AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Qwen-Audio-3.0-Gen-Preview is presented, a unified non-autoregressive framework that uses a Diffusion Transformer and a shared variational autoencoder (VAE) to generate the complete mixed waveform and demonstrates the potential of unified generation for temporally structured audio without task-specific branches.
Qwen-Audio-3.0-ASR is presented, a Mixture-of-Experts (MoE) LLM-based ASR system designed to address production demands through a unified, instruction-following framework and demonstrates state-of-the-art or highly competitive recognition performance across a broad range of evaluation conditions.
FullDiT is introduced, a conditional DiT that fuses eight frame-aligned RVQ streams with independently encoded captions and lyrics and uses non-causal self-attention over the complete acoustic latent sequence and outperforms five commercial systems on 15 of 18 automatic metrics.
In this report, we present Qwen-Audio-3.0-TTS, a production-oriented speech synthesis system that jointly advances content consistency, speaker similarity, prosodic naturalness, audio quality, controllability, multilingual coverage, efficiency, and robustness. It combines a 12.5~Hz low-frame-rate speech tokenizer for r...
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