Adaptive Headset Noise Cancellation Without Downlink Signals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing active noise cancellation technologies in headsets are challenged by variable and irregular environment noise, varying fit between headsets and human ears due to different ear canal sizes and shapes, and the inability to perform cancellation without a downlink signal.
Innovation Solution
A noise cancellation method that determines target noise cancellation parameters using reference and error microphones, feedforward and feedback filters, and adaptive algorithms to eliminate dependence on downlink signals, allowing for per-frame adjustments of filter coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If active noise cancellation is performed based on a downlink signal, then noise cancellation can be achieved when the downlink signal is available, but noise cancellation cannot be performed when there is no downlink signal
Solution Approach 1:
The system uses the error microphone to collect error signals and automatically adjusts the feedforward filter coefficients through adaptive algorithms, enabling the noise cancellation system to serve itself without requiring external downlink signals for coefficient adjustment
2Adaptability or versatility
If a same headset is used by different people, then the headset can serve multiple users, but degrees of fitting between the headset and human ears are different due to different ear canal sizes and shapes, resulting in different noise leakage degrees
Solution Approach 1:
The feedforward filter coefficients are dynamically adjusted in real-time based on the error signals collected by the error microphone, allowing the system to adapt to different users' ear canal characteristics and fitting degrees without requiring manual reconfiguration
Solution Approach 2:
The error microphone continuously monitors the noise leakage and feeds this information back to the adaptive algorithm, which then adjusts the feedforward filter coefficients to optimize noise cancellation for each user's specific ear geometry and fitting condition
3Adaptability or versatility
If environment noise is variable and irregular, then the system must handle diverse noise conditions, but this makes noise cancellation more challenging and reduces prediction accuracy
Solution Approach 1:
The adaptive algorithm continuously updates the feedforward filter coefficients in real-time based on the current noise characteristics captured by the reference microphone, enabling the system to track and adapt to variable and irregular noise conditions rather than relying on fixed or pre-stored coefficients
Data Source
AI summary
This application discloses a noise cancellation method, a headset, an apparatus, a storage medium, and a computer program product, and relates to the field of audio processing technologies. The headset includes at least one first reference microphone, one error microphone, at least one speaker, and one first FF filter. The method includes: determining a target noise cancellation parameter based on a reference signal collected by the at least one first reference microphone, an error signal collected by the error microphone, and an initial noise cancellation coefficient, where the target noise cancellation parameter includes a filter coefficient of the first FF filter; and performing noise cancellation through a target speaker in the at least one speaker based on the target noise cancellation parameter.