SkillHub

voice-stt-tts

v1.0.3

Full voice message setup (STT + TTS) for OpenClaw using faster-whisper and Edge TTS

Sourced from ClawHub, Authored by Dmitry Aksenkin

Installation

Please help me install the skill `voice-stt-tts` from SkillHub official store. npx skills add aksenkin/voice-stt-tts

Voice Messages (STT + TTS) for OpenClaw 🎙️

Complete voice message setup using faster-whisper for transcription and Edge TTS for voice replies.

What we configure

  • STT (Speech-to-Text) — transcribe voice messages via faster-whisper
  • TTS (Text-to-Speech) — voice replies via Edge TTS
  • 🎯 Result: voice → text → reply with voice

Installation

1. Create virtual environment (venv)

For Ubuntu create an isolated venv:

python3 -m venv ~/.openclaw/workspace/voice-messages

2. Install faster-whisper

Install packages in venv:

~/.openclaw/workspace/voice-messages/bin/pip install faster-whisper

What gets installed: - faster-whisper — Python library for transcription - Dependencies: ctranslate2, onnxruntime, huggingface-hub, av, numpy, and others. - Size: ~250 MB


Transcription Script

Path and content

File: ~/.openclaw/workspace/voice-messages/transcribe.py

#!/usr/bin/env python3
import argparse
from faster_whisper import WhisperModel


def transcribe(audio_path: str, model_name: str = "small", lang: str = "en", device: str = "cpu") -> str:
    model = WhisperModel(
        model_name,
        device=device,
        compute_type="int8" if device == "cpu" else "float16",
    )
    segments, _ = model.transcribe(audio_path, language=lang, vad_filter=True)
    text = " ".join(seg.text.strip() for seg in segments if seg.text and seg.text.strip()).strip()
    return text


def main():
    p = argparse.ArgumentParser()
    p.add_argument("--audio", required=True)
    p.add_argument("--model", default="small")
    p.add_argument("--lang", default="en")
    p.add_argument("--device", default="cpu", choices=["cpu", "cuda"])
    args = p.parse_args()

    text = transcribe(args.audio, args.model, args.lang, args.device)
    print(text if text else "")


if __name__ == "__main__":
    main()

What the script does: 1. Accepts audio file path (--audio) 2. Loads Whisper model (--model): small by default 3. Sets language (--lang): en for English 4. Transcribes with VAD filter (Voice Activity Detection) 5. Outputs clean text to stdout

Make file executable:

chmod +x ~/.openclaw/workspace/voice-messages/transcribe.py

OpenClaw Configuration

1. Configure STT (tools.media.audio)

Add to ~/.openclaw/openclaw.json:

{
  "tools": {
    "media": {
      "audio": {
        "enabled": true,
        "maxBytes": 20971520,
        "models": [
          {
            "type": "cli",
            "command": "~/.openclaw/workspace/voice-messages/bin/python",
            "args": [
              "~/.openclaw/workspace/voice-messages/transcribe.py",
              "--audio",
              "{{MediaPath}}",
              "--lang",
              "en",
              "--model",
              "small"
            ],
            "timeoutSeconds": 120
          }
        ]
      }
    }
  }
}

Parameters:

Parameter Value Description
enabled true Enable audio transcription
maxBytes 20971520 Max file size (20 MB)
type "cli" Model type: CLI command
command Python path Path to python in venv
args argument array Arguments for script
{{MediaPath}} placeholder Replaced with audio file path
timeoutSeconds 120 Transcription timeout (2 minutes)

2. Configure TTS (messages.tts)

Add to ~/.openclaw/openclaw.json:

{
  "messages": {
    "tts": {
      "auto": "inbound",
      "provider": "edge",
      "edge": {
        "voice": "en-US-JennyNeural",
        "lang": "en-US"
      }
    }
  }
}

Parameters:

Parameter Value Description
auto "inbound" Key mode! — reply with voice only on incoming voice messages
provider "edge" TTS provider (free, no API key)
voice "en-US-JennyNeural" Voice (see available below)
lang "en-US" Locale (en-US for US english)

