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Novel approach to separation of musical signal sources by NMF

机译:NMF分离音乐信号源的新方法

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This paper proposes a method to separate polyphonic music signal into signals of each musical instrument by NMF: Non-negative Matrix Factorization based on preservation of spectrum envelope. Sound source separation is taken as a fundamental issue in music signal processing and NMF is becoming common to solve it because of its versatility and compatibility with music signal processing. Our method bases on a common feature of harmonic signal: spectrum envelopes of musical signal in close pitches played by the harmonic music instrument would be similar. We estimate power spectrums of each instrument by NMF with restriction to synchronize spectrum envelope of bases which are allocated to all possible center frequencies of each instrument. This manipulation means separation of components which refers to tones of each instrument and realizes both of separation without pre-training and separation of signal including harmonic and non-harmonic sound. We had an experiment to decompose mixture sound signal of MIDI instruments into each instrument and evaluated the result by SNR of single MIDI instrument sound signals and separated signals. As a result, SNR of lead guitar and drums approximately marked 3.6 and 6.0 dB and showed significance of our method.
机译:本文提出了一种利用NMF将和弦音乐信号分离为各种乐器信号的方法:基于频谱包络保留的非负矩阵分解。音源分离被视为音乐信号处理中的基本问题,而NMF由于其多功能性和与音乐信号处理的兼容性而变得越来越普遍。我们的方法基于谐波信号的一个共同特征:谐波乐器演奏的音调接近的音乐信号的频谱包络将相似。我们通过NMF估算每个仪器的功率谱,并限制其同步分配给每个仪器所有可能中心频率的碱基的频谱包络。这种操作意味着分离组件,这是指每种乐器的音调,并且在不进行预训练的情况下实现了分离,并且实现了包括谐波和非谐波声音在内的信号分离。我们进行了一项实验,将MIDI乐器的混合声音信号分解为每个乐器,并通过单个MIDI乐器声音信号和分离信号的SNR评估了结果。结果,主音吉他和鼓的SNR分别约为3.6和6.0 dB,显示了我们方法的重要性。

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