Voice Detection in In-Ear Headsets Without Boom Microphones
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Solution Overview
Problem
In-ear active noise reduction headsets face challenges in detecting the user's voice effectively without a boom microphone, especially in noisy environments, which affects telephony and radio communication by introducing environmental noise and distorting self-voice.
Innovation Solution
The solution involves combining signals from feedback and feed-forward microphones within the earpieces to reconstruct a clear and intelligible voice signal without an additional voice microphone, using filters and array processing to enhance noise rejection and voice fidelity, and dynamically adjusting signal paths based on speech characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a boom microphone is used to detect user voice, then voice detection quality is improved, but device complexity and comfort are worsened
Solution Approach 1:
The patent makes the existing feedback and feed-forward microphones serve dual purposes: their primary function for active noise reduction and an additional function for voice detection. By processing these microphones' outputs through specific signal processing paths, the system extracts voice signals without requiring dedicated voice microphones or boom structures.
Solution Approach 2:
The system uses its own existing components (feedback and feed-forward microphones already present for noise cancellation) to also perform voice detection. This self-service approach eliminates the need for additional external components like boom microphones, reducing structural complexity while maintaining voice detection capability.
2Measurement precision
If feedback and feed-forward microphone signals are combined for voice detection, then voice intelligibility is improved, but environmental noise rejection becomes more challenging
Solution Approach 1:
The patent applies different signal processing treatments to different frequency components and signal paths. By analyzing the specific characteristics of feedback and feed-forward microphone signals at different frequencies and applying appropriate filtering and combination strategies, the system enhances voice frequencies while suppressing environmental noise frequencies.
Solution Approach 2:
The system uses the feedback microphone signal, which already contains information about sounds within the ear canal including the user's voice, and combines it with the feed-forward signal. This feedback-based approach allows the system to identify and extract voice components while the active noise reduction processing simultaneously suppresses environmental noise.
3Ease of operation
If side-tone audio is provided to help user hear their own voice, then communication comfort is improved, but environmental noise is introduced
Solution Approach 1:
The system provides side-tone audio at an optimized level that is sufficient for the user to hear their own voice clearly for communication comfort, but not so excessive as to introduce significant environmental noise. The signal processing selectively enhances voice frequencies in the side-tone while suppressing environmental noise frequencies.
Data Source
AI summary
A headset includes an acoustic structure, a first microphone located outside the acoustic structure, a second microphone located inside the acoustic structure, and an output driver configured to receive an antinoise signal based on a combination of input from the first and second microphones. A voice signal of a user of the headset is generated using input from the first and second microphones. The first microphone could be a feed-forward microphone that provides input to a feed-forward filter to produce a filtered feed-forward signal for producing the antinoise signal. The second microphone could be a feedback microphone that provides input to a feedback filter to produce a filtered feedback signal for producing the antinoise signal.