whisper

Transcribe spoken audio into text using OpenAI's Whisper model.

4|Updated Apr 19, 2026

Search Tags:#speech recognition #transcription #audio processing #multilingual #ASR

Ready to run

npx skills add https://github.com/ragnarokhaa/hermes --skill whisper-ragnarokhaa

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: whisper
Source: https://github.com/ragnarokhaa/hermes/tree/main/hermes-cerul-tech-news-package/hermes-cerul-tech-news-package/hermes-agent/skills/mlops/models/whisper
Command: npx skills add https://github.com/ragnarokhaa/hermes --skill whisper-ragnarokhaa

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 addresses the challenge of converting spoken words into written text with high accuracy, supporting multiple languages and providing versatile transcription options.

Core Features & Use Cases

Multilingual Speech Recognition: Transcribe audio in 99 languages with high accuracy.
Versatile Applications: Use for transcription, translation, language identification, and more.
Use Case: Automate the transcription of podcasts, meetings, or other audio content to improve accessibility and efficiency.

Quick Start

Use the whisper skill to transcribe the audio file 'meeting_recording.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 to text using OpenAI's Whisper model?▼

You transcribe audio to text using OpenAI's Whisper model by feeding spoken audio files into the transcription process, which supports speech-to-text conversion for podcast and meeting recordings. It supports 99 languages for high-accuracy multilingual speech recognition.

Can I translate spoken audio from multiple languages into English text?▼

Yes, you can translate spoken audio into English text. The multilingual speech recognition process supports 99 languages and provides direct translation to English alongside standard transcription and language identification features.

Do I need PyTorch and Transformers installed to run Whisper speech recognition?▼

Yes, running Whisper speech recognition requires PyTorch and Transformers installed in your environment. These dependencies provide the underlying deep learning framework needed to load and execute the OpenAI Whisper ASR model.

What's the best way to automate podcast transcription for multilingual audio?▼

Automating podcast transcription for multilingual audio is best handled by using a dedicated ASR model like Whisper. It processes 99 languages with high accuracy, converting spoken audio content into written text to improve accessibility.

Does Whisper support language identification for unknown audio recordings?▼

Yes, Whisper supports language identification for unknown audio recordings. The speech-to-text model automatically detects the spoken language from the 99 supported languages during the audio processing and transcription workflow.

What are the limitations of using local ASR models for meeting transcription?▼

Using local ASR models for meeting transcription requires significant computational resources due to PyTorch and Transformers dependencies. Large audio files may process slowly, and the accuracy depends heavily on the audio clarity and the specific Whisper model variant utilized.