alicloud-ai-audio-tts-voice-clone
v1.0.2Voice cloning workflows with Alibaba Cloud Model Studio Qwen TTS VC models. Use when creating cloned voices from sample audio and synthesizing text with cloned timbre.
Installation
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:
python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope
- Set
DASHSCOPE_API_KEYin your environment, or adddashscope_api_keyto~/.alibabacloud/credentials.
Normalized interface (tts.voice_clone)
Request
text(string, required)voice_sample(string | bytes, required) enrollment samplevoice_name(string, optional)stream(bool, optional)
Response
audio_url(string) or streaming PCM chunksvoice_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_idand reuse for future synthesis requests.
Local helper script
Prepare a normalized request JSON and validate response schema:
.venv/bin/python skills/ai/audio/alicloud-ai-audio-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
mkdir -p output/alicloud-ai-audio-tts-voice-clone
for f in skills/ai/audio/alicloud-ai-audio-tts-voice-clone/scripts/*.py; do
python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/alicloud-ai-audio-tts-voice-clone/validate.txt
Pass criteria: command exits 0 and output/alicloud-ai-audio-tts-voice-clone/validate.txt is generated.
Output And Evidence
- Save artifacts, command outputs, and API response summaries under
output/alicloud-ai-audio-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