arXiv:2606. 24307v1 Announce Type: cross Abstract: Interactive music and live performance relies on real-time human expression, but modern generative music AI remains largely absent from this domain due to its prohibitive inference latency and offline rendering paradigm.
By Baisen Wang, Chenxi Bao, Qisong Han
arXiv:2607. 24873v1 Announce Type: new Abstract: Recent advances in AI music generation have enabled users to create complete musical pieces from natural-language prompts.
By Callie C. Liao, Duoduo Liao, Ellie L. Zhang
arXiv:2606. 05121v1 Announce Type: cross Abstract: Audio is an inherently interactive modality, yet today's Large Audio Language Models (LALMs) are offline, and streaming audio models each handle only a single task such as streaming ASR or voice chatting.
By Zhifei Xie, Zihang Liu, Ze An, Xiaobin Hu, Yue Liao, Ziyang Ma, Dongchao Yang, Mingbao Lin, Deheng Ye, Shuicheng Yan, Chunyan Miao
arXiv:2502. 00023v2 Announce Type: replace-cross Abstract: Our research explores the development and application of musical agents, human-in-the-loop generative AI systems designed to support music performance and improvisation within co-creative spaces.
By Keon Ju M. Lee, Philippe Pasquier
Recent advances in AI music generation have enabled users to create complete musical pieces from natural-language prompts. However, most existing systems follow a prompt-and-regenerate paradigm, making iterative refinement difficult because users must repeatedly recreate compositions instead of directly evolving existing musical ideas.
Qwen3.8-Omni-Flash is a natively multimodal agentic model designed for real‑world multimodal productivity, offering enhanced multimodal understanding, reasoning, and long‑horizon agentic task performance. It builds on a sparse mixture‑of‑experts architecture, extends its context window to one million tokens, and supports long‑context multimodal reasoning and planning. The release includes Qwen-MM-Plugins for native audio and video support and Qwen-Live-Harness for building responsive, real‑time multimodal agents, with extensive evaluations confirming strong performance across multimodal tasks.
By Qwen Team
arXiv:2608. 04378v1 Announce Type: cross Abstract: Collaborative music agents need internal representations rich enough to support both understanding and generation, yet flexible enough for a workflow where the human retains agency.
By Scott H. Hawley
We introduce Qwen3.8-Omni-Flash, a natively multimodal agentic model for real-world multimodal productivity. Compared with previous omni models, which primarily emphasized perception and interaction,...
arXiv:2606. 30642v1 Announce Type: cross Abstract: Full-length song generation must preserve coherence and musicality, render detailed vocal and accompaniment acoustics, and follow lyrics and prompts.
By Shun Lei, Huaicheng Zhang, Dapeng Wu, Yaoxun Xu, Lishi Zuo, Wei Tan, Hangting Chen, Guangzheng Li, Jianwei Yu, Zhiyong Wu, Dong Yu
arXiv:2609. 27303v1 Announce Type: new Abstract: Livestreams are long-lasting interactive environments where audiovisual content, viewer activity, host behavior, and platform signals evolve together, creating assistance needs that emerge from the stream itself.
By Shujian Gao, Jiamei Yan, Yuchen Yang, Penghao Zhou, Qinglei Wang, Tiehan Fan, Yuan Wang, Zuxuan Wu, Yu-gang Jiang
MENASpeechBank is a new reference voice bank that provides about 18,000 high‑quality utterances from 124 speakers across multiple MENA countries, covering English, Modern Standard Arabic, and regional Arabic varieties. The dataset is built through a controllable pipeline that creates persona profiles inspired by the World Values Survey, defines a taxonomy of roughly 5,000 conversational scenarios, matches personas to scenarios via semantic similarity, and generates around 417,000 role‑play conversations using an LLM. Synthetic speaker‑conditioned user‑turn audio is produced from reference recordings to maintain speaker diversity, and both synthetic and human‑recorded conversations are evaluated and analyzed for quality.
By Zien Sheikh Ali, Hunzalah Hassan Bhatti, Rabindra Nath Nandi, Shammur Absar Chowdhury, Firoj Alam
arXiv:2603. 00610v3 Announce Type: replace-cross Abstract: While music generation models have evolved to handle complex multimodal inputs mixing text, lyrics, and reference audio, evaluation mechanisms have lagged behind.
By Yinghao Ma, Haiwen Xia, Hewei Gao, Weixiong Chen, Yuxin Ye, Yuchen Yang, Sungkyun Chang, Mingshuo Ding, Yizhi Li, Ruibin Yuan, Simon Dixon, Emmanouil Benetos