Voice Operated Control Using Dual Microphone Signal Analysis
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Solution Overview
Problem
Earpiece devices struggle to differentiate between the user's voice and background noise, leading to degraded communication quality in noisy environments, as they are sound agnostic and cannot adequately discriminate between voices.
Innovation Solution
A device with dual microphones and a processor that analyzes sound signals using methods like sound pressure level comparison, correlation, coherence, and spectral difference to detect the user's voice and control audio operations, such as adjusting gain to prioritize the user's voice in the mixed signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If audio processing technologies suppress noise, then background noise is reduced, but the earpiece cannot differentiate between user's voice and other voices in the background
Solution Approach 1:
The patent divides the audio signal processing into multiple independent analysis streams: sound pressure level comparison, correlation analysis, coherence analysis, and spectral difference analysis. Each stream processes the signals from multiple microphones separately and contributes to the overall voice discrimination decision, enabling the system to differentiate user's voice from background voices through segmented analytical approaches.
Solution Approach 2:
The patent extends voice discrimination beyond simple noise suppression by adding multiple analysis dimensions: temporal dimension (cross-correlation, timing analysis), spectral dimension (spectral difference, frequency analysis), and spatial dimension (sound pressure level comparison across multiple microphones). This multi-dimensional approach enables the system to distinguish user's voice from background voices that simple noise suppression cannot differentiate.
2Loss of information
If the earpiece microphone captures all sounds, then no voice information is lost, but the communication quality degrades due to environmental sounds
Solution Approach 1:
The patent implements feedback mechanisms where the processor continuously analyzes signals from multiple microphones, compares sound pressure levels, calculates correlation and coherence values, and adjusts the mixed signal accordingly. The system uses spectral difference analysis and cross-correlation results to provide feedback control over signal mixing, dynamically enhancing user's voice while suppressing environmental sounds based on real-time analysis.
Solution Approach 2:
The patent changes multiple signal processing parameters to differentiate user's voice from environmental sounds: it adjusts gain levels based on sound pressure level comparisons, modifies spectral characteristics through frequency analysis, and alters temporal relationships through cross-correlation timing analysis. By dynamically changing these parameters, the system prioritizes user's voice information while reducing environmental sound interference.
3Measurement precision
If multiple microphones are used to detect acoustic signals, then voice detection accuracy improves, but device complexity increases
Solution Approach 1:
The patent makes the processor perform multiple functions using the same hardware components: it conducts sound pressure level comparison, cross-correlation analysis, coherence analysis, and spectral difference analysis all through a single processing unit. This multi-functionality approach improves voice detection accuracy through multiple analytical methods without proportionally increasing device complexity, as one processor handles all analysis tasks.
Solution Approach 2:
The patent combines multiple analysis results (sound pressure level comparison, correlation values, coherence measurements, spectral differences) into a single mixed signal output. By merging these different analytical approaches and their results into one unified signal processing pipeline, the system achieves improved voice detection accuracy while avoiding the complexity of completely separate processing systems for each analysis method.
Data Source
AI summary
At least one exemplary embodiment is directed to a method and device for voice operated control. The method can include measuring a first sound received from a first microphone, measuring a second sound received from a second microphone, detecting a spoken voice based on an analysis of measurements taken at the first and second microphone, mixing the first sound and the second sound to produce a mixed signal, and controlling the production of the mixed signal based on one or more aspects of the spoken voice.