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aliyun-qwen-tts-voice-design

aliyun-qwen-tts-voice-design

github.com/cinienceCreative & media39657 installsUpdated 11w ago
Repository

About aliyun-qwen-tts-voice-design

aliyun-qwen-tts-voice-design is a skill for generating synthetic speech with Model Studio voice design models, using natural-language descriptions to shape voice traits. It supports text-to-audio and streaming audio workflows.

Key features

  1. 01Design voices from natural-language descriptions
  2. 02Generate speech from text
  3. 03Support streaming PCM audio
  4. 04Return a reusable voice_id

Use cases

  1. 01Create a consistent synthetic voice for a product
  2. 02Test a voice with short utterances
  3. 03Generate audio from text and a voice description

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/cinience/alicloud-skills --skill aliyun-qwen-tts-voice-design

After installing, type/aliyun-qwen-tts-voice-designin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
sources.md
scripts/
prepare_voice_design_request.py

Details

From the project README

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

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