A high-performance, privacy-first tool for local speech-to-text transcription using NVIDIA GPU acceleration.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install faster-whisper-gpu
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install faster-whisper-gpu using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Faster Whisper GPU?
Faster Whisper GPU is a specialized skill designed for high-efficiency audio transcription. By leveraging NVIDIA CUDA technology and the optimized Faster Whisper implementation, it provides a significantly faster alternative to standard Whisper models without compromising on accuracy. This tool is part of the growing ecosystem of Openclaw Skills, enabling developers and researchers to process audio data entirely on their local hardware.
The primary value of this skill lies in its combination of speed, privacy, and cost-effectiveness. Since all processing occurs locally, sensitive data never leaves your environment. It supports 99 languages and offers various model sizes, ranging from the lightweight tiny model for speed to the robust large-v3 for maximum precision, making it a versatile asset for any speech processing pipeline.
Faster Whisper GPU Use Cases
- Transcribing long-form recordings like podcasts or meetings with high accuracy using local resources.
- Generating SRT or VTT subtitle files for video content with precise word-level timestamps.
- Translating foreign language audio directly into English text without external API calls.
- Deploying transcription workflows in privacy-sensitive environments where data cannot be uploaded to the cloud.
- Batch processing large volumes of audio files efficiently by leveraging Openclaw Skills and dedicated GPU hardware.
How Faster Whisper GPU Works
- The user provides an audio file in a supported format such as MP3, WAV, or FLAC.
- The system initializes the Whisper model, defaulting to NVIDIA GPU (CUDA) for accelerated performance.
- The audio is processed through the Faster Whisper engine, which uses CTranslate2 for fast inference.
- If enabled, a VAD (Voice Activity Detection) filter identifies and skips silent segments to reduce processing time.
- The skill segments the audio and transcribes the speech into the specified language or auto-detects it.
- The final output is generated in the requested format, such as plain text, JSON, or subtitle files.
Faster Whisper GPU Setup
To get started with this skill, ensure you have an NVIDIA GPU with CUDA support and Python 3.8+ installed. Follow these steps to prepare your environment:
# Install the necessary Python packages
pip install faster-whisper torch
# Verify that your GPU is correctly recognized by PyTorch
python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"
Faster Whisper GPU Data Schema & Taxonomy
The skill manages audio data and produces structured outputs as detailed below:
| Feature | Specification |
|---|---|
| Supported Inputs | MP3, WAV, FLAC, OGG, M4A |
| Available Outputs | TXT, SRT, JSON, VTT |
| Model Storage | Models are cached locally in ~/.cache/huggingface/hub/ |
| Metadata Capture | Includes language detection probability, start/end timestamps, and word-level confidence |
| Compute Types | Supports int8, float16, and float32 precision for varying hardware capabilities |
Faster Whisper GPU Advanced Features
- Voice Activity Detection (VAD) with customizable parameters to filter out silence.
- Subtitle generation with word-level timestamps for perfectly synced captions.
- Direct translation task support to convert any of the 99 supported languages into English.
- Hotword boosting to improve recognition accuracy for specific domain terminology.
- Flexible computation precision settings to optimize for either VRAM usage or transcription speed within the Openclaw Skills framework.
SKILL.md
Loading
Related Openclaw Skills
Ant Design Skill
A comprehensive front-end design skill for building professional React interfaces using Ant Design components, layouts, and v5 design tokens.
Passo - Remote Browser Access
Passo enables secure remote browser access on your server to handle manual logins, 2FA, and captchas within Openclaw Skills environments.
gcloud
A professional automation skill that enables AI agents to manage Google Cloud Platform resources safely using the official gcloud CLI.
Firestore
A powerful tool for managing Google Cloud Firestore databases directly through the REST API using curl and gcloud authentication.
SonarQube Analyzer
An AI-powered tool for analyzing self-hosted SonarQube projects, retrieving issues, and providing automated code suggestions.
Stripe CLI
A secure interface for managing Stripe CLI operations, webhook forwarding, and sandbox testing within Openclaw Skills.
Featured*
