ArXiv Preprint
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.
Jihyun Mun, Sunhee Kim, Myeong Ju Kim, Jiwon Ryu, Sejoong Kim, Minhwa Chung
2022-11-03
