Have a Cake and Eat it Too: Assessing Discriminating Performance of an Intelligibility Index Obtained from a Reduced Sample Size

Anna Marczyk, Alain Ghio, Muriel Lalain, Marie Rebourg, Corinne Fredouille, Virginie Woisard


Abstract
This paper investigates random vs. phonetically motivated reduction of linguistic material used in an intelligibility task in speech disordered populations and the subsequent impact on the discrimination classifier quantified by the area under the receiver operating characteristics curve (AUC of ROC). The comparison of obtained accuracy indexes shows that when the sample size is reduced based on a phonetic criterium—here, related to phonotactic complexity—, the classifier has a higher ranking ability than when the linguistic material is arbitrarily reduced. Crucially, downsizing the linguistic sample to about 30% of the original dataset does not diminish the discriminatory performance of the classifier. This result is of significant interest to both clinicians and patients as it validates a tool that is both reliable and efficient.
Anthology ID:
2020.lrec-1.221
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
1791–1795
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.221
DOI:
Bibkey:
Cite (ACL):
Anna Marczyk, Alain Ghio, Muriel Lalain, Marie Rebourg, Corinne Fredouille, and Virginie Woisard. 2020. Have a Cake and Eat it Too: Assessing Discriminating Performance of an Intelligibility Index Obtained from a Reduced Sample Size. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 1791–1795, Marseille, France. European Language Resources Association.
Cite (Informal):
Have a Cake and Eat it Too: Assessing Discriminating Performance of an Intelligibility Index Obtained from a Reduced Sample Size (Marczyk et al., LREC 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.lrec-1.221.pdf