transcribe-audio
Skill2 starsChanged 45 days agoMITView on GitHub
Transcribe audio files to text using a local Whisper ASR service. Use when: the user wants to transcribe an audio file to text, convert speech to text from an audio recording, extract text from voice recordings, or needs transcription of podcasts/interviews/voice notes. Only works for English language audio. The skill saves the transcription to a text file in the agent's local folder.
- Sends data out
7 other projects use a version of this.
Adopted by
Most recently taken up by
- umakhanpro/vocalingo-mcptheir own version, first seen Nov 1, 2026
- zedxter/utility-belttheir own version, first seen Nov 1, 2026
- jwkchung/claude-skillstheir own version, first seen Oct 8, 2026
- caiopizzol/skillstheir own version, first seen Sep 28, 2026
- barefootford/buttercuttheir own version, first seen Sep 14, 2026
- montezuma-p/harkentheir own version, first seen Aug 25, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 7
- barefootford/buttercut★ 598same name
- montezuma-p/harken★ 12same name
- zedxter/utility-belt★ 4same name
- caiopizzol/skills★ 3same name
- andfrancot-alt/claude-skills★ 0same name
- jwkchung/claude-skills★ 0same name
- umakhanpro/vocalingo-mcp★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
Files
Transcribe Audio
Transcribe audio files to text using the local Whisper ASR service running at http://localhost:9000.
Prerequisites
- The Whisper service must be running (check with
curl http://localhost:9000/health) - Audio file must be in a supported format: OGG, MP3, M4A, WAV, or WebM
- Audio must be in English (the local model is English-only)
Usage
Basic Transcription
To transcribe an audio file:
curl -X POST http://localhost:9000/asr \
-F "audio_file=@/path/to/audio.wav" \
-F "language=en"Save to File
Save the transcription to the agent's local folder:
curl -X POST http://localhost:9000/asr \
-F "audio_file=@/path/to/audio.wav" \
-F "language=en" \
-o transcription.txtOr with a specific output path:
OUTPUT_FILE="${PWD}/$(basename /path/to/audio.wav .wav).txt"
curl -X POST http://localhost:9000/asr \
-F "audio_file=@/path/to/audio.wav" \
-F "language=en" \
-o "$OUTPUT_FILE"Quick Workflow
- Verify the service is running:
Expected response:curl -s http://localhost:9000/health{"status": "ok"} - Transcribe and save:
curl -X POST http://localhost:9000/asr \ -F "audio_file=@<audio-file-path>" \ -F "language=en" \ -o <output-file-path> - Verify the output:
cat <output-file-path>
Supported Audio Formats
| Format | Extension | MIME Type |
| OGG Vorbis | .oga, .ogg | audio/ogg |
| MP3 | .mp3 | audio/mpeg |
| M4A | .m4a | audio/mp4 |
| WAV | .wav | audio/wav |
| WebM | .webm | audio/webm |
Performance Notes
- The local Whisper service uses the
tiny.enmodel - Processing time is roughly 10-20% of audio duration (e.g., 1 minute of audio takes ~6-12 seconds)
- The service only supports English transcription
- For best results, ensure audio has clear speech with minimal background noise
Error Handling
Common issues and solutions:
| Error | Cause | Solution |
| Connection refused | Whisper service not running | Start the local Whisper service using your own deployment method (for example Docker Compose in your chosen whisper-service directory) |
| Empty response | Audio file is silent or corrupted | Check the audio file can be played |
| Garbage text | Audio is not in English | Only English is supported |
| Slow transcription | High CPU load or concurrent requests | Wait for other transcriptions to complete |
Example: Transcribe a Single File
# Set variables
AUDIO_FILE="/path/to/recording.wav"
OUTPUT_FILE="${PWD}/transcription.txt"
# Verify service
if ! curl -s http://localhost:9000/health | grep -q '"status": "ok"'; then
echo "Error: Whisper service is not running"
exit 1
fi
# Transcribe
curl -X POST http://localhost:9000/asr \
-F "audio_file=@${AUDIO_FILE}" \
-F "language=en" \
-o "$OUTPUT_FILE"
echo "Transcription saved to: $OUTPUT_FILE"
cat "$OUTPUT_FILE"Example: Batch Transcribe Multiple Files
for audio_file in *.wav; do
output_file="${PWD}/$(basename "$audio_file" .wav).txt"
echo "Transcribing: $audio_file -> $output_file"
curl -X POST http://localhost:9000/asr \
-F "audio_file=@${audio_file}" \
-F "language=en" \
-o "$output_file"
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