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Audio & Voice AI

Whisper Standalone Win

Whisper Standalone Win is a collection of standalone command-line executables for OpenAI Whisper and Faster-Whisper that process audio or video for speech transcription and translation.

Independent OpenViST project profile, based on linked sources.

Whisper Standalone Win — OpenViST project profile in Audio & Voice AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you want standalone Whisper or Faster-Whisper executables for command-line transcription or translation, particularly for media and batch workflows.

Who it is for

  • People who want to run Whisper-based speech recognition from a command line without setting up Python.
  • Subtitle editors and media workflows that can use the listed command-line tools.
  • Users handling folders of media or needing speaker diarization, voice-activity detection or vocal extraction.

Documented uses

  • Transcribe a single audio or video file with a selected language and model.
  • Translate media using the documented task option.
  • Process a folder recursively in a batch workflow.
  • Use Faster-Whisper-XXL options for vocal extraction, voice-activity detection and speaker diarization.
Before you choose

Requirements & limits

Executables and libraries are available through the repository's Releases page. The repository describes x86-64 builds with distinct operating-system requirements; check the requirements for the specific build.

  • Build requirements differ: Faster-Whisper lists Windows 7, Linux 5.4 and macOS 10.15 or later; Faster-Whisper-XXL lists Windows 10 and Linux 5.15 or later; standalone Whisper lists Windows 10 or later.
  • The README describes the standalone Faster-Whisper version as deprecated and directs users to Faster-Whisper-XXL.
  • Faster-Whisper-XXL includes optional vocal extraction, multiple VAD methods and speaker diarization.
  • Models can download automatically or be downloaded manually; the README recommends medium or larger for decent transcription.
  • CUDA detection selects GPU use automatically.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Transcribe one video with Faster-Whisper-XXL

Run the README's example for transcribing a video with a chosen language, model and output directory.

Before you start

  • An x86-64 system meeting the Faster-Whisper-XXL requirements: Windows 10 or later, or Linux 5.15 or later.
  • The Faster-Whisper-XXL executable from the repository's Releases page.
  • A video file and a model; models can download automatically or be downloaded manually.

Steps

  1. Download the executable from Releases.

  2. Open a command-line interface in the executable's location.

  3. Run the documented example, replacing the example file path as needed: faster-whisper-xxl.exe "D:\videofile.mkv" --language English --model medium --output_dir source.

Expected outcome

The command requests transcription of the specified video using English and the medium model, with output directed to the source directory.

Guide limitations

  • The README recommends using a model no smaller than medium for decent transcription.
  • GPU use is selected automatically when CUDA is detected.
Source-based practical guide

Submit a folder for recursive batch transcription

Use the documented Faster-Whisper-XXL folder example with recursive batch processing.

Before you start

  • An x86-64 system meeting the Faster-Whisper-XXL requirements: Windows 10 or later, or Linux 5.15 or later.
  • The Faster-Whisper-XXL executable from the repository's Releases page.
  • A folder containing media files and a model.

Steps

  1. Download the executable from Releases.

  2. Open a command-line interface in the executable's location.

  3. Run the documented example, substituting the folder path if needed: faster-whisper-xxl.exe "D:\Folder" -l en -m turbo --sentence --batch_recursive.

Expected outcome

The command requests recursive batch processing of the specified folder, using English, the turbo model and sentence output.

Guide limitations

  • The example's flags and model are reproduced as shown in the README; the project labels some Faster-Whisper settings and tweaks experimental.
  • GPU use is selected automatically when CUDA is detected.
Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
15 October 2026
Original website title
Purfview/whisper-standalone-win · Official homepage title · retained in its source language