论文标题
信号混合物与可区分词典的概率建模
Probabilistic Modelling of Signal Mixtures with Differentiable Dictionaries
论文作者
论文摘要
我们介绍了一种新颖的方式，将先前的信息纳入（半）监督的非负矩阵分解中，我们称之为可区分的字典搜索。它使一般，高度柔韧性和原则性建模对非线性源是线性混合的混合物。我们研究其在音频分解任务上的行为，并对其建模能力进行广泛的，高度对照的研究。
We introduce a novel way to incorporate prior information into (semi-) supervised non-negative matrix factorization, which we call differentiable dictionary search. It enables general, highly flexible and principled modelling of mixtures where non-linear sources are linearly mixed. We study its behavior on an audio decomposition task, and conduct an extensive, highly controlled study of its modelling capabilities.
