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Automatic evaluation of noise suppression in speech signal recorded during phonation in the open-air MRI

机译:在露天MRI中录音期间记录的语音信号中噪声抑制的自动评估

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The paper is focused on the evaluation of successfulness of noise reduction of the speech signal recorded in an open-air magnetic resonance imager during a phonation for the 3D human vocal tract modeling. In more detail is there described the automatic evaluation method based on Gaussian mixture models (GMM) classification. Performed first-step experiments have successfully confirmed that the proposed GMM classifier of the speech quality is functional and fully comparable with the standard evaluation based on the listening test.
机译:该纸张专注于评估在3D人声道建模的发声期间在露天磁共振成像器中记录在露天磁共振成像仪中记录的噪声信号的成功。更详细的是,基于高斯混合模型(GMM)分类的自动评估方法。执行的第一步实验已成功证实,语音质量的提议GMM分类器是功能性的,并与基于聆听测试的标准评估完全相当。

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