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An Audio-Visual System for Object-Based Audio:udFrom Recording to Listening

机译:基于对象的音频的视听系统: ud从录音到听力

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摘要

Object-based audio is an emerging representationudfor audio content, where content is represented in a reproductionformat-udagnostic way and thus produced once for consumption onudmany different kinds of devices. This affords new opportunitiesudfor immersive, personalized, and interactive listening experiences.udThis article introduces an end-to-end object-based spatial audioudpipeline, from sound recording to listening. A high-leveludsystem architecture is proposed, which includes novel audiovisualudinterfaces to support object-based capture and listenertrackedudrendering, and incorporates a proposed component forudobjectification, i.e., recording content directly into an object-basedudform. Text-based and extensible metadata enable communicationudbetween the system components. An open architecture for objectudrendering is also proposed.udThe system’s capabilities are evaluated in two parts. First,udlistener-tracked reproduction of metadata automatically estimatedudfrom two moving talkers is evaluated using an objectiveudbinaural localization model. Second, object-based scene captureudwith audio extracted using blind source separation (to remixudbetween two talkers) and beamforming (to remix a recording ofuda jazz group), is evaluated with perceptually-motivated objectiveudand subjective experiments. These experiments demonstrate thatudthe novel components of the system add capabilities beyondudthe state of the art. Finally, we discuss challenges and futureudperspectives for object-based audio workflows.
机译:基于对象的音频是音频内容的一种新兴表示形式,其中内容以再现格式/诊断方式表示,因此一次被制作出来,可以在多种类型的设备上消费。这为沉浸式,个性化和交互式聆听体验提供了新的机会。 ud本文介绍了从声音录制到聆听的端到端基于对象的空间音频 udpipeline。提出了一种高级 udsystem体系结构,该体系结构包括新颖的视听 udinterfaces以支持基于对象的捕获和侦听器跟踪的 udrendering,并结合了一个拟议的组件以实现 udobjectification的功能,即直接将内容记录到基于object udform中。基于文本的可扩展元数据使系统组件之间能够进行通信。还提出了用于对象渲染的开放体系结构。 ud系统的功能分为两部分进行评估。首先,使用客观双耳本地化模型评估 udlistener跟踪的从两个运动说话者自动估计的 ude元数据的再现。其次,通过感知动机的客观主观和主观实验来评估基于对象的场景捕获音频,并使用盲源分离(在两个讲话者之间进行混音)和波束成形(在爵士乐队的录音中进行混音)提取音频。这些实验证明,该系统的新颖组件增加了超越现有技术的功能。最后,我们讨论了基于对象的音频工作流程的挑战和未来的前景。

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