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An Introduction to Energy‐Based Blind Separating Algorithm for Speech Signals

机译:基于能量的语音信号盲分离算法简介

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We introduce the Energy‐Based Blind Separating (EBS) algorithm for extremely fast separation of mixed speech signals without loss of quality, which is performed in two stages: iterative‐form separation and closed‐form separation. This algorithm significantly improves the separation speed simply due to incorporating only some specific frequency bins into computations. Simulation results show that, on average, the proposed algorithm is 43 times faster than the independent component analysis (ICA) for speech signals, while preserving the separation quality. Also, it outperforms the fast independent component analysis (FastICA), the joint approximate diagonalization of eigenmatrices (JADE), and the second‐order blind identification (SOBI) algorithm in terms of separation quality.
机译:我们引入了基于能量的盲分离(EBS)算法,可在不损失质量的情况下极快地分离混合语音信号,该算法分两个阶段执行:迭代形式分离和闭合形式分离。该算法仅通过将一些特定的频率仓合并到计算中即可显着提高分离速度。仿真结果表明,在保持分离质量的同时,该算法平均比语音信号的独立分量分析(ICA)快43倍。而且,在分离质量方面,它优于快速独立成分分析(FastICA),特征矩阵联合近似对角化(JADE)和二阶盲识别(SOBI)算法。

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