OpenClaw Whisper Voice#

Use this skill to make local Whisper transcription dependable on the OpenClaw Gateway host.

Install on the host#

Run:

bash

{baseDir}/scripts/install_local_whisper.sh

The installer:

• installs Python packages into ~/.local
• installs a CPU-safe PyTorch build
• installs openai-whisper
• installs imageio-ffmpeg
• creates stable ~/.local/bin/whisper and ~/.local/bin/ffmpeg launchers

Transcribe a file manually#

Use the wrapper instead of raw whisper when reliability matters:

bash

{baseDir}/scripts/transcribe.sh /path/to/audio.ogg
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --model tiny --stdout-only
{baseDir}/scripts/transcribe.sh /path/to/audio.mp3 --task translate --format srt

Configure inbound WhatsApp and Telegram voice notes#

Patch OpenClaw config so inbound audio uses the wrapper:

json5

{
  tools: {
    media: {
      audio: {
        enabled: true,
        maxBytes: 20971520,
        timeoutSeconds: 120,
        models: [
          {
            type: "cli",
            command: "{baseDir}/scripts/transcribe.sh",
            args: ["{{MediaPath}}", "--model", "base", "--stdout-only"],
            timeoutSeconds: 120
          }
        ]
      }
    }
  }
}

Model choices#

• tiny: fastest, weakest accuracy
• base: best default for chat voice notes
• small or larger: better accuracy, heavier CPU and RAM use

Output rules#

• Use --stdout-only for tools.media.audio so stdout is only transcript text.
• Use --format txt|srt|vtt|json for standalone file transcription.
• First model download goes into ~/.cache/whisper.