openai-whisper

You can transcribe audio offline by running the Whisper CLI locally, which eliminates cloud dependencies and preserves privacy. This approach processes speech-to-text directly on your machine, reducing latency and ensuring sensitive data never leaves your local filesystem.

Yes, Whisper CLI supports offline transcription for podcasts, interviews, and meeting notes. It processes audio recordings locally, making it highly suitable for privacy-conscious workflows where uploading audio files to cloud-based speech-to-text services is restricted.

Whisper CLI transcribes local audio files, such as MP3s, and saves the resulting text to your local filesystem. You can process files by specifying the path, selecting a model, and choosing an output format like plain text or subtitles for your speech-to-text results.

Yes, Whisper CLI supports outputting local speech-to-text results in both plain text and subtitle formats. You can specify your desired output format and directory using CLI arguments, and the system saves the transcribed files directly to your local filesystem.

No, an internet connection is not required for the actual speech-to-text transcription because Whisper CLI runs locally. An initial connection may be needed to download the selected model, which is then cached locally for faster offline reuse during subsequent transcription tasks.

You select a specific model when transcribing audio by including the `--model` argument in your Whisper CLI command, such as `whisper /path/file.mp3 --model medium`. This allows you to balance transcription accuracy and processing speed based on your local hardware capabilities.