Aliyun Qwen Tts Voice Clone

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.

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_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:

.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

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