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qwenspeakqwenspeak 音频

Agent Skill

qwenspeak 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

27,189

周安装

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下载量

9,525
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:qwenspeak(qwenspeak 音频)
来源仓库:https://github.com/psyb0t/qwenspeak
安装命令:
openclaw skills install qwenspeak
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 qwenspeak

简介

通过 SSH 上的 Qwen3-TTS 生成文本到语音。预设声音、声音克隆、声音设计。当用户想要生成语音音频、克隆声音等时使用

SKILL.md

name
qwenspeak
description
Text-to-speech generation via Qwen3-TTS over SSH. Preset voices, voice cloning, voice design. Use when the user wants to generate speech audio, clone voices, or work with TTS.
compatibility
Requires ssh and a running qwenspeak instance. QWENSPEAK_HOST and QWENSPEAK_PORT env vars must be set.
metadata
author
psyb0t
homepage
https://github.com/psyb0t/docker-qwenspeak

qwenspeak

YAML-driven text-to-speech over SSH using Qwen3-TTS models.

For installation and deployment, see references/setup.md.

SSH Wrapper

Use scripts/qwenspeak.sh for all commands. It handles host, port, and host key acceptance via QWENSPEAK_HOST and QWENSPEAK_PORT env vars.

scripts/qwenspeak.sh <command> [args]
scripts/qwenspeak.sh <command> < input_file
scripts/qwenspeak.sh <command> > output_file

TTS Generation

Submit YAML, get a job UUID back immediately, poll for progress. Jobs run sequentially — one at a time, the rest queue up.

# Get the YAML template
scripts/qwenspeak.sh "tts print-yaml" > job.yaml

# Submit job
scripts/qwenspeak.sh "tts" < job.yaml
# {"id": "550e8400-...", "status": "queued", "total_steps": 3, "total_generations": 7}

# Check progress
scripts/qwenspeak.sh "tts get-job 550e8400"

# Follow job log
scripts/qwenspeak.sh "tts get-job-log 550e8400 -f"

# Download result
scripts/qwenspeak.sh "get hello.wav" > hello.wav

YAML Structure

Global settings + list of steps. Each step loads a model, runs all its generations, then unloads. Settings cascade: global > step > generation.

steps:
  - mode: custom-voice
    model_size: 1.7b
    speaker: Ryan
    language: English
    generate:
      - text: "Hello world"
        output: hello.wav
      - text: "I cannot believe this!"
        speaker: Vivian
        instruct: "Speak angrily"
        output: angry.wav

  - mode: voice-design
    generate:
      - text: "Welcome to our store."
        instruct: "A warm, friendly young female voice with a cheerful tone"
        output: welcome.wav

  - mode: voice-clone
    model_size: 1.7b
    ref_audio: ref.wav
    ref_text: "Transcript of reference"
    generate:
      - text: "First line in cloned voice"
        output: clone1.wav
      - text: "Second line"
        output: clone2.wav

Modes

custom-voice — Pick from 9 preset speakers. 1.7B supports emotion/style via instruct.

voice-design — Describe the voice in natural language via instruct. 1.7B only.

voice-clone — Clone from reference audio. Set ref_audio and ref_text at step level to reuse across generations. x_vector_only: true skips transcript.

Emotion trick for cloned voices

Upload references with different emotions, use separate steps:

scripts/qwenspeak.sh "create-dir refs"
scripts/qwenspeak.sh "put refs/happy.wav" < me_happy.wav
scripts/qwenspeak.sh "put refs/angry.wav" < me_angry.wav
steps:
  - mode: voice-clone
    ref_audio: refs/happy.wav
    ref_text: "transcript of happy ref"
    generate:
      - text: "Great news everyone!"
        output: happy1.wav

  - mode: voice-clone
    ref_audio: refs/angry.wav
    ref_text: "transcript of angry ref"
    generate:
      - text: "This is unacceptable"
        output: angry1.wav

Job Management

scripts/qwenspeak.sh "tts list-jobs"              # list all
scripts/qwenspeak.sh "tts list-jobs --json"        # JSON output
scripts/qwenspeak.sh "tts get-job <id>"            # job details
scripts/qwenspeak.sh "tts get-job-log <id>"        # view log
scripts/qwenspeak.sh "tts get-job-log <id> -f"     # follow log
scripts/qwenspeak.sh "tts cancel-job <id>"         # cancel

Statuses: queuedrunningcompleted | failed | cancelled

Completed jobs auto-cleaned after 1 day, all jobs after 1 week. UUID prefixes work (e.g. first 8 chars).

File Operations

All paths relative to the work directory. Traversal blocked.

CommandDescription
put <path>Upload file from stdin
get <path>Download file to stdout
list-files [--json]List directory
remove-file <path>Delete a file
create-dir <path>Create directory
remove-dir <path>Remove empty directory
move-file <src> <dst>Move or rename
copy-file <src> <dst>Copy a file
file-exists <path>Check if file exists (true/false)
search-files <glob>Glob search (** recursive)

Speakers

SpeakerGenderLanguageDescription
VivianFemaleChineseBright, slightly edgy young voice
SerenaFemaleChineseWarm, gentle young voice
Uncle_FuMaleChineseSeasoned, low mellow timbre
DylanMaleChineseYouthful Beijing dialect, clear natural timbre
EricMaleChineseLively Chengdu/Sichuan dialect, slightly husky
RyanMaleEnglishDynamic with strong rhythmic drive
AidenMaleEnglishSunny American, clear midrange
Ono_AnnaFemaleJapanesePlayful, light nimble timbre
SoheeFemaleKoreanWarm with rich emotion

YAML Options

All settings cascade: global > step > generation.

FieldDefaultDescription
dtypefloat32float32, float16, bfloat16 (float16/bfloat16 GPU only)
flash_attnautoFlashAttention-2: auto-detects, auto-switches float32→bfloat16
temperature0.9Sampling temperature
top_k50Top-k sampling
top_p1.0Top-p / nucleus sampling
repetition_penalty1.05Repetition penalty
max_new_tokens2048Max codec tokens to generate
no_samplefalseGreedy decoding
streamingfalseStreaming mode (lower latency)
moderequiredStep only: custom-voice, voice-design, or voice-clone
model_size1.7bStep only: 1.7b or 0.6b
textrequiredText to synthesize
outputrequiredOutput file path
speakerViviancustom-voice: speaker name
languageAutoLanguage for synthesis
instruct-custom-voice: emotion/style; voice-design: voice description
ref_audio-voice-clone: reference audio file path
ref_text-voice-clone: transcript of reference audio
x_vector_onlyfalsevoice-clone: use speaker embedding only

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

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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。

平台分布

OpenClaw

83.49%
按下载量换算7,952

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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