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A hybrid approach to singing pitch extraction based on trend estimation and hidden Markov models

机译:基于趋势估计和隐马尔可夫模型的歌唱沥青提取的混合方法

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In this paper, we propose a hybrid method for singing pitch extraction from polyphonic audio music. We have observed several kinds of pitch errors made by a previously proposed algorithm based on trend estimation. We also noticed that other pitch tracking methods tend to have other types of pitch error. Then it becomes intuitive to combine the results of several pitch trackers to achieve a better accuracy. In this paper, we adopt 3 methods as a committee to determine the pitch, including the trend-estimation-based method for forward and backward signals, and training-based HMM method. Experimental results demonstrate that the proposed approach outperforms the best algorithm for the task of audio melody extraction in MIREX 2010.
机译:在本文中,我们提出了一种用于从多汉音频音乐唱歌的混合方法。我们已经观察到了基于趋势估计的先前提出的算法制成的几种音调误差。我们还注意到其他俯仰跟踪方法往往具有其他类型的音高误差。然后将多个音调跟踪器的结果与实现更好的准确性变得直观。在本文中,我们采用3种方法作为委员会来确定音高,包括基于趋势估计的前向和向后信号的方法,以及基于培训的HMM方法。实验结果表明,该方法优于Mirex 2010中音频旋律提取任务的最佳算法。

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