podcast-splitter

You can split a podcast into chapters automatically by detecting silence gaps with configurable thresholds and minimum silence lengths, dividing the audio into distinct segments at those gaps.

Silence detection for audio segmentation works by scanning the audio file for gaps below a configurable volume threshold and matching a minimum silence length to identify split points.

Yes, you can use pydub to remove long pauses and dead air by detecting silence gaps that exceed a configured minimum length and exporting the remaining audio segments.

After splitting audio files by silence, you can export individual clips utilizing pydub, which supports standard audio format exports for the extracted segments.

Yes, you need to configure silence thresholds and minimum silence lengths to segment a podcast recording, as these parameters define what constitutes a gap for splitting audio into chapters.

A limitation of using silence detection for auto-chaptering is that it relies entirely on audio gaps; overlapping speech or continuous background noise may prevent accurate silence detection and segmentation.