whisper-transcribe-docker

Transcribe audio files to text locally in a Docker container using faster-whisper.

49|7|Updated Feb 8, 2026

Search Tags:#transcription #whisper #docker #audio processing #local #speech-to-text

Ready to run

npx skills add https://github.com/hc-tec/my-collection-skills --skill whisper-transcribe-docker

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: whisper-transcribe-docker
Source: https://github.com/hc-tec/my-collection-skills/tree/main/skills/whisper-transcribe-docker
Command: npx skills add https://github.com/hc-tec/my-collection-skills --skill whisper-transcribe-docker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and Dockerfile (resource) components.

What problem does it solve?

This Skill converts audio files into text transcripts locally, eliminating the need for external APIs or cloud services and ensuring data privacy.

Core Features & Use Cases

Local Transcription: Utilizes the faster-whisper model for accurate speech-to-text conversion directly on your machine.
Audio File Input: Accepts audio files (e.g., .m4a) as input.
Timestamp Generation: Optionally includes timestamps for each transcribed segment.
Use Case: After downloading a podcast episode as an audio file, use this Skill to generate a full transcript for easy searching and summarization.

Quick Start

Transcribe the audio file located at /work/out/audio.m4a using the small model and output the transcript to /work/out/audio.txt.

Frequently Asked Questions about whisper-transcribe-docker

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

FAQPage Schema

How do I transcribe audio files locally without using cloud APIs?▼

Local speech-to-text transcription processes your audio files directly on your machine using a Docker container, eliminating the need for external cloud APIs and ensuring complete data privacy. The Skill uses the faster-whisper library to convert inputs into text.

What's the best way to generate speech-to-text transcripts with timestamps for podcasts?▼

Generating speech-to-text transcripts with timestamps involves using the faster-whisper library to process audio files. This Skill optionally includes timestamps for each transcribed segment, producing detailed outputs ideal for searching and summarizing podcast episodes.

Can I use Docker to run faster-whisper for audio processing on my machine?▼

Yes, you can use Docker to run faster-whisper for audio processing on your machine. The Skill provides a Dockerfile and scripts to execute local speech-to-text transcription, supporting various model sizes and language detection for accurate results.

Does local transcription with faster-whisper support different model sizes and language detection?▼

Yes, local transcription with faster-whisper supports various model sizes and language detection. This allows you to balance transcription accuracy and processing performance based on your local hardware capabilities while handling audio file inputs.

How do I output transcribed text to a specific file from a Docker container?▼

To output transcribed text to a specific file from a Docker container, you specify the target file path in your execution command. This Skill can output the transcription results as plain text or JSON directly to a designated file on your machine.