whisper

Convert spoken language into written text across multiple languages.

Updated Apr 29, 2026
One-click install
npx skills add https://github.com/fikriaf/agentos --skill whisper-fikriaf
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: whisper
Source: https://github.com/fikriaf/agentos/tree/main/src/agentos/skills/mlops/models/whisper
Command: npx skills add https://github.com/fikriaf/agentos --skill whisper-fikriaf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai-whisper, transformers, torch, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies speech recognition, enabling users to transcribe, translate, and process audio with ease, regardless of language or location.

Core Features & Use Cases

  • Multilingual Support: Transcribe and translate audio in 99 languages.
  • Model Size Flexibility: Choose from 6 model sizes to balance speed and quality.
  • Use Case: Need to transcribe a meeting in French and translate it to English? Whisper can do it all in one go.

Quick Start

Install Whisper and transcribe your audio file using the command: whisper audio.mp3

Frequently Asked Questions about whisper

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I transcribe audio files into written text across multiple languages?

To transcribe audio files into written text across multiple languages, use Whisper to convert spoken language into text. It supports 99 languages for automated transcription and multilingual audio processing.

Can I use Whisper to translate a French audio recording to English text?

Yes, you can use Whisper to translate a French audio recording to English text. It provides a speech recognition and transcription service capable of translating audio in one go across 99 supported languages.

Do I need to install torch and transformers to run speech recognition tasks?

Yes, you need to install torch and transformers to run speech recognition tasks. These dependencies are required alongside openai-whisper to perform language detection and text generation.

What is the best way to balance transcription speed and quality for audio processing?

The best way to balance transcription speed and quality for audio processing is to choose from Whisper's 6 available model sizes. Selecting a smaller model increases processing speed, while a larger model improves text quality.

How does multilingual speech recognition handle automated transcription?

Multilingual speech recognition handles automated transcription by detecting spoken language and generating written text. Whisper processes the audio input directly to convert spoken words into accurate text across 99 languages.