Noise treatment program
Solutions for different noise scenarios:
- Active Noise Reduction Technology::
- exist
src/lib/audioProcessor.tsEnable FFT filter module in - set up
noiseThreshold: -45dBFiltering background noise - Add Adaptive Gain Control (AGC) to maintain signal stability
- exist
- Protocol Level Optimization::
- utilization
npm run configureSelect high frequency mode (8-12kHz) to avoid common environmental noise bands - exist
gibberlink.init()Enable CRC checksum retransmission mechanism in the
- utilization
- Hardware Configuration Recommendations::
- External directional microphone to enhance signal-to-noise ratio
- Adding acoustic foam to devices like the Raspberry Pi
- Avoid placing equipment near sources of constant noise such as air conditioners/fans
Test data shows that after enabling the full set of noise reduction scheme, the decoding success rate under 60dB background noise can be improved from 35% to 82%. developers can refer to the project wiki for theNoiseProfiling.mdPerform deep optimization.
This answer comes from the articlegibberlink: a demonstration project for efficient audio communication between two AI intelligencesThe
May not be reproduced without permission:AI productivity tools " How to eliminate the interference of environmental noise on AI audio communication protocols?
