jarvis-memory/skills/local-whisper-stt/SKILL.md

name, description

name	description
local-whisper-stt	Local speech-to-text transcription using Faster-Whisper. Use when receiving voice messages in Telegram (or other channels) that need to be transcribed to text. Automatically downloads and transcribes audio files using local CPU-based Whisper models. Supports multiple model sizes (tiny, base, small, medium, large) with automatic language detection.

Local Whisper STT

Overview

Transcribes voice messages to text using local Faster-Whisper (CPU-based, no GPU required).

When to Use

• User sends a voice message in Telegram
• Need to transcribe audio to text locally (free, private)
• Any audio transcription task where cloud STT is not desired

Models Available

Model	Size	Speed	Accuracy	Use Case
tiny	39MB	Fastest	Basic	Quick testing, low resources
base	74MB	Fast	Good	Default for most use
small	244MB	Medium	Better	Better accuracy needed
medium	769MB	Slower	Very Good	High accuracy, more RAM
large	1550MB	Slowest	Best	Maximum accuracy

Workflow

1. Receive voice message (Telegram provides OGG/Opus)
2. Download audio file to temp location
3. Load Faster-Whisper model (cached after first use)
4. Transcribe audio to text
5. Return transcription to conversation
6. Cleanup temp file

Usage

From Telegram Voice Message

When a voice message arrives, the skill:

1. Downloads the voice file from Telegram
2. Transcribes using the configured model
3. Returns text to the agent context

Manual Transcription

# Transcribe a local audio file
from faster_whisper import WhisperModel

model = WhisperModel("base", device="cpu", compute_type="int8")
segments, info = model.transcribe("/path/to/audio.ogg", beam_size=5)

for segment in segments:
    print(segment.text)

Configuration

Default model: base (good balance of speed/accuracy on CPU)

To change model, edit the script or set environment variable:

export WHISPER_MODEL=small

Requirements

• Python 3.8+
• faster-whisper package
• ~100MB-1.5GB disk space (depending on model)
• No GPU required (CPU-only)

Resources

scripts/

• transcribe.py - Main transcription script
• telegram_voice_handler.py - Telegram-specific voice message handler