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Polyphonic Music Transcription by Nonnegative Matrix Factorization with Harmonicity and Temporality Criteria

机译:非负矩阵因式分解的调和性和时间性标准的和声音乐转录

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摘要

Non-negative matrix factorization (NMF) is widely used for music transcription because of its efficiency. However, the conventional NMF-based music transcription algorithm often causes harmonic confusion errors or time split-up errors, because the NMF decomposes the time-frequency data according to the activated frequency in its time. To solve these problems, we proposed an NMF with temporal continuity and harmonicity constraints. The temporal continuity constraint prevented the time split-up of the continuous time components, and the harmonicity constraint helped to bind the fundamental with harmonic frequencies by reducing the additional octave errors. The transcription performance of the proposed algorithm was compared with that of the conventional algorithms, which showed that the proposed method helped to reduce additional false errors and increased the overall transcription performance.
机译:非负矩阵分解(NMF)由于其效率高而被广泛用于音乐转录。但是,传统的基于NMF的音乐转录算法经常会引起谐波混淆错误或时间分割错误,因为NMF会根据其时间中的激活频率分解时频数据。为了解决这些问题,我们提出了具有时间连续性和谐波约束的NMF。时间连续性约束防止了连续时间分量的时间分裂,并且谐波约束通过减少附加的倍频程误差帮助将基频与谐波频率绑定在一起。将该算法的转录性能与常规算法的转录性能进行了比较,结果表明该方法有助于减少附加的错误错误,提高了总体转录性能。

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