collaborators

6 papers

eess.AS2026

Qwen-Audio-VAE Technical Report

Ziyue Jiang, Dake Guo, Zekai Zhang +11

Qwen-Audio-VAE is a low‑bitrate, fast‑encoding continuous audio autoencoder that produces compact latent representations for scalable text‑to‑audio generation, using a causal encod…

cs.SD2026

Qwen-Music Technical Report

Jin Xu, Kangdi Wang, Ruibin Yuan +24

Qwen-Music is a large language model‑based system that generates high‑fidelity songs with vocals from text prompts or re‑imagines existing tracks, using a semantic token representa…

cs.SD2026

Qwen3-TTS Technical Report

Hangrui Hu, Xinfa Zhu, Ting He +13

In this report, we present the Qwen3-TTS series, a family of advanced multilingual, controllable, robust, and streaming text-to-speech models. Qwen3-TTS supports state-of-the-art 3…

cs.CL2025

Qwen3-Omni Technical Report

Jin Xu, Zhifang Guo, Hangrui Hu +35

We present Qwen3-Omni, a single multimodal model that, for the first time, maintains state-of-the-art performance across text, image, audio, and video without any degradation relat…

eess.AS2025

Long-Context Speech Synthesis with Context-Aware Memory

Zhipeng Li, Xiaofen Xing, Jingyuan Xing +3

In long-text speech synthesis, current approaches typically convert text to speech at the sentence-level and concatenate the results to form pseudo-paragraph-level speech. These me…

cs.CL2025

Qwen2.5-Omni Technical Report

Jin Xu, Zhifang Guo, Jinzheng He +11

In this report, we present Qwen2.5-Omni, an end-to-end multimodal model designed to perceive diverse modalities, including text, images, audio, and video, while simultaneously gene…