Overlapping Singer Identification in Music Recordings

Wei-Ho Tsai, Cin-Hao Ma
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Abstract

Singer identification (SID), which refers to the task of automatically identifying the singer(s) in a music recording, is of great help in handling the rapid proliferation of music data on the internet and digital media. Although a number of SID studies from acoustic features have been reported, most systems are designed to identify the singer in recordings of solo performances. Very little research has considered a more realistic case, which is to identify more than one singer in a music recording. The research presented in this chapter investigates the feasibility of identifying singers in music recordings that contain overlapping (simultaneous) singing voices (e.g., duet or trio singings). This problem is referred to as overlapping singer identification (OSID). Several approaches to OSID are discussed and evaluated in this chapter. In addition, a related issue on how to distinguish solo singings from overlapping singing recordings is also discussed.
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音乐录音中的重叠歌手识别
歌手识别(SID)是指在音乐录音中自动识别歌手的任务,它对处理互联网和数字媒体上快速增长的音乐数据有很大的帮助。虽然已经报道了一些声学特征的SID研究,但大多数系统都是为了识别独奏表演录音中的歌手而设计的。很少有研究考虑到更现实的情况,即在音乐录音中识别多个歌手。本章的研究探讨了在音乐录音中识别歌手的可行性,这些录音中包含重叠(同时)唱歌的声音(例如,二重唱或三重唱)。这个问题被称为重叠歌手识别(OSID)。本章讨论和评估了几种OSID方法。此外,还讨论了如何区分独唱和重叠演唱录音的相关问题。
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