Version 4.x.x+ Plus Features for Noise Mitigation

What Is Spectral Subtraction?

Spectral subtraction is a frequency-domain noise reduction method.

The main idea:

Estimate the noise spectrum and subtract it from the noisy signal’s spectrum to recover the clean signal.

It assumes that noise is additive and approximately stationary (not changing much over time).

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What is LMS?

The Least Mean Squares (LMS) algorithm is an adaptive filtering method used to minimize the difference between a desired signal and the output of a filter. It’s based on a simple gradient descent approach that learns and updates filter coefficients in real time.

🎯 Goal in Noise Reduction

In noise reduction, LMS tries to remove unwanted noise from a signal (like audio) while preserving the desired signal.

An adaptive filter (using LMS) takes the reference noise x[n], estimates the noise component in d[n], and subtracts it from d[n] to produce a cleaner signal y[n].

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What is RNN-Based Noise Reduction?

An RNN (Recurrent Neural Network) learns temporal dependencies in audio signals — it can remember context from previous time steps. This makes it ideal for noise reduction in speech and audio, where patterns evolve over time.

Instead of using a simple mathematical adaptation like LMS, an RNN learns from data how to separate speech from noise.

 Real-World Use

RNN-based noise reduction is used in:

• Zoom, Discord, Google Meet (RNNoise variants)
• Hearing aids
• Mobile phones
• Audio restoration and music mastering

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Yup some Learning Software going on. Automagic.

Go Flex. I said years ago if they could figure static dis-charges and noise on the band we would be really close to noise free. Yes filtering anything will always have delays nothing is instantaneous .

There is voice range and noise range just need separation the hardest thing to do.

Mathematically things are happening and getting there!.

Can`t wait to hear and see the results of all this.

73 de AA0KM