FFmpeg’s ARNN (Audio Recurrent Neural Network) noise reduction filter is a powerful tool for improving audio quality in videos.
ARNN is a machine learning-based noise reduction algorithm that uses a recurrent neural network to identify and remove background noise from audio. The model has been trained on various types of noise and can effectively at “Remove background noise”, “Reduce wind noise”, “Minimize room echo”, “Clean up audio artifacts”, “Preserve speech quality”
The mix parameter (0.8 in this case) is crucial as it determines how aggressive the noise reduction is:
Higher values (closer to 1.0) provide stronger noise reduction but might affect speech quality
Lower values (closer to 0.0) provide gentler noise reduction while preserving more of the original audio
A value of 0.8 is a good balance between noise reduction and audio quality preservation
