Whisply
Whisply is free software for transcribing, translating, annotating and creating subtitles from audio and video with Whisper models.
What Whisply is
Whisply is free software for transcribing, translating, annotating and creating subtitles from audio and video with Whisper models. It provides both a command-line interface and a browser app that runs locally. Batch processing accepts individual files, folders, URLs and lists of inputs. Processing stays on the user’s hardware, with implementations selected for CPU, Nvidia GPU or Apple Silicon MLX. Exports include JSON, RTTM, TXT, HTML, SRT, VTT and WebVTT. Word-level speaker annotation uses whisperX and pyannote, requiring a Hugging Face access token and acceptance of the pyannote model conditions. The project describes Whisply as a research tool for work such as qualitative interviews and group discussions. It is MIT licensed, permitting use, copying, modification, publication and distribution under the stated conditions. Setup requires FFmpeg and Python 3.10 through a version below 3.14. The README notes that overlapping speakers can reduce diarization accuracy and that built-in word alignment supports ten languages.
Good
- Runs processing on your own hardware
- Command-line and local browser interfaces
- Batch inputs include files, folders and URLs
- Exports subtitles and multiple data formats
- Supports CPU, Nvidia GPU and Apple Silicon
Watch out
- Requires FFmpeg and Python
- Speaker annotation needs a Hugging Face token
- Overlapping speech can reduce diarization accuracy
- Word alignment supports ten languages
Who it suits
Whisply suits researchers and others processing interviews or group discussions who want local audio and video transcription. It fits users comfortable with command-line or local browser tools and the listed requirements.
Verdict
Whisply offers local Whisper-based transcription, translation, annotation and subtitle export with flexible input handling. Its setup requirements and speaker-annotation conditions should be considered before use.
The facts
Each one read from Whisply's own pages, with the date it was checked.
What it does
- Annotation limitation
- The README notes diarization may be inaccurate when speakers talk at the same time and lists built-in word-alignment support for ten languages.checked 12 Oct 2026
- Batch input
- It can process individual files, folders, URLs, and lists of files.checked 12 Oct 2026
- Exports
- Export formats include JSON, RTTM, TXT, HTML, SRT, VTT, and WebVTT.checked 12 Oct 2026
- Hardware
- It selects implementations for CPU, Nvidia GPU, or Apple Silicon MLX processing.checked 12 Oct 2026
- Hardware support
- It selects faster-whisper for CPU or Nvidia GPU processing and mlx-whisper for Apple M1–M5 devices.checked 12 Oct 2026
- Intended use
- The project metadata describes Whisply as a research tool, including for transcribing qualitative interviews and group discussions.checked 12 Oct 2026
- Interfaces
- Whisply offers a command-line interface and an optional browser app that runs at a local URL.checked 12 Oct 2026
- Known limitation
- The README notes that speaker diarization can be inaccurate when multiple speakers talk at the same time.checked 12 Oct 2026
- License
- The package metadata identifies the software as MIT licensed.checked 12 Oct 2026
- Privacy
- The project metadata says processing runs entirely on the user's own hardware to protect sensitive research data.checked 12 Oct 2026
- Processing
- It supports batch processing of files, folders, URLs, and lists of inputs.checked 12 Oct 2026
- Purpose
- Whisply transcribes, translates, annotates, and creates subtitles for audio and video files using Whisper models.checked 12 Oct 2026
- Requirements
- The README lists FFmpeg and Python 3.10 through below 3.14 as requirements.checked 12 Oct 2026
- Speaker annotation
- Word-level speaker annotation uses whisperX and pyannote and requires a Hugging Face access token and acceptance of the pyannote model terms.checked 12 Oct 2026
- Speaker annotations
- Word-level speaker annotation uses whisperX and pyannote and requires a Hugging Face access token and acceptance of the model conditions.checked 12 Oct 2026
- Speaker identification
- Yeschecked 22 Sep 2026
- Subtitle export
- other formatschecked 22 Sep 2026
- Subtitles and exports
- It can create SRT, VTT, and WebVTT subtitles and export JSON, RTTM, text, annotated text, and HTML.checked 12 Oct 2026
Money
- Free plan
- Yeschecked 22 Sep 2026
The company
- Makers
- The package metadata names Thomas Schmidt and Renat Shigapov as authors.checked 12 Oct 2026
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