A Chinese Heart Failure Status Speech Database with Universal and Personalised Classification

TL;DR

This paper introduces the first Chinese speech database for heart failure detection, demonstrating the effectiveness of speech analysis in identifying HF and highlighting individual differences as key factors affecting accuracy.

Contribution

It presents a novel Chinese HF speech database with paired recordings and proposes an adaptive frequency filter for frequency importance analysis, advancing HF detection research in Chinese.

Findings

Chinese speech contains HF-related information.

Personalised classification improves detection accuracy.

Individual differences significantly impact classification performance.

Abstract

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.