Towards robust heart failure detection in digital telephony environments by utilizing transformer-based codec inversion

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Authors

Date

2025-09

Department

Department of Information and Communications Engineering

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Mcode

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Language

en

Pages

15

Series

Speech Communication, Volume 173

Abstract

This study introduces the Codec Transformer Network (CTN) to enhance the reliability of automatic heart failure (HF) detection from coded telephone speech by addressing codec-related challenges in digital telephony. The study specifically addresses the codec mismatch between training and inference in HF detection. CTN is designed to map the mel-spectrogram representations of encoded speech signals back to their original, non-encoded forms, thereby recovering HF-related discriminative information. The effectiveness of CTN is demonstrated in conjunction with three HF detectors, based on Support Vector Machine, Random Forest, and K-Nearest Neighbors classifiers. The results show that CTN effectively retrieves the discriminative information between patients and controls, and performs comparably to or better than a baseline approach, based on multi-condition training.

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Publisher Copyright: © 2025 The Authors

Keywords

Codec inversion, Heart failure detection, Speech codecs, Tele-monitoring, Transformer

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DOI

10.1016/j.specom.2025.103279

Citation

Tirronen, S, Javanmardi, F, Pohjalainen, H, Kadiri, S R, Mittapalle, K R, Helkkula, P, Kaitue, K, Minkkinen, M, Tolppanen, H, Nieminen, T & Alku, P 2025, 'Towards robust heart failure detection in digital telephony environments by utilizing transformer-based codec inversion', Speech Communication, vol. 173, 103279. https://doi.org/10.1016/j.specom.2025.103279

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https://urn.fi/URN:NBN:fi:aalto-202508075795

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