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Whisper can create an SRT or VTT subtitle file from a video on your Mac at no software cost. Install FFmpeg and OpenAI Whisper, run Whisper on the video, then check the transcript and timings. The result is a separate subtitle file—not captions automatically burned into the video.
What you need
- A Mac with Python available for installing and running Whisper. The project README says its codebase is expected to work with Python 3.8–3.11; check the current Whisper README if you use a newer version or installation fails.
- FFmpeg, which Whisper requires to read audio from video files.
- The video file you want to transcribe, with a path you can enter in Terminal.
Whisper’s code and model weights are released under the MIT License, according to the project README. That license does not determine your rights to the source video or its transcript.
Install FFmpeg and Whisper
- Open Terminal and install FFmpeg with Homebrew:
brew install ffmpeg - Install Whisper in your Python environment:
pip install -U openai-whisper
The README also documents installing from GitHub. See its installation section if the pip command does not work in your setup.
If a command is not found or installation fails, confirm that Homebrew and Python are installed and that Terminal is using the Python environment where Whisper was installed. For newer Python versions, consult the README rather than assuming compatibility from the documented 3.8–3.11 range.
Generate an SRT subtitle file
In Terminal, run Whisper with the video path and the SRT output option:
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whisper "input-video.mp4" --model turbo --output_format srt
Replace input-video.mp4 with the actual path to your video. For example, you can enter a full path in quotation marks if the file is not in Terminal’s current folder. The CLI accepts an input file path and supports an output directory option, so you can specify where the generated file should go:
whisper "/path/to/input-video.mp4" --model turbo --output_format srt --output_dir "/path/to/subtitles"
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Whisper writes a subtitle sidecar file; it does not automatically place captions over the video image. The CLI also supports VTT, text, TSV, JSON, and JSONL output. Choose SRT or VTT based on what your editor or publishing platform accepts. The available documentation does not establish import or burn-in steps for a particular editor.
Choose a model and language
Transcribe speech in its original language
The CLI defaults to the turbo model, which the project describes as an optimized version of large-v3 intended to run faster with minimal accuracy degradation. The README says the default turbo setting works well for transcribing English. This is not a Mac-specific speed or accuracy guarantee; the sources do not establish runtime for a given Mac or video.
Whisper can detect the spoken language, or you can set it explicitly with --language. For example:
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whisper "input-video.mp4" --model turbo --language Spanish --output_format srt
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Use the language name or code accepted by the CLI. Explicitly setting it can help when you know the speech language; otherwise, Whisper attempts language detection.
Translate non-English speech into English
For translation, select a multilingual model such as medium or large and add --task translate. For example:
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whisper "input-video.mp4" --model medium --task translate --output_format srt
Turbo is not trained for translation: when asked to translate, it returns speech in the original language. Translation is distinct from transcription, which retains the source language.
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Review the subtitles before using them
Automatic speech recognition can mishear or omit words, and a generated transcript is not guaranteed to be publication-ready. Play the video while checking the subtitle file, paying particular attention to:
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- Names, numbers, and technical terms.
- Missed speech, punctuation, and whether the wording matches what was said.
- Subtitle timing, line breaks, and whether text stays readable on screen.
The CLI offers experimental word-level timestamps and controls for maximum subtitle line width and line count. These can help with timing and layout, but do not remove the need to review the captions against the video.
Use the subtitle file with your video
Keep the SRT or VTT file alongside the video to use it as a separate subtitle track in a compatible editor or platform. If you want captions permanently visible in the image, you must take an additional step in a video editor or another tool that can burn subtitles into the video. The Whisper CLI creates subtitle files; it does not style or embed them in the finished video.
Quick Recap
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