Model Studio Qwen TTS

---

name: alicloud-ai-audio-tts

description: Generate human-like speech audio with Model Studio DashScope Qwen TTS models (qwen3-tts-flash, qwen3-tts-instruct-flash). Use when converting text to speech, producing voice lines for short drama/news videos, or documenting TTS request/response fields for DashScope.

version: 1.0.0

---

Category: provider

# Model Studio Qwen TTS

Validation

mkdir -p output/alicloud-ai-audio-tts
python -m py_compile skills/ai/audio/alicloud-ai-audio-tts/scripts/generate_tts.py && echo "py_compile_ok" > output/alicloud-ai-audio-tts/validate.txt

Pass criteria: command exits 0 and `output/alicloud-ai-audio-tts/validate.txt` is generated.

Output And Evidence

Critical model names

Use one of the recommended models:

Prerequisites

python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope

Normalized interface (tts.generate)

Request

Response

Quick start (Python + DashScope SDK)

import os
import dashscope

# Prefer env var for auth: export DASHSCOPE_API_KEY=...
# Or use ~/.alibabacloud/credentials with dashscope_api_key under [default].
# Beijing region; for Singapore use: https://dashscope-intl.aliyuncs.com/api/v1
dashscope.base_http_api_url = "https://dashscope.aliyuncs.com/api/v1"

text = "Hello, this is a short voice line."
response = dashscope.MultiModalConversation.call(
    model="qwen3-tts-instruct-flash",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    text=text,
    voice="Cherry",
    language_type="English",
    instruction="Warm and calm tone, slightly slower pace.",
    stream=False,
)

audio_url = response.output.audio.url
print(audio_url)

Streaming notes

Operational guidance

Output location

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