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voiceclawvoiceclaw 音频

Agent Skill

用于辅助音频、音乐、语音转写、语音合成或声音素材处理。它适合让 Agent 生成配乐说明、整理音频流程、调用语音工具或处理播客和视频配音素材。使用时需要确认输入音频来源、输出格式、时长和模型限制;涉及人声克隆、版权音乐或公开发布时,应先核对授权和合规边界。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:voiceclaw(voiceclaw 音频)
来源仓库:https://github.com/asif2bd/voiceclaw
安装命令:
openclaw skills install voiceclaw
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install voiceclaw

简介

OpenClaw 本地语音输入输出解决方案。

  • 使用 whisper.cpp 转录入站语音,Piper T 生成回复语音。
  • 减少对云端服务的依赖,提升响应速度。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 需本地部署相关模型文件并保证算力充足。
  • voiceclaw 属于运维类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
voiceclaw
description
Local voice I/O for OpenClaw agents. Transcribe inbound audio/voice messages using local Whisper (whisper.cpp) and generate voice replies using local Piper TTS. Requires whisper, piper, and ffmpeg pre-installed on the system. All inference runs on-device — no network calls, no cloud APIs, no API keys. Use when an agent receives a voice/audio message and should respond in both voice and text, or when any text response should be synthesized and sent as audio. Triggers on: voice messages, audio attachments, respond in voice, send as audio, speak this, voiceclaw.
metadata

VoiceClaw

Local-only voice I/O for OpenClaw agents.

  • STT: transcribe.sh — converts audio to text via local Whisper binary
  • TTS: speak.sh — converts text to speech via local Piper binary
  • Network calls: none — both scripts run fully offline
  • No cloud APIs, no API keys required

Prerequisites

The following must be installed on the system before using this skill:

RequirementPurpose
whisper binarySpeech-to-text inference
ggml-base.en.bin model fileWhisper STT model
piper binaryText-to-speech synthesis
*.onnx voice model filesPiper TTS voices
ffmpegAudio format conversion

See README.md for installation and setup instructions.


Environment Variables

VariableDefaultPurpose
WHISPER_BINauto-detected via whichPath to whisper binary
WHISPER_MODEL~/.cache/whisper/ggml-base.en.binPath to Whisper model file
PIPER_BINauto-detected via whichPath to piper binary
VOICECLAW_VOICES_DIR~/.local/share/piper/voicesDirectory containing .onnx voice model files

Verify Setup

which whisper && echo "STT binary: OK"
which piper   && echo "TTS binary: OK"
which ffmpeg  && echo "ffmpeg: OK"
ls "${WHISPER_MODEL:-$HOME/.cache/whisper/ggml-base.en.bin}" && echo "STT model: OK"
ls "${VOICECLAW_VOICES_DIR:-$HOME/.local/share/piper/voices}"/*.onnx 2>/dev/null | head -1 && echo "TTS voices: OK"

Inbound Voice: Transcribe

# Transcribe audio → text (supports ogg, mp3, m4a, wav, flac)
TRANSCRIPT=$(bash scripts/transcribe.sh /path/to/audio.ogg)

Override model path:

WHISPER_MODEL=/path/to/ggml-base.en.bin bash scripts/transcribe.sh audio.ogg

Outbound Voice: Speak

# Step 1: Generate WAV (local Piper — no network)
WAV=$(bash scripts/speak.sh "Your response here." /tmp/reply.wav en_US-lessac-medium)

# Step 2: Convert to OGG Opus (Telegram voice requirement)
ffmpeg -i "$WAV" -c:a libopus -b:a 32k /tmp/reply.ogg -y -loglevel error

# Step 3: Send via message tool (filePath=/tmp/reply.ogg)

Override voice directory:

VOICECLAW_VOICES_DIR=/path/to/voices bash scripts/speak.sh "Hello." /tmp/reply.wav

Available Voices

VoiceStyle
en_US-lessac-mediumNeutral American (default)
en_US-amy-mediumWarm American female
en_US-joe-mediumAmerican male
en_US-kusal-mediumExpressive American male
en_US-danny-lowDeep American male (fast)
en_GB-alba-mediumBritish female
en_GB-northern_english_male-mediumNorthern British male

Agent Behavior Rules

  1. Voice in → Voice + Text out. Always respond with both a voice reply and a text reply when a voice message is received.
  2. Include the transcript. Show *"🎙️ I heard: [transcript]"* at the top of every text reply to a voice message.
  3. Keep voice responses concise. Piper TTS works best under ~200 words — summarize for audio, include full detail in text.
  4. Local only. Never use a cloud TTS/STT API. Only the local whisper and piper binaries.
  5. Send voice before text. Send the audio file first, then follow with the text reply.

Full Example

# 1. Transcribe inbound voice message
TRANSCRIPT=$(bash path/to/voiceclaw/scripts/transcribe.sh /path/to/voice.ogg)

# 2. Compose reply and generate audio
RESPONSE="Deployment complete. All checks passed."
WAV=$(bash path/to/voiceclaw/scripts/speak.sh "$RESPONSE" /tmp/reply_$$.wav)
ffmpeg -i "$WAV" -c:a libopus -b:a 32k /tmp/reply_$$.ogg -y -loglevel error

# 3. Send voice + text
# message(action=send, filePath=/tmp/reply_$$.ogg, ...)
# reply: "🎙️ I heard: $TRANSCRIPT\
\
$RESPONSE"

Troubleshooting

IssueFix
whisper: command not foundEnsure whisper binary is installed and in PATH
Whisper model not foundSet WHISPER_MODEL=/path/to/ggml-base.en.bin
piper: command not foundEnsure piper binary is installed and in PATH
Voice model missingSet VOICECLAW_VOICES_DIR=/path/to/voices/
OGG won't play on TelegramEnsure -c:a libopus flag in ffmpeg command

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

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能力 5

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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