aliyun-qwen-tts-voice-design

name	aliyun-qwen-tts-voice-design
description	Use when designing custom voices with Alibaba Cloud Model Studio Qwen TTS VD models. Use when creating custom synthetic voices from text descriptions and using them for speech synthesis.
version	1.0.0

Category: provider

Model Studio Qwen TTS Voice Design

Use voice design models to create controllable synthetic voices from natural language descriptions.

Critical model names

Use one of these exact model strings:

• qwen3-tts-vd-2026-01-26
• qwen3-tts-vd-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_design)

Request

• voice_prompt (string, required) target voice description
• text (string, required)
• stream (bool, optional)

Response

• audio_url (string) or streaming PCM chunks
• voice_id (string)
• request_id (string)

Operational guidance

• Write voice prompts with tone, pace, emotion, and timbre constraints.
• Build a reusable voice prompt library for product consistency.
• Validate generated voice in short utterances before long scripts.

Local helper script

Prepare a normalized request JSON and validate response schema:

.venv/bin/python skills/ai/audio/aliyun-qwen-tts-voice-design/scripts/prepare_voice_design_request.py \
  --voice-prompt "A warm female host voice, clear articulation, medium pace" \
  --text "This is a voice-design demo"

Output location

• Default output: output/ai-audio-tts-voice-design/audio/
• Override base dir with OUTPUT_DIR.

Validation

mkdir -p output/aliyun-qwen-tts-voice-design
for f in skills/ai/audio/aliyun-qwen-tts-voice-design/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/aliyun-qwen-tts-voice-design/validate.txt

Pass criteria: command exits 0 and output/aliyun-qwen-tts-voice-design/validate.txt is generated.

Output And Evidence

• Save artifacts, command outputs, and API response summaries under output/aliyun-qwen-tts-voice-design/.
• 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