Whisperer – free, open-source batch subtitle generator GUI (faster-whisper / whisper.cpp, offline, CPU or CUDA)
I got tired of running Whisper from the command line every time I wanted subtitles for a folder of videos, so I built a small desktop GUI around it. Drop files in, pick a model, press Start — .srt / .vtt / .txt / .json land next to your videos, optionally embedded into an .mkv/.mp4 copy as a soft subtitle track (FFmpeg stream copy, no re-encode).
GitHub: https://github.com/hclivess/whisperer (MIT, Python/PySide6, prebuilt Windows/Linux/macOS binaries in Releases — no Python needed)
What it does:
- Two engines: faster-whisper (CTranslate2) built in, or an external whisper.cpp whisper-cli (CUDA / Vulkan / Metal builds)
- All models: tiny → large-v3, large-v3-turbo, distil-large-v3, .en variants, or any faster-whisper HF repo id. Models download on first use.
- ~30 languages or auto-detect, plus translate to English
- Live queue: add files/folders or drag & drop while a run is going, reorder, pause/resume/stop. Live transcript panel as segments decode.
- Progress with ETA and × realtime speed per file and overall
- Subtitle layout control: max chars per line, max lines per cue, max cue duration — long segments get re-split on word timestamps with balanced lines (no orphan words)
- video.en.srt naming that Plex/Jellyfin/VLC auto-detect, custom output folder, overwrite guard
- Presets (Fast / Balanced / Accurate / Best) + save/load your own
- Sanity checks before starting (e.g. English-only model with a foreign language selected)
GPU: the one thing that always annoyed me with faster-whisper was CUDA library hell. The Model tab has a one-click Download CUDA libraries button that pulls cuBLAS 12 / cuDNN 9 / NVRTC from the official NVIDIA PyPI wheels (~1 GB, resumable) into a folder next to the app, and shows exactly what it found (GPU, driver, libs, whether CTranslate2 can use it). No PATH editing. Expect ~10–30× realtime with large-v3-turbo on a mid-range card, ~1–3× on CPU with small.en.
Everything runs locally, nothing leaves your machine.
It's a sibling of videer (https://github.com/hclivess/videer), my batch FFmpeg encoder, and shares the same queue/presets workflow.
Feedback, bug reports and feature requests welcome — especially from people with AMD/Intel GPUs or macOS, since I can mostly only test NVIDIA + CPU myself.
