whisper

Name: whisper
Availability: InStock
Author: quiznat

Transcribe multilingual audio into text with optional English translation.

Updated Mar 31, 2026

Search Tags:#translation #transcription #whisper #multilingual #audio-processing #speech-recognition

Ready to run

npx skills add https://github.com/quiznat/Hermes_Sapho --skill whisper-quiznat

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: whisper
Source: https://github.com/quiznat/Hermes_Sapho/tree/main/.hermes/skills/mlops/models/whisper
Command: npx skills add https://github.com/quiznat/Hermes_Sapho --skill whisper-quiznat

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Whisper enables automatic transcription and understanding of spoken language across 99 languages, including translation to English and quick language identification, simplifying audio data workflows.

Core Features & Use Cases

Speech-to-text transcription across 99 languages for accurate transcripts.
Translation to English for cross-language content comprehension.
Language identification to determine source language and categorize audio.
Use Case: Transcribe podcasts, meetings, lectures, or video captions to generate searchable text.

Quick Start

Install the whisper package and run a sample transcription on an audio file to see results.

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 into text for podcasts or meetings?▼

Speech-to-text transcription processes audio files to generate searchable text across 99 languages. It identifies the spoken language automatically and transcribes podcasts, meetings, and lectures into readable text using the Whisper runtime.

Can I translate spoken audio to English while transcribing?▼

Translation to English is supported alongside multilingual speech recognition. The Skill identifies the spoken source language and provides an English translation output, enabling cross-language content comprehension for audio data workflows.

Do I need Python and specific runtime dependencies to run Whisper speech recognition?▼

Yes, Python is required along with Whisper runtime dependencies including openai-whisper, transformers, and torch. These packages provide the speech recognition processing logic and model execution environment required for audio transcription tasks.

What is the best way to identify the language of an audio file?▼

Language identification detects the source language of an audio file automatically. By running audio through Whisper speech recognition, you can categorize and label audio files by their detected spoken language across 99 supported languages.

Does Whisper transcription support both CPU and GPU execution?▼

Yes, Whisper transcription supports multiple model sizes for CPU or GPU execution. You select the appropriate model size based on available hardware to optimize audio processing speed and speech-to-text generation performance.