A speech corpus for chronic kidney disease
This provides a dataset for pathological voice analysis and illness identification in CKD patients, but it is incremental as it focuses on data collection rather than novel methods.
The study tackled the problem of analyzing speech in chronic kidney disease (CKD) patients by creating a corpus of 289 patients and comparing it to a control group, revealing differences in voice quality, pronunciation, prosody, glottal source, and aerodynamic parameters.
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.