3. Full configuration example

{
  "tools": {
    "media": {
      "audio": {
        "enabled": true,
        "maxBytes": 20971520,
        "models": [
          {
            "type": "cli",
            "command": "~/.openclaw/workspace/voice-messages/bin/python",
            "args": [
              "~/.openclaw/workspace/voice-messages/transcribe.py",
              "--audio",
              "{{MediaPath}}",
              "--lang",
              "en",
              "--model",
              "small"
            ],
            "timeoutSeconds": 120
          }
        ]
      }
    },
  },
  "messages": {
    "tts": {
      "auto": "inbound",
      "provider": "edge",
      "edge": {
        "voice": "en-US-JennyNeural",
        "lang": "en-US"
      }
    },
    "ackReactionScope": "group-mentions"
  }
}

Apply Changes

Restart Gateway

# Method 1: via openclaw CLI
openclaw gateway restart

# Method 2: via systemd
systemctl --user restart openclaw-gateway

# Check status
systemctl --user status openclaw-gateway
# Should show: active (running)

Testing

Test STT (transcription)

Action: Send a voice message to your Telegram bot

Expected result:

[Audio] User text: [Telegram ...] <media:audio> Transcript: <transcribed text>

Example response:

[Audio] User text: [Telegram kd (@someuser) id:12345678 +5s ...] <media:audio> Transcript: Hello. How are you?

Test TTS (voice replies)

Action: After successful transcription, bot should send a voice reply

Expected result: - Voice file arrives in Telegram - Voice note (round bubble)

Expected behavior: - Incoming voice → bot replies with voice - Text messages → bot replies with text (this is normal!)


Available Edge TTS Voices

Female voices

Voice ID Usage example
Jenny en-US-JennyNeural ← current
Ana en-US-AnaNeural Softer

Male voices

Voice ID Usage example
Dmitry en-US-RogerNeural More bass

How to change voice:

cat ~/.openclaw/openclaw.json | 
  jq '.messages.tts.edge.voice = "en-US-MichelleNeural"' > ~/.openclaw/openclaw.json.tmp
mv ~/.openclaw/openclaw.json.tmp ~/.openclaw/openclaw.json
systemctl --user restart openclaw-gateway

Additional Edge TTS Parameters

Adjusting speed, pitch, volume

{
  "messages": {
    "tts": {
      "edge": {
        "voice": "en-US-JennyNeural",
        "lang": "en-US",
        "rate": "+10%",      // Speed: -50% to +100%
        "pitch": "-5%",     // Pitch: -50% to +50%
        "volume": "+5%"     // Volume: -100% to +100%
      }
    }
  }
}

Troubleshooting

Problem: Voice not transcribed

Logs show:

[ERROR] Transcription failed

Possible causes: 1. File too large — > 20 MB bash # Solution: Increase maxBytes in config maxBytes: 52428800 # 50 MB

  1. Timeout — transcription took > 2 minutes bash # Solution: Increase timeoutSeconds timeoutSeconds: 180 # 3 minutes

  2. Model not downloaded — first run bash # Solution: Wait while it downloads (1-2 minutes) # Models are cached in ~/.cache/huggingface/

Problem: No voice reply

Possible causes: 1. Reply too short (< 10 characters) - TTS skips very short replies - Solution: this is expected behavior

  1. auto: "inbound" but text message
  2. TTS in inbound mode replies with voice only on voice messages
  3. Text messages get text replies — this is correct!

  4. Edge TTS unavailable bash # Check curl -s "https://speech.platform.bing.com/consumer/api/v1/tts" | head -c 100 # If error — temporarily unavailable


Performance

Transcription time (Raspberry Pi 4/ARM)

Whisper Model Est. time Quality
tiny ~5-10 sec Low
base ~10-20 sec Medium
small ~20-40 sec High ← current
medium ~40-80 sec Very high
large ~80-160 sec Maximum

Recommendation: For Raspberry Pi use small or base. medium/large will be very slow.

Where Whisper models are stored

~/.cache/huggingface/

Models download automatically on first run.

Done! 🎉

After completing these steps:

  1. ✅ faster-whisper installed in venv
  2. transcribe.py script created
  3. ✅ OpenClaw configured (STT + TTS)
  4. ✅ Gateway restarted
  5. ✅ Voice messages working

Now your Telegram bot: - 🎙️ Accepts voice → transcribes via faster-whisper - 🎤 Replies with voice → generates via Edge TTS - 💬 Accepts text → replies with text (as usual)


Useful links: - OpenClaw docs: https://docs.openclaw.ai - TTS docs: https://docs.openclaw.ai/tts - Audio docs: https://docs.openclaw.ai/nodes/audio - Install skills: npx clawhub search voice


Created: 2026-03-01 for OpenClaw 2026.2.26