Subtitle Edit

the subtitle editor :)

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Speech to Text

Subtitle Edit can automatically transcribe audio to text using Whisper-based and other modern speech recognition engines.

• Menu: Video → Speech to text…

Supported Engines

Engine	Platform	Notes
Whisper CPP	Windows, Linux, macOS	Local CPU engine. On Windows the cuBLAS (NVIDIA CUDA) and Vulkan GPU backends can also be selected from the Whisper CPP backend dropdown.
Purfview Faster Whisper XXL	Windows, Linux	Fast local engine, often used with NVIDIA CUDA
Whisper CTranslate2	Windows, Linux (x64), macOS (Apple Silicon)	CPU / NVIDIA CUDA depending on installation; CUDA requires CUDA 12.x
MLX Whisper	macOS (Apple Silicon)	Runs Whisper on the Apple GPU / Neural Engine via Apple’s MLX. Not downloaded by Subtitle Edit — install the mlx-whisper Python package yourself (see notes below)
Whisper Const-me	Windows	DirectX-based engine
Whisper OpenAI	All	Python-based OpenAI Whisper workflow
OpenAI Compatible Server	All	Connect to any OpenAI-compatible speech-to-text endpoint
Qwen3 ASR CPP	Windows, Linux	Local Qwen3 ASR engine with downloadable GGUF models
Crisp ASR	Windows, Linux, macOS	Single engine with selectable backends: Parakeet, Canary, Cohere, Fire Red, GLM, Granite, Qwen3, Mega, Omni, Kyutai

Engines and models are downloaded automatically on first use.

SE5 Engine Notes

• Whisper CPP is shown as a single entry; the CPU / cuBLAS / Vulkan backends are selected from a secondary dropdown when Whisper CPP is selected.
• Qwen3 ASR CPP includes 0.6B and 1.7B model options, plus a forced-aligner model used for timing workflows.
• Crisp ASR is exposed as one engine that wraps multiple backends (Parakeet, Canary, Cohere, Fire Red, GLM, Granite, Qwen3, Mega, Omni, Kyutai). Pick the backend from the Crisp ASR backend dropdown.
• MLX Whisper (Apple Silicon Macs) is not bundled or auto-downloaded — it drives Apple’s mlx-whisper Python package. Install it once with pip3 install mlx-whisper (or pipx install mlx-whisper); models download from Hugging Face on first use. Subtitle Edit detects the install by finding a Python that can import mlx_whisper — it probes Homebrew, python.org, pyenv and system interpreters, and (for pipx / virtual-env / conda installs, which isolate the package) reads the mlx_whisper command found on your PATH or at ~/.local/bin/mlx_whisper to locate the matching interpreter. If it reports “not found” after a pipx/venv install, make sure which mlx_whisper resolves.
• A Forced aligner option is shown for Crisp ASR backends and exposes the built-in aligner, Canary CTC, Qwen3, and the wav2vec2 zoo (12 language-specific CTC aligners that run on top of any Crisp ASR backend).
• Several newer engines support automatic language selection.
• Each engine can have separate advanced command-line parameters.

How to Use

1. Open a video file in Subtitle Edit
2. Go to Video → Speech to text…
3. Select an Engine from the dropdown
4. Select a Model (larger models usually improve accuracy but take more time and disk space)
5. Select the Language of the audio, or use auto-language when the selected engine supports it
6. Optionally enable:
   • Translate to English — Translate non-English audio to English
   • Adjust timings — Post-process timing using waveform data
   • Post-processing — Fix casing, merge lines, add periods, etc.
7. Click Transcribe

Models

Each engine has its own set of models. Common model sizes:

• tiny — Fastest, least accurate
• base — Good balance for quick work
• small — Better accuracy
• medium — High accuracy
• large / large-v2 / large-v3 — Best accuracy, slowest

Models ending in .en are English-only and perform better for English audio.

Batch Mode

Transcribe multiple video files at once:

1. Click Batch mode
2. Add video files
3. Click Transcribe
4. Results are saved as .srt files next to the video files

Advanced Settings

Click the Advanced button to configure custom command-line arguments for the Whisper engine:

• Use VAD (voice activity detection) for better timing
• Highlight spoken words in the transcript
• Adjust temperature or other model parameters

Advanced settings are stored per engine, so you can keep separate parameters for Whisper CPP, Qwen3 ASR, Crisp ASR, and other engines.

Post-Processing Settings

Click the Post-processing button to configure:

• Adjust timings (using waveform peak data)
• Fix short durations
• Fix casing
• Add periods
• Merge short lines
• Split long lines
• Change underline to color (useful for highlight spoken words)

Console Log

The console log at the bottom shows real-time output from the Whisper process, useful for debugging issues.

Tips

• For NVIDIA GPU users, use the Whisper CPP cuBLAS backend or Purfview Faster Whisper XXL for fastest transcription
• If you get “CUDA out of memory” errors, try a smaller model
• The --standard parameter is automatically added for Purfview Faster Whisper XXL
• You can re-download an engine by right-clicking the engine area
• If an engine executable has gone missing (typically quarantined by antivirus software), Subtitle Edit detects it when transcription starts, names the missing file, and offers to re-download the engine
• If a new engine has no model installed yet, let Subtitle Edit download both the engine and the selected model before starting transcription