MinusPod

What it is

Transcription - Local transcription with faster-whisper (Whisper) or NVIDIA Parakeet TDT 0.6B v3 on GPU or CPU, or a remote OpenAI-compatible API - Works with whisper.cpp, Groq, OpenAI Whisper, and OpenVINO (Intel GPU)

What the README says it does

• An LLM finds ads in the transcript, a second pass verifies the cut, and an optional reviewer confirms or adjusts each boundary. How it works
• Audio evidence backs the transcript: loudness and DAI transitions, a cross-fetch diff against a second download, per-feed jingle cues, and the publisher's own transcript. Audio cues, Transcript differential
• Each detection gets a category (sponsor, cross-promo, self-promo, intro/outro) and a per-feed action: remove, beep, keep, or mark as a skippable chapter
• Low-confidence cuts wait in a review queue with a waveform editor; your corrections become cross-episode patterns so repeat sponsors are caught without another LLM call
• Five per-feed processing modes, from full detection to pass-through

From the project’s README.

Where the decision sits

MinusPod calls the hosted decision API rather than running its own weights. That keeps the project small and means its behaviour moves whenever the vendor ships a new model version. It also means an API key and a network round trip sit in the path of every decision.

Models it references: Jev.

How active it is

Created 2025-11-26, last pushed 2026-11-02, 521 stars and 53 forks when we read it on 2026-11-02. Everything in this category is weeks old at most, so a stale push date means something different here than it would on a mature project. Check the repository before you depend on it.