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Authors: Piotr Barycki ; Irene Murtagh and Barry Kirkpatrick

Affiliation: TU Dublin, Blanchardstown Campus, Dublin, Ireland

Keyword(s): Glottal Flow, Glottal Model, Pathological Speech, System Identification.

Abstract: This study proposes a new method of fitting a glottal model to the glottal flow estimate using system identification (SI) algorithms. Each period of the glottal estimate is split into open and closed phases and each phase is modelled as the output of a linear filter. This approach allows the parametric model fitting task to be cast as a system identification problem and sidesteps issues encountered with standard glottal parametrisation algorithms. The study compares the performance of two SI methods: Steiglitz-McBride and Prony. The tests were performed on synthetic glottal signals (n=121) and real speech (n=50 healthy, n=23 pathological). The effectiveness of the techniques is quantified by calculating the Normalised Root Mean Squared Error (NRMSE) between the estimated glottal fit and the glottal estimate. Tests on synthetic glottal signals show that the average performance of the Steiglitz-McBride method (97.25%) was better than the Prony method (70.41%). Real speech tests produce d results of 64.29% and 51.57% for healthy and pathological speech respectively. The results show that system identification techniques can produce robust parametric model estimates of the glottal waveform and that the Steiglitz-McBride method is superior to the Prony method for this task. (More)

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Paper citation in several formats:
Barycki, P.; Murtagh, I. and Kirkpatrick, B. (2019). System Identification Algorithms Applied to Glottal Model Fitting. In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS; ISBN 978-989-758-353-7; ISSN 2184-4305, SciTePress, pages 124-131. DOI: 10.5220/0007259801240131

@conference{biosignals19,
author={Piotr Barycki. and Irene Murtagh. and Barry Kirkpatrick.},
title={System Identification Algorithms Applied to Glottal Model Fitting},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS},
year={2019},
pages={124-131},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007259801240131},
isbn={978-989-758-353-7},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS
TI - System Identification Algorithms Applied to Glottal Model Fitting
SN - 978-989-758-353-7
IS - 2184-4305
AU - Barycki, P.
AU - Murtagh, I.
AU - Kirkpatrick, B.
PY - 2019
SP - 124
EP - 131
DO - 10.5220/0007259801240131
PB - SciTePress

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