Enhancementof a desired speech signal in the presence of competing or interfering speech remains an unsolved problem, as it can be hard to determine which of the speech signals is the one of interest. In this paper, we propose a multichannel noise reduction algorithm which uses the presence of the user’s own voice signal, e.g. during conversations with the target speaker, as an asset to efficiently identify interfering speech and noise. Specifically, following the typical speech pattern in natural conversations, the presence of an own voice may indicate the absence of the target speech, hence undesired speech and noise can be identified and estimated during own voice presence. In contrast to conventional noise reduction systems, the proposed noise reduction systems use the user’s own voice to identify interfering speech that otherwise could be confused with the target speech. We demonstrate the performance of the proposed noise reduction systems in a comparison against state-of-the-art noise reduction systems in terms of beamforming performance for hearing assistive devices. The results show that the proposed beamforming scheme in particular outperforms state-of-the-art methods in terms of ESTOI and PESQ in situations with a target speaker and a strong interfering speaker.

中文翻译：

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用于听力辅助设备的基于语音的干扰语音抑制的多通道语音增强


在存在竞争或干扰语音的情况下增强期望的语音信号仍然是一个未解决的问题，因为很难确定哪个语音信号是感兴趣的。在本文中，我们提出了一种多通道降噪算法，该算法使用用户自己的语音信号的存在（例如在与目标说话者对话期间）作为有效识别干扰语音和噪声的资产。具体地，遵循自然对话中的典型语音模式，自己的语音的存在可以指示目标语音的不存在，因此可以在自己的语音存在期间识别和估计不期望的语音和噪声。与传统的降噪系统相比，所提出的降噪系统使用用户自己的语音来识别干扰语音，否则该干扰语音可能与目标语音混淆。我们在听力辅助设备的波束成形性能方面与最先进的降噪系统进行比较，展示了所提出的降噪系统的性能。结果表明，在存在目标扬声器和强干扰扬声器的情况下，所提出的波束形成方案在 ESTOI 和 PESQ 方面尤其优于最先进的方法。