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Linear mixing models for active listening of music productions in realistic studio conditions

机译:线性混合模型,用于现实工作室条件中音乐制作的主动收音

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The mixing/demixing of audio signals as addressed in the signal processing literature (the "source separation" problem) and the music production in studio remain quite separated worlds. Scientific audio scene analysis rather focuses on "natural" mixtures and most often uses linear (convolutive) models of point sources placed in the same acoustic space. In contrast, the sound engineer can mix musical signals of very different nature and belonging to different acoustic spaces, and exploits many audio effects including non-linear processes. In the present paper we discuss these differences within the strongly emerging framework of active music listening, which is precisely at the crossroads of these two worlds: it consists in giving to the listener the ability to manipulate the different musical sources while listening to a musical piece. We propose a model that allows the description of a general studio mixing process as a linear stationary process of "generalized source image signals" considered as individual tracks. Such a model can be used to allow the recovery of the isolated tracks while preserving the professional sound quality of the mixture. A simple addition of these recovered tracks enables the end-user to recover the full-quality stereo mix, while these tracks can also be used for, e.g., basic remix / karaoke / soloing and re-orchestration applications.
机译:在信号处理文献中所说的音频信号的混合/解析(“源分离”问题)和工作室中的音乐生产仍然是相当分开的世界。科学音频场景分析相当侧重于“自然”混合物,并且大多数常常使用位于相同声学空间中的点源的线性(卷曲)模型。相比之下,声音工程师可以混合非常不同的性质和属于不同的声学空间的音乐信号,并利用许多音频效应,包括非线性过程。在本文中,我们在积极音乐聆听框架内讨论了这些差异,这正是这两个世界的十字路口:它包括给听众在听音乐作品时操纵不同音乐来源的能力。我们提出了一种模型,其允许将常规工作室混合过程描述为作为单个轨道被认为的“广义源图像信号”的线性固定过程。这种模型可用于允许恢复隔离的轨道,同时保留混合物的专业音质。简单地添加这些恢复的曲目使得最终用户能够恢复全质量的立体声混音,而这些轨道也可以用于例如基本混合/卡拉OK /独奏和重编程应用。

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