aliyun-qwen-tts-voice-clone
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npx mdskill add cinience/alicloud-skills/aliyun-qwen-tts-voice-cloneClones voices using Alibaba Cloud Qwen TTS VC models for text synthesis
- Solves the task of replicating a speaker's voice from sample audio
- Depends on Alibaba Cloud Model Studio and DashScope SDK for voice cloning
- Uses enrollment audio samples and text input to generate cloned voice output
- Returns synthesized audio as a URL or stream with a unique voice ID for reuse
SKILL.md
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--- name: aliyun-qwen-tts-voice-clone description: Use when cloning voices with Alibaba Cloud Model Studio Qwen TTS VC models. Use when creating cloned voices from sample audio and synthesizing text with cloned timbre. version: 1.0.0 --- Category: provider # Model Studio Qwen TTS Voice Clone Use voice cloning models to replicate timbre from enrollment audio samples. ## Critical model names Use one of these exact model strings: - `qwen3-tts-vc-2026-01-22` - `qwen3-tts-vc-realtime-2026-01-15` ## Prerequisites - Install SDK in a virtual environment: ```bash python3 -m venv .venv . .venv/bin/activate python -m pip install dashscope ``` - Set `DASHSCOPE_API_KEY` in your environment, or add `dashscope_api_key` to `~/.alibabacloud/credentials`. ## Normalized interface (tts.voice_clone) ### Request - `text` (string, required) - `voice_sample` (string | bytes, required) enrollment sample - `voice_name` (string, optional) - `stream` (bool, optional) ### Response - `audio_url` (string) or streaming PCM chunks - `voice_id` (string) - `request_id` (string) ## Operational guidance - Use clean speech samples with low background noise. - Respect consent and policy requirements for cloned voices. - Persist generated `voice_id` and reuse for future synthesis requests. ## Local helper script Prepare a normalized request JSON and validate response schema: ```bash .venv/bin/python skills/ai/audio/aliyun-qwen-tts-voice-clone/scripts/prepare_voice_clone_request.py \ --text "Welcome to this voice-clone demo" \ --voice-sample "https://example.com/voice-sample.wav" ``` ## Output location - Default output: `output/ai-audio-tts-voice-clone/audio/` - Override base dir with `OUTPUT_DIR`. ## Validation ```bash mkdir -p output/aliyun-qwen-tts-voice-clone for f in skills/ai/audio/aliyun-qwen-tts-voice-clone/scripts/*.py; do python3 -m py_compile "$f" done echo "py_compile_ok" > output/aliyun-qwen-tts-voice-clone/validate.txt ``` Pass criteria: command exits 0 and `output/aliyun-qwen-tts-voice-clone/validate.txt` is generated. ## Output And Evidence - Save artifacts, command outputs, and API response summaries under `output/aliyun-qwen-tts-voice-clone/`. - Include key parameters (region/resource id/time range) in evidence files for reproducibility. ## Workflow 1) Confirm user intent, region, identifiers, and whether the operation is read-only or mutating. 2) Run one minimal read-only query first to verify connectivity and permissions. 3) Execute the target operation with explicit parameters and bounded scope. 4) Verify results and save output/evidence files. ## References - `references/sources.md`