Microphone Array Signal Processing Using Voice Triggered Beamforming
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Solution Overview
Problem
Existing microphone array signal processing systems face challenges in reducing noise while maintaining low power consumption, especially in portable devices, where voice activation and recognition require efficient noise reduction without continuous high power usage.
Innovation Solution
A microphone array signal processing system that uses a digital buffer to store audio signals and applies fixed beamformer coefficients to noise-reduced digital audio signals, reducing noise components by determining noise statistics based on specific signal segments and utilizing a voice trigger input to activate the beamforming algorithm, thereby minimizing power consumption and enhancing voice recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous beamforming processing is applied to all digital audio signals from multiple microphones, then noise reduction performance is improved, but power consumption increases significantly
Solution Approach 1:
The system performs preliminary voice detection on a single digital audio signal before activating the full beamforming processing. The voice detector analyzes one microphone signal in advance to determine whether voice presence warrants activation of the more power-intensive beamformer that processes all microphone signals, thus avoiding continuous high power consumption while maintaining noise reduction capability when needed
Solution Approach 2:
Instead of applying full beamforming processing to all microphone signals continuously, the system applies partial processing by first detecting voice on a single signal, then selectively applying beamforming only when voice is detected. This partial action approach reduces overall computational load and power consumption while still achieving effective noise reduction during voice segments
2Measurement precision
If voice detection is performed on all digital audio signals from multiple microphones, then voice detection accuracy is improved, but signal processing resources and power consumption increase
Solution Approach 1:
The system extracts the voice detection function from the full beamforming processing chain and implements it separately on a single digital audio signal. This extraction allows voice detection to be performed with minimal processing resources, and only when voice is detected does the system activate the more resource-intensive beamforming algorithm that processes all microphone signals
Solution Approach 2:
The system performs partial voice detection on only one digital audio signal rather than analyzing all microphone signals simultaneously. This partial detection approach reduces computational complexity and power consumption while still providing sufficient accuracy to trigger beamforming when voice is present, thereby managing signal processing resources efficiently
Data Source
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AI summary
The present invention relates in one aspect to a microphone array signal processing system comprising a digital buffer coupled to a signal input and configured to store first and second digital audio signals. A beamformer analyser is configured to, in response to a first voice trigger, determine noise statistics based on the first signal segment of the first digital audio signal and a first signal segment of the second digital audio signal. A coefficients calculator is configured to calculate a first set of fixed beamformer coefficients of a beamforming algorithm. The beamforming algorithm is configured for applying the first set of fixed beamformer coefficients to the first signal segments of the first and second digital audio signals retrieved from the digital buffer to produce a noise reduced digital audio signal.