In this study, we present a speech corpus of patients with chronic kidney disease (CKD) that will be used for research on pathological voice analysis, automatic illness identification, and severity prediction. This paper introduces the steps involved in creating this corpus, including the choice of speech-related parameters and speech lists as well as the recording technique. The speakers in this corpus, 289 CKD patients with varying degrees of severity who were categorized based on estimated glomerular filtration rate (eGFR), delivered sustained vowels, sentence, and paragraph stimuli. This study compared and analyzed the voice characteristics of CKD patients with those of the control group; the results revealed differences in voice quality, phoneme-level pronunciation, prosody, glottal source, and aerodynamic parameters.

翻译：在此研究中,我们展示了慢性肾病患者的语音资料,用于研究病理语音分析、自动疾病识别和严重性预测,本文介绍了创建这一资料的步骤,包括选择与语言有关的参数和语音列表以及记录技术,该资料的讲演者有289名严重性不一的慢性肾病患者,这些患者根据估计的球状过滤率(eGFR)进行了分类,并提供了持续的元音、句子和段落刺激。本研究报告比较并分析了CKD患者与控制组患者的语音特征;研究结果揭示了声音质量、电话-水平发音、发音、发声、格洛特源和空气动力学参数的差异。