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Simultaneous processing of sound source separation and musical instrument identification using Bayesian spectral modeling

机译:使用贝叶斯频谱建模同时处理声源分离和乐器识别

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This paper presents a method of both separating audio mixtures into sound sources and identifying the musical instruments of the sources. A statistical tone model of the power spectrogram, called an integrated model, is defined and source separation and instrument identification are carried out on the basis of Bayesian inference. Since, the parameter distributions of the integrated model depend on each instrument, the instrument name is identified by selecting the one that has the maximum relative instrument weight. Experimental results showed correct instrument identification enables precise source separation even when many overtones overlap.
机译:本文提出了一种既将混合音频分离成声源又识别声源的乐器的方法。定义了功率谱图的统计音调模型(称为集成模型),并基于贝叶斯推断进行了源分离和仪器识别。由于集成模型的参数分布取决于每种仪器,因此可以通过选择具有最大相对仪器重量的仪器来识别仪器名称。实验结果表明,即使许多泛音重叠,正确的仪器识别也可以实现精确的信号源分离。

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