Automated speech analysis enables MCI diagnosis. Themistocleous, C., Eckerström, M., & Kokkinakis, D. In Proceedings of 11th International Conference of Experimental Linguistics, 2020. ExLing Society. ![Automated speech analysis enables MCI diagnosis [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper doi abstract bibtex Mild Cognitive Impairment (MCI) is a condition characterized by cognitive decline greater than expected for an individual's age and education level. In this study, we are investigating whether acoustic properties of speech production can improve the classification of individuals with MCI from healthy controls augmenting the Mini Mental State Examination, a traditional screening tool, with automatically extracted acoustic information. We found that just one acoustic feature, can improve the AUC score (measuring a trade-off between sensitivity and specificity) from 0.77 to 0.89 in a boosting classification task. These preliminary results suggest that computerized language analysis can improve the accuracy of traditional screening tools.
@inproceedings{themistocleous_automated_2020,
title = {Automated speech analysis enables {MCI} diagnosis},
isbn = {9786188458512},
url = {https://exlingsociety.com/wp-content/uploads/proceedings/exling-2020/11_0047_000462.pdf},
doi = {10.36505/ExLing-2020/11/0050/000465},
abstract = {Mild Cognitive Impairment (MCI) is a condition characterized by cognitive decline greater than expected for an individual's age and education level. In this study, we are investigating whether acoustic properties of speech production can improve the classification of individuals with MCI from healthy controls augmenting the Mini Mental State Examination, a traditional screening tool, with automatically extracted acoustic information. We found that just one acoustic feature, can improve the AUC score (measuring a trade-off between sensitivity and specificity) from 0.77 to 0.89 in a boosting classification task. These preliminary results suggest that computerized language analysis can improve the accuracy of traditional screening tools.},
urldate = {2025-04-17},
booktitle = {Proceedings of 11th {International} {Conference} of {Experimental} {Linguistics}},
publisher = {ExLing Society},
author = {Themistocleous, Charalambos and Eckerström, Marie and Kokkinakis, Dimitrios},
year = {2020},
}
Downloads: 0
{"_id":"ehgyQLY5Ert7YDi67","bibbaseid":"themistocleous-eckerstrm-kokkinakis-automatedspeechanalysisenablesmcidiagnosis-2020","author_short":["Themistocleous, C.","Eckerström, M.","Kokkinakis, D."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","title":"Automated speech analysis enables MCI diagnosis","isbn":"9786188458512","url":"https://exlingsociety.com/wp-content/uploads/proceedings/exling-2020/11_0047_000462.pdf","doi":"10.36505/ExLing-2020/11/0050/000465","abstract":"Mild Cognitive Impairment (MCI) is a condition characterized by cognitive decline greater than expected for an individual's age and education level. In this study, we are investigating whether acoustic properties of speech production can improve the classification of individuals with MCI from healthy controls augmenting the Mini Mental State Examination, a traditional screening tool, with automatically extracted acoustic information. We found that just one acoustic feature, can improve the AUC score (measuring a trade-off between sensitivity and specificity) from 0.77 to 0.89 in a boosting classification task. These preliminary results suggest that computerized language analysis can improve the accuracy of traditional screening tools.","urldate":"2025-04-17","booktitle":"Proceedings of 11th International Conference of Experimental Linguistics","publisher":"ExLing Society","author":[{"propositions":[],"lastnames":["Themistocleous"],"firstnames":["Charalambos"],"suffixes":[]},{"propositions":[],"lastnames":["Eckerström"],"firstnames":["Marie"],"suffixes":[]},{"propositions":[],"lastnames":["Kokkinakis"],"firstnames":["Dimitrios"],"suffixes":[]}],"year":"2020","bibtex":"@inproceedings{themistocleous_automated_2020,\n\ttitle = {Automated speech analysis enables {MCI} diagnosis},\n\tisbn = {9786188458512},\n\turl = {https://exlingsociety.com/wp-content/uploads/proceedings/exling-2020/11_0047_000462.pdf},\n\tdoi = {10.36505/ExLing-2020/11/0050/000465},\n\tabstract = {Mild Cognitive Impairment (MCI) is a condition characterized by cognitive decline greater than expected for an individual's age and education level. In this study, we are investigating whether acoustic properties of speech production can improve the classification of individuals with MCI from healthy controls augmenting the Mini Mental State Examination, a traditional screening tool, with automatically extracted acoustic information. We found that just one acoustic feature, can improve the AUC score (measuring a trade-off between sensitivity and specificity) from 0.77 to 0.89 in a boosting classification task. These preliminary results suggest that computerized language analysis can improve the accuracy of traditional screening tools.},\n\turldate = {2025-04-17},\n\tbooktitle = {Proceedings of 11th {International} {Conference} of {Experimental} {Linguistics}},\n\tpublisher = {ExLing Society},\n\tauthor = {Themistocleous, Charalambos and Eckerström, Marie and Kokkinakis, Dimitrios},\n\tyear = {2020},\n}\n\n\n\n","author_short":["Themistocleous, C.","Eckerström, M.","Kokkinakis, D."],"key":"themistocleous_automated_2020","id":"themistocleous_automated_2020","bibbaseid":"themistocleous-eckerstrm-kokkinakis-automatedspeechanalysisenablesmcidiagnosis-2020","role":"author","urls":{"Paper":"https://exlingsociety.com/wp-content/uploads/proceedings/exling-2020/11_0047_000462.pdf"},"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://bibbase.org/zotero-group/Inter_Linguistic_Sociey/5953948","dataSources":["wqFBtZsLZwQqPkACg"],"keywords":[],"search_terms":["automated","speech","analysis","enables","mci","diagnosis","themistocleous","eckerström","kokkinakis"],"title":"Automated speech analysis enables MