A Chinese Heart Failure Status Speech Database with Universal and Personalised Classification
This addresses the lack of Chinese speech data for heart failure detection, which could enable cost-effective monitoring for Chinese-speaking patients.
This study created the first Chinese speech database of heart failure patients with paired recordings before and after hospitalization, confirming that Chinese syllables contain HF-related information and showing effectiveness in both standard patient-wise and personalized pair-wise classification approaches.
Speech is a cost-effective and non-intrusive data source for identifying acute and chronic heart failure (HF). However, there is a lack of research on whether Chinese syllables contain HF-related information, as observed in other well-studied languages. This study presents the first Chinese speech database of HF patients, featuring paired recordings taken before and after hospitalisation. The findings confirm the effectiveness of the Chinese language in HF detection using both standard 'patient-wise' and personalised 'pair-wise' classification approaches, with the latter serving as an ideal speaker-decoupled baseline for future research. Statistical tests and classification results highlight individual differences as key contributors to inaccuracy. Additionally, an adaptive frequency filter (AFF) is proposed for frequency importance analysis. The data and demonstrations are published at https://github.com/panyue1998/Voice_HF.