Noise Detection

To reduce background noise automatically, the pipeline includes a simple noise-region detection step. This replaces the manual process of selecting a “quiet” section of audio (as you might do in Audacity).

Region Detection

The recording is divided into short, overlapping windows (typically 50 ms). For each window, two measurements are taken:

• Loudness (RMS amplitude) → Quieter windows are more likely to contain background noise only.
• Band energy ratio → The fraction of spectral energy within the expected signal band (for bat recordings, typically ~3.5–6.5 kHz after time expansion).

The band energy ratio is then used to identify the type of signal in the window:

• Low ratio → broadband noise / hiss
• High ratio → structured signal (e.g. bat calls)

A window is considered likely noise if it is both:

• Relatively quiet compared to the rest of the recording, and
• Relatively low in energy within the target band

Thresholds are determined using percentiles, so the detection adapts to each recording rather than relying on fixed values.

From Windows to Regions

Neighbouring “noise” windows are merged into longer regions, and only regions above a minimum duration are kept. These regions are then used as the noise profile for subsequent noise reduction. An example waveform, with noise regions highlighted, is shown below: