The performance of voice-based Parkinson’s disease (PD) detection systems degrades when there is an acoustic mismatch between training and operating conditions caused mainly by degradation in test signals. In this paper, we address this mismatch by considering three types of degradation commonly encountered in remote voice analysis, namely background noise, reverberation and nonlinear distortion, and investigate how these degradations influence the performance of a PD detection system. Given that the specific degradation is known, we explore the effectiveness of a variety of enhancement algorithms in compensating this mismatch and improving the PD detection accuracy. Then, we propose two approaches to automatically control the quality of recordings by identifying the presence and type of short-term and long-term degradations and protocol violations in voice signals. Finally, we experiment with using the proposed quality control methods to inform the choice of enhancement algorithm. Experimental results using the voice recordings of the mPower mobile PD data set under different degradation conditions show the effectiveness of the quality control approaches in selecting an appropriate enhancement method and, consequently, in improving the PD detection accuracy. This study is a step towards the development of a remote PD detection system capable of operating in unseen acoustic environments.

当训练和操作条件之间存在声学失配时，基于语音的帕金森氏病（PD）检测系统的性能会下降，这主要是由于测试信号的下降引起的。在本文中，我们通过考虑远程语音分析中常见的三种类型的降级来解决这种不匹配问题，即背景噪声，混响和非线性失真，并研究这些降级如何影响PD检测系统的性能。鉴于已知特定的降级，我们探索了各种增强算法在补偿这种失配并提高PD检测精度方面的有效性。然后，我们提出了两种方法，通过识别语音信号中短期和长期劣化以及协议违规的存在和类型来自动控制录音质量。最后，我们尝试使用提出的质量控制方法来告知增强算法的选择。使用mPower移动PD数据集在不同降级条件下的录音的实验结果表明，质量控制方法在选择合适的增强方法方面有效，因此在提高PD检测精度方面也很有效。这项研究是朝着开发能够在看不见的声音环境中运行的远程PD检测系统迈出的一步。我们尝试使用提出的质量控制方法来告知增强算法的选择。使用mPower移动PD数据集在不同降级条件下的录音的实验结果表明，质量控制方法在选择合适的增强方法方面有效，因此在提高PD检测精度方面也很有效。这项研究是朝着开发能够在看不见的声音环境中运行的远程PD检测系统迈出的一步。我们尝试使用提出的质量控制方法来告知增强算法的选择。使用mPower移动PD数据集在不同降级条件下的录音的实验结果表明，质量控制方法在选择合适的增强方法方面有效，因此在提高PD检测精度方面也很有效。这项研究是朝着开发能够在看不见的声音环境中运行的远程PD检测系统迈出的一步。