whisper

Transcribe and translate audio files using OpenAI's Whisper model.

Updated Jul 3, 2026
One-click install
npx skills add https://github.com/LynxLabVN/office-agent --skill whisper-lynxlabvn
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: whisper
Source: https://github.com/LynxLabVN/office-agent/tree/main/agent-core/optional-skills/mlops/whisper
Command: npx skills add https://github.com/LynxLabVN/office-agent --skill whisper-lynxlabvn

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill simplifies the process of transcribing and translating audio into text, making it easier to access and analyze spoken content.

Core Features & Use Cases

  • Speech-to-Text: Convert spoken language into written text, supporting 99 languages.
  • Translation: Translate audio to English from any of the supported languages.
  • Language Identification: Automatically detect the language of the audio.
  • Use Case: Ideal for automating transcription in podcasts, meetings, and multilingual audio content.

Quick Start

Use the whisper skill to transcribe the audio file 'meeting.mp3'.

Frequently Asked Questions about whisper

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

FAQPage Schema
How do I transcribe multilingual audio files to text using OpenAI Whisper?

Audio transcription to text using OpenAI Whisper works by processing your audio files with the Whisper model to automatically detect and transcribe speech across 99 supported languages.

Can I translate podcast audio to English text from any language?

You can translate podcast audio to English from any of the 99 supported languages by using the Whisper model to process the audio file and output the translated English text.

Do I need PyTorch and Transformers installed for speech-to-text processing?

Yes, speech-to-text processing requires openai-whisper, transformers, and torch libraries to be installed in your environment to run the model and execute the transcription tasks.

Does Whisper automatically detect the spoken language in an audio file?

Whisper provides language identification capabilities, automatically detecting the spoken language present in the audio file before transcribing or translating it into the desired text output.

What is the best way to automate meeting transcription for multilingual audio content?

Automating meeting transcription for multilingual audio content is best handled by using the Whisper model to process your meeting audio files, converting spoken language into written text efficiently.

Are there limitations when processing audio files with Whisper for speech-to-text conversion?

Limitations of speech-to-text conversion with Whisper include dependency on having openai-whisper, transformers, and torch libraries properly configured, and audio files must be clear enough for accurate multilingual processing.