Aliyun Qwen Tts Voice Clone

Name: Aliyun Qwen Tts Voice Clone
Author: cinience

cinience/alicloud-skills

105 installs
396 repo stars
Updated July 18, 2026
cinience/alicloud-skills

Clone voices with Alibaba Cloud Model Studio Qwen TTS VC models from sample audio and synthesize text in the cloned timbre.

About

Uses Model Studio Qwen TTS VC models to replicate a voice timbre from enrollment audio and synthesize speech with it. A developer uses it to create and use cloned voices for TTS.

qwen3-tts-vc and vc-realtime model variants
Enrollment-from-sample then synthesis with cloned timbre

Aliyun Qwen Tts Voice Clone by the numbers

105 all-time installs (skills.sh)
Ranked #784 of 1,335 Generative Media skills by installs in the Skillselion catalog
Data as of Aug 5, 2026 (Skillselion catalog sync)

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

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Installs	105
repo stars	★ 396
Last updated	July 18, 2026
Repository	cinience/alicloud-skills ↗

What it does

Clone voices with Alibaba Cloud Model Studio Qwen TTS VC models from sample audio and synthesize text in the cloned timbre.

Files

SKILL.mdMarkdownGitHub ↗

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

interface:
  display_name: "Alibaba Cloud AI Audio TTS Voice Clone"
  short_description: "Qwen voice cloning workflows"
  default_prompt: "Use $aliyun-qwen-tts-voice-clone to complete this ai/audio voice cloning task on Alibaba Cloud."

#!/usr/bin/env python3
"""Prepare and validate normalized request/response for Qwen TTS voice clone."""

from __future__ import annotations

import argparse
import json
import sys
from pathlib import Path


def _load_json(path: str) -> dict:
    return json.loads(Path(path).read_text(encoding="utf-8"))


def main() -> None:
    parser = argparse.ArgumentParser(description="Prepare tts.voice_clone request and validate response shape")
    parser.add_argument("--text", required=True)
    parser.add_argument("--voice-sample", required=True)
    parser.add_argument("--voice-name")
    parser.add_argument("--stream", action="store_true")
    parser.add_argument("--output", default="output/ai-audio-tts-voice-clone/request.json")
    parser.add_argument("--validate-response", help="Path to JSON response file")
    args = parser.parse_args()

    req = {
        "text": args.text,
        "voice_sample": args.voice_sample,
        "stream": bool(args.stream),
    }
    if args.voice_name:
        req["voice_name"] = args.voice_name

    out = Path(args.output)
    out.parent.mkdir(parents=True, exist_ok=True)
    out.write_text(json.dumps(req, ensure_ascii=False, indent=2), encoding="utf-8")

    result = {"ok": True, "request_path": str(out)}

    if args.validate_response:
        resp = _load_json(args.validate_response)
        if "audio_url" not in resp and "audio_base64_pcm" not in resp:
            print(json.dumps({"ok": False, "error": "missing audio_url/audio_base64_pcm"}, ensure_ascii=False))
            sys.exit(1)
        result["response_valid"] = True

    print(json.dumps(result, ensure_ascii=False))


if __name__ == "__main__":
    main()