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whisper-daemon

Fast audio transcription via FGP daemon - 3-10x faster than spawning whisper per file. Use when user needs to transcribe audio, convert speech to text, generate subtitles, or translate audio. Triggers on "transcribe audio", "speech to text", "whisper", "generate subtitles", "transcription", "audio to text".

personAuthor: jakexiaohubgithub
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FGP Whisper Daemon

Ultra-fast audio transcription with persistent Whisper model. 3-10x faster than spawning whisper per file.

Why FGP?

| Operation | FGP Daemon | whisper CLI | Speedup | |-----------|------------|-------------|---------| | Model load | 0ms (cached) | ~5-30s | ∞ | | Short audio (<30s) | 1-5s | 10-35s | 3-10x | | Long audio (5min) | 15-45s | 60-180s | 3-4x | | Batch (10 files) | 30-90s | 300-600s | 5-10x |

Persistent daemon keeps model loaded in memory (GPU or CPU).

Installation

brew install fast-gateway-protocol/tap/fgp-whisper

# Or
bash ~/.claude/skills/fgp-whisper/scripts/install.sh

Prerequisites

For local inference, install whisper.cpp or openai-whisper:

# whisper.cpp (recommended - faster, less memory)
brew install whisper-cpp

# Or Python whisper
pip install openai-whisper

# For GPU acceleration (NVIDIA)
pip install openai-whisper[cuda]

# For Apple Silicon (uses Metal)
# whisper.cpp automatically uses Metal

For API-based transcription:

export OPENAI_API_KEY="sk-..."

Usage

Basic Transcription

# Transcribe audio file
fgp whisper transcribe audio.mp3

# Transcribe video file (extracts audio)
fgp whisper transcribe video.mp4

# Output to file
fgp whisper transcribe audio.mp3 --output transcript.txt

# With timestamps
fgp whisper transcribe audio.mp3 --timestamps

# Specific language
fgp whisper transcribe audio.mp3 --language en
fgp whisper transcribe audio.mp3 --language es
fgp whisper transcribe audio.mp3 --language ja

Output Formats

# Plain text (default)
fgp whisper transcribe audio.mp3 --format txt

# JSON with segments
fgp whisper transcribe audio.mp3 --format json

# SRT subtitles
fgp whisper transcribe audio.mp3 --format srt

# VTT subtitles
fgp whisper transcribe audio.mp3 --format vtt

# TSV (tab-separated)
fgp whisper transcribe audio.mp3 --format tsv

# All formats
fgp whisper transcribe audio.mp3 --format all

Models

# List available models
fgp whisper models

# Use specific model
fgp whisper transcribe audio.mp3 --model tiny      # Fastest, least accurate
fgp whisper transcribe audio.mp3 --model base      # Fast, good accuracy
fgp whisper transcribe audio.mp3 --model small     # Balanced (default)
fgp whisper transcribe audio.mp3 --model medium    # Better accuracy
fgp whisper transcribe audio.mp3 --model large     # Best accuracy, slowest
fgp whisper transcribe audio.mp3 --model large-v3  # Latest large model

# English-only models (faster)
fgp whisper transcribe audio.mp3 --model tiny.en
fgp whisper transcribe audio.mp3 --model base.en
fgp whisper transcribe audio.mp3 --model small.en
fgp whisper transcribe audio.mp3 --model medium.en

