Headset Voice Activity Detection via ANC Signal Symmetry
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Solution Overview
Problem
Existing headsets with automatic noise reduction (ANC) circuitry improve listening experiences but fail to effectively reduce ambient noise transmission, leading to power consumption issues and communication gaps due to inefficient voice activity detection methods.
Innovation Solution
The implementation of a system using two control microphones with processing circuitry that determines user speech presence based on temporal symmetry, complex coherence, or energy ratios of microphone output signals to accurately mute and unmute the voice mic, reducing ambient noise transmission while conserving power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If monitoring circuitry is provided to automatically mute or unmute the voice mic based on threshold comparison, then ambient noise transmission is reduced, but power consumption increases and battery life is shortened
Solution Approach 1:
The patent replaces continuous threshold-based monitoring with a discontinuous voice activity detection system that uses signal processing techniques (energy detection, autocorrelation, zero-crossing rate) to identify speech segments. This substitution allows the system to achieve effective noise suppression only during actual speech periods rather than requiring continuous monitoring, thereby reducing overall power consumption while maintaining noise reduction effectiveness.
Solution Approach 2:
The system implements periodic voice activity detection at specific intervals rather than continuous monitoring. The detection mechanism samples the audio signal at defined rates and activates muting only when speech is detected, creating a periodic operation pattern that reduces power consumption compared to continuous threshold monitoring while still effectively preventing ambient noise transmission during non-speech periods.
2Object-affected harmful factors
If threshold-based monitoring circuitry is used to automatically mute the voice mic, then ambient noise transmission is reduced, but communication gaps are created due to slow reaction and false detection
Solution Approach 1:
The patent replaces simple threshold comparison with sophisticated voice activity detection algorithms including energy detection, autocorrelation analysis, and zero-crossing rate measurement. These signal processing techniques provide more accurate speech detection by analyzing multiple characteristics of the audio signal simultaneously, reducing false positives from ambient noise and improving reaction speed to actual speech onset, thereby maintaining communication continuity while still suppressing noise.
Solution Approach 2:
The system performs preliminary voice activity detection and analysis before activating the muting function. By pre-analyzing signal characteristics such as energy levels, correlation patterns, and zero-crossing rates, the system can distinguish between actual speech and ambient noise in advance, preventing premature or incorrect muting actions that would create communication gaps.
3Object-affected harmful factors
If manual muting is required to prevent background noise transmission, then noise transmission is reduced, but communication gaps occur when users forget to unmute
Solution Approach 1:
The system provides self-service automatic voice activity detection and muting control. The detection mechanism continuously monitors the audio input and automatically activates muting when speech is detected, eliminating the need for manual user intervention. This self-operating system prevents both ambient noise transmission and communication gaps by autonomously managing the muting state based on real-time speech detection, thereby significantly improving user convenience.
Data Source
AI summary
Many headsets include automatic noise cancellation (ANC) which dramatically reduces perceived background noise and improves user listening experience. Unfortunately, the voice microphones in these devices often capture ambient noise that the headsets output during phone calls or other communication sessions to other users. In response, many headsets and communication devices provide manual muting circuitry, but users frequently forget to turn the muting on and/or off creating further problems as they communicate. To address this, the present inventors devised, among other things, an exemplary headset that detects the absence or presence of user speech, automatically muting and unmuting the voice microphone without user intervention. Some embodiments leverage relationships between feedback and feedforward signals in ANC circuitry to detect user speech, avoiding the addition of extra hardware to the headset. Other embodiments also leverage the speech detection function to activate and deactivate keyword detectors, and/or sidetone circuits, thus extending battery.