Qwen-Audio-TTS
Overview
Qwen-Audio-3.0-TTS-Plus is a high-performance speech synthesis model, designed for high-quality speech generation scenarios. Compared with the previous version, it supports more low-resource languages and Chinese dialects, significantly improves dialect authenticity, and enhances free-style instruction following and fine-grained tag control for more accurate control over emotion, tone, character, speaking rate, volume, and synthesis style. It is also more robust under noisy and reverberant acoustic conditions, with further improvements in audio quality, clarity, resolution, and overall expressiveness. The Plus version focuses more on synthesis quality and detailed expressiveness, making it suitable for professional scenarios with higher requirements for audio quality, naturalness, and expressiveness, such as content creation, audiobooks, film and video dubbing, brand voice design, and premium speech services.
Input
Output
Features
Prefix Completion
Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docsFunction Calling
Use function calling to connect large language models with external tools and systems.View docsCache
Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docsStructured Outputs
Structured Outputs help ensure the model returns a JSON string in the expected format.View docsBatches
feature.funeTuning
Pricing
- TTS$0.2Per 10,000 characters
Rate Limits
- RPMRequests Per Minute180
API Reference
Get API Key# coding=utf-8
import dashscope
from dashscope.audio.tts_v2 import *
# If the API Key is not configured in the environment variable, your-api-key needs to be replaced with your own API Key
# dashscope.api_key = "your-api-key"
dashscope.base_websocket_api_url='wss://dashscope-intl.aliyuncs.com/api-ws/v1/inference'
model = "qwen-audio-3.0-tts-plus"
#Please enter the correct voice below.
voice = ""
synthesizer = SpeechSynthesizer(model=model, voice=voice)
audio = synthesizer.call("How is the weather today?")
with open('output.mp3', 'wb') as f:
f.write(audio)