alicloud-ai-audio-tts-voice-design

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: ```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_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: ```bash .venv/bin/python skills/ai/audio/alicloud-ai-audio-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 ```bash mkdir -p output/alicloud-ai-audio-tts-voice-design for f in skills/ai/audio/alicloud-ai-audio-tts-voice-design/scripts/*.py; do python3 -m py_compile "$f" done echo "py_compile_ok" > output/alicloud-ai-audio-tts-voice-design/validate.txt ``` Pass criteria: command exits 0 and `output/alicloud-ai-audio-tts-voice-design/validate.txt` is generated. ## Output And Evidence - Save artifacts, command outputs, and API response summaries under `output/alicloud-ai-audio-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`