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English(EN) Audio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing

Audio-Omni 框架统一音频生成、编辑和理解

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出 Audio-Omni，一个旨在统一语音、音乐和通用声音等不同领域音频理解、生成和编辑的新框架。该系统集成了冻结的多模态大语言模型和可训练的扩散 Transformer，并通过一个名为 AudioEdit 的新数据集解决了音频编辑中的数据稀缺性挑战。实验表明，Audio-Omni 取得了最先进的成果，可与专用模型相媲美，并展示了知识增强推理和零样本跨语言控制等高级功能。 AI

影响 引入了一个统一的音频任务框架，可能推动生成式音频智能和跨模态应用的发展。

排序理由 这是一篇介绍音频处理新框架和数据集的研究论文。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Audio-Omni 框架统一音频生成、编辑和理解

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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Zeyue Tian, Binxin Yang, Zhaoyang Liu, Jiexuan Zhang, Ruibin Yuan, Hubery Yin, Qifeng Chen, Chen Li, Jing Lyu, Wei Xue, Yike Guo ·

    Audio-Omni：将多模态理解扩展到通用的音频生成和编辑

    arXiv:2604.10708v2 Announce Type: replace-cross Abstract: Recent progress in multimodal models has spurred rapid advances in audio understanding, generation, and editing. However, these capabilities are typically addressed by specialized models, leaving the development of a truly…

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