics detected in each stage. The multi-channel stage handles non-stationary noise while the single-channel stage refines stationary noise reduction, creating an adaptive system that responds to changing acoustic environments
2Measurement precision
If multiple microphones with different orientations are used, then signal-to-noise ratio is improved, but device complexity increases
Solution Approach 1:
Each microphone in the array is positioned with a specific orientation optimized for capturing speech from particular directions. The first microphone is oriented to maximize speech capture, while the second microphone has a different orientation to capture noise from other directions, creating complementary local optimization across the array
Solution Approach 2:
The system transitions from single-channel to multi-channel processing by incorporating spatial information from multiple microphones with different orientations. This adds a spatial dimension to the noise cancellation process, enabling the system to distinguish between speech and noise based on their different spatial characteristics
Data Source
AI summary
Systems and methods are described to extract desired audio from an apparatus to be worn on a user's wrist. The apparatus includes a wrist wearable device, configured to be worn on the user's wrist. The wrist wearable device includes a first microphone. The first microphone has a first response pattern. The first microphone is coupled to the wrist wearable device. The first microphone is positioned on the wrist wearable device to receive a voice signal from a user when the wrist wearable device is on the user's wrist.