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Monaural speech/music source separation using discrete energy separation algorithm

机译:使用离散能量分离算法的单声道语音/音乐源分离

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In this paper, we address the problem of monaural source separation of a mixed signal containing speech and music components. We use Discrete Energy Separation Algorithm (DESA) to estimate frequency-modulating (FM) signal energy. The FM signal energy is used to design a time-varying filter in the time-frequency domain for rejecting the interfering signal. The FM signal energy was chosen due to its good ability to differentiate between speech and music signals using localized information both in time and frequency. We present experimental results which demonstrate the advantages and limitations of the proposed method using synthetic data and real audio signals.
机译:在本文中,我们解决了包含语音和音乐成分的混合信号的单声道信号源分离问题。我们使用离散能量分离算法(DESA)来估计调频(FM)信号能量。 FM信号能量用于在时频域中设计时变滤波器,以抑制干扰信号。之所以选择FM信号能量,是因为它具有使用时间和频率方面的局部信息来区分语音和音乐信号的良好能力。我们目前的实验结果证明了使用合成数据和真实音频信号提出的方法的优点和局限性。

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