Automatic Anomaly Detection for Dysarthria across Two Speech Styles: Read vs Spontaneous Speech

Imed Laaridh, Corinne Fredouille, Christine Meunier


Abstract
Perceptive evaluation of speech disorders is still the standard method in clinical practice for the diagnosing and the following of the condition progression of patients. Such methods include different tasks such as read speech, spontaneous speech, isolated words, sustained vowels, etc. In this context, automatic speech processing tools have proven pertinence in speech quality evaluation and assistive technology-based applications. Though, a very few studies have investigated the use of automatic tools on spontaneous speech. This paper investigates the behavior of an automatic phone-based anomaly detection system when applied on read and spontaneous French dysarthric speech. The behavior of the automatic tool reveals interesting inter-pathology differences across speech styles.
Anthology ID:
L16-1316
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
1998–2004
Language:
URL:
https://aclanthology.org/L16-1316
DOI:
Bibkey:
Cite (ACL):
Imed Laaridh, Corinne Fredouille, and Christine Meunier. 2016. Automatic Anomaly Detection for Dysarthria across Two Speech Styles: Read vs Spontaneous Speech. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 1998–2004, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Automatic Anomaly Detection for Dysarthria across Two Speech Styles: Read vs Spontaneous Speech (Laaridh et al., LREC 2016)
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PDF:
https://aclanthology.org/L16-1316.pdf