# Download model
fgp whisper download large-v3

# Check loaded model
fgp whisper status

Translation

# Translate to English
fgp whisper translate audio.mp3

# Translate from specific language
fgp whisper translate audio.mp3 --from es

# Translate with subtitles
fgp whisper translate video.mp4 --format srt

Language Detection

# Detect language
fgp whisper detect audio.mp3

# Get confidence scores
fgp whisper detect audio.mp3 --verbose

Batch Processing

# Transcribe multiple files
fgp whisper batch *.mp3

# Transcribe folder
fgp whisper batch ./audio --output ./transcripts

# With specific format
fgp whisper batch ./audio --format srt --output ./subtitles

# Parallel processing
fgp whisper batch ./audio --parallel 4

Real-time / Streaming

# Transcribe from microphone
fgp whisper stream

# Stream to file
fgp whisper stream --output live.txt

# Stream with translation
fgp whisper stream --translate

# Set audio device
fgp whisper stream --device 1

Timestamps & Segments

# Word-level timestamps
fgp whisper transcribe audio.mp3 --word-timestamps

# Segment by sentence
fgp whisper transcribe audio.mp3 --segment sentence

# Custom segment length
fgp whisper transcribe audio.mp3 --segment-length 30

# Get specific time range
fgp whisper transcribe audio.mp3 --start 00:01:30 --end 00:05:00

Speaker Diarization

# Identify speakers
fgp whisper transcribe audio.mp3 --diarize

# Set number of speakers
fgp whisper transcribe audio.mp3 --diarize --speakers 2

# With speaker labels
fgp whisper transcribe audio.mp3 --diarize --speaker-labels "Alice,Bob"

Audio Processing

# Normalize audio before transcription
fgp whisper transcribe audio.mp3 --normalize

# Reduce noise
fgp whisper transcribe audio.mp3 --denoise

# Specific sample rate
fgp whisper transcribe audio.mp3 --sample-rate 16000

# Mono conversion
fgp whisper transcribe audio.mp3 --mono

OpenAI API

# Use OpenAI API instead of local model
fgp whisper transcribe audio.mp3 --api openai

# With specific model
fgp whisper transcribe audio.mp3 --api openai --model whisper-1

# Set API key
export OPENAI_API_KEY="sk-..."

Prompting

# Initial prompt for context
fgp whisper transcribe audio.mp3 --prompt "This is a podcast about technology."

# Technical vocabulary
fgp whisper transcribe audio.mp3 --prompt "Kubernetes, Docker, PostgreSQL, GraphQL"

# Prompt from file
fgp whisper transcribe audio.mp3 --prompt-file context.txt

Performance Tuning

# CPU threads
fgp whisper transcribe audio.mp3 --threads 8

# GPU acceleration
fgp whisper transcribe audio.mp3 --device cuda

# Apple Metal (default on macOS)
fgp whisper transcribe audio.mp3 --device metal

# Beam size (accuracy vs speed)
fgp whisper transcribe audio.mp3 --beam-size 5

# Temperature (randomness)
fgp whisper transcribe audio.mp3 --temperature 0

Available Commands

| Command | Description | Example | |---------|-------------|---------| | transcribe | Transcribe audio | fgp whisper transcribe audio.mp3 | | translate | Translate to English | fgp whisper translate audio.mp3 | | detect | Detect language | fgp whisper detect audio.mp3 | | batch | Batch transcribe | fgp whisper batch *.mp3 | | stream | Real-time from mic | fgp whisper stream | | models | List models | fgp whisper models | | download | Download model | fgp whisper download large-v3 | | status | Daemon status | fgp whisper status |

Supported Formats

Audio:

  • MP3, WAV, FLAC, OGG, M4A, AAC, WMA, AIFF

Video (audio extracted):

  • MP4, MKV, AVI, MOV, WebM, FLV

Output:

  • TXT, JSON, SRT, VTT, TSV

Supported Languages

Whisper supports 99 languages including:

| Code | Language | Code | Language | |------|----------|------|----------| | en | English | es | Spanish | | fr | French | de | German | | it | Italian | pt | Portuguese | | ru | Russian | ja | Japanese | | ko | Korean | zh | Chinese | | ar | Arabic | hi | Hindi |

Full list: fgp whisper languages

Example Workflows

Podcast transcription

# Transcribe podcast with speaker diarization
fgp whisper transcribe podcast.mp3 \
  --model medium \
  --diarize \
  --format json \
  --output podcast_transcript.json

Video subtitles

# Generate SRT subtitles for video
fgp whisper transcribe video.mp4 \
  --format srt \
  --output video.srt

# For non-English video, translate subtitles
fgp whisper translate video.mp4 \
  --format srt \
  --output video_en.srt

Meeting notes

# Transcribe meeting with timestamps
fgp whisper transcribe meeting.m4a \
  --model small \
  --timestamps \
  --diarize \
  --output meeting_notes.txt

Batch process interviews

# Transcribe all interviews
fgp whisper batch ./interviews \
  --model medium \
  --format json \
  --diarize \
  --parallel 2 \
  --output ./transcripts

Live captioning

# Real-time captions from microphone
fgp whisper stream --model base.en

Troubleshooting

Model not found

Error: Model 'large-v3' not found

Download model: fgp whisper download large-v3

Out of memory

Error: CUDA out of memory

Use smaller model: --model small or use CPU: --device cpu

Audio format error

Error: Unsupported audio format

Install ffmpeg: brew install ffmpeg

Slow transcription

Tip: Transcription is slow
  • Use GPU acceleration: --device cuda or --device metal
  • Use smaller model: --model base or --model tiny
  • Use English-only model: --model small.en

Inaccurate results

Tip: Improve accuracy
  • Use larger model: --model large-v3
  • Add context prompt: --prompt "Technical terms..."
  • Check audio quality

Architecture

  • whisper.cpp or openai-whisper backend
  • Model caching in memory (GPU or CPU)
  • UNIX socket at ~/.fgp/services/whisper/daemon.sock
  • Metal acceleration on Apple Silicon
  • CUDA acceleration on NVIDIA GPUs
  • Streaming support for real-time transcription