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alicloud-ai-audio-tts-voice-design

alicloud-ai-audio-tts-voice-design

github.com/cinienceCreative & media396284 installsUpdated 11w ago
Repository

About alicloud-ai-audio-tts-voice-design

A skill for creating controllable synthetic voices with Alibaba Cloud Model Studio Qwen TTS voice-design models. It guides request preparation, voice-prompt formulation, and response validation for users building speech-generation workflows.

Key features

  1. 01Natural-language voice descriptions
  2. 02Qwen TTS voice-design model selection
  3. 03Normalized request and response fields
  4. 04Local request preparation script
  5. 05Guidance for reusable voice prompts

Use cases

  1. 01Creating a consistent product voice
  2. 02Testing a voice with short utterances
  3. 03Preparing requests for speech generation

Install

Copy the command and run it in a terminal.

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

After installing, type/alicloud-ai-audio-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/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

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

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