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使用源分离算法重新混音音乐以改善人工耳蜗使用者的音乐体验。

Remixing music using source separation algorithms to improve the musical experience of cochlear implant users.

作者信息

Pons Jordi, Janer Jordi, Rode Thilo, Nogueira Waldo

机构信息

Department of Otolaryngology, Medical University Hannover and Cluster of Excellence Hearing4all, Karl-Wiechert Allee 3, 30625, Hannover, Germany.

Music Technology Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra. Roc Boronat 138, 55.310, 08018 Barcelona, Spain.

出版信息

J Acoust Soc Am. 2016 Dec;140(6):4338. doi: 10.1121/1.4971424.

Abstract

Music perception remains rather poor for many Cochlear Implant (CI) users due to the users' deficient pitch perception. However, comprehensible vocals and simple music structures are well perceived by many CI users. In previous studies researchers re-mixed songs to make music more enjoyable for them, favoring the preferred music elements (vocals or beat) attenuating the others. However, mixing music requires the individually recorded tracks (multitracks) which are usually not accessible. To overcome this limitation, Source Separation (SS) techniques are proposed to estimate the multitracks. These estimated multitracks are further re-mixed to create more pleasant music for CI users. However, SS may introduce undesirable audible distortions and artifacts. Experiments conducted with CI users (N = 9) and normal hearing listeners (N = 9) show that CI users can have different mixing preferences than normal hearing listeners. Moreover, it is shown that CI users' mixing preferences are user dependent. It is also shown that SS methods can be successfully used to create preferred re-mixes although distortions and artifacts are present. Finally, CI users' preferences are used to propose a benchmark that defines the maximum acceptable levels of SS distortion and artifacts for two different mixes proposed by CI users.

摘要

由于人工耳蜗(CI)使用者的音高感知能力不足,他们对音乐的感知仍然相当差。然而,许多CI使用者能够很好地感知可理解的人声和简单的音乐结构。在先前的研究中,研究人员对歌曲进行重新混音,以使音乐对他们来说更具欣赏性,突出他们喜欢的音乐元素(人声或节拍),弱化其他元素。然而,混音需要单独录制的音轨(多轨),而这些音轨通常无法获取。为了克服这一限制,提出了源分离(SS)技术来估计多轨。这些估计出的多轨会进一步重新混音,为CI使用者创造出更悦耳的音乐。然而,源分离可能会引入不想要的可听失真和伪像。对CI使用者(N = 9)和正常听力听众(N = 9)进行的实验表明,CI使用者与正常听力听众可能有不同的混音偏好。此外,研究表明CI使用者的混音偏好因人而异。研究还表明,尽管存在失真和伪像,但源分离方法可以成功地用于创建偏好的重新混音。最后,利用CI使用者的偏好提出了一个基准,该基准定义了CI使用者提出的两种不同混音中源分离失真和伪像的最大可接受水平。

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