利用相位差分离声源和可靠掩模选择

Chanwoo Kim, Anjali Menon, M. Bacchiani, R. Stern
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引用次数: 8

摘要

本文提出了一种可靠掩模选择-相位差信道加权(RMS-PDCW)算法,该算法利用相位差信息计算的到达角(AoA)信息来选择被噪声源掩盖的目标源。RMS-PDCW算法利用局部声源信息和语音起始检测选择掩码进行应用。我们证明,该算法比基线声学模型显示出相对5.3%的改进,该模型在模拟测试集上使用2200万个话语进行多风格训练,该模拟测试集由真实世界和干扰扬声器噪声组成,混响时间分布在0 ms到900 ms之间,信噪比分布在0 dB到clean之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sound Source Separation Using Phase Difference and Reliable Mask Selection Selection
We present an algorithm called Reliable Mask Selection-Phase Difference Channel Weighting (RMS-PDCW) which selects the target source masked by a noise source using the Angle of Arrival (AoA) information calculated using the phase difference information. The RMS-PDCW algorithm selects masks to apply using the information about the localized sound source and the onset detection of speech. We demonstrate that this algorithm shows relatively 5.3 percent improvement over the baseline acoustic model, which was multistyle-trained using 22 million utterances on the simulated test set consisting of real-world and interfering-speaker noise with reverberation time distribution between 0 ms and 900 ms and SNR distribution between 0 dB up to clean.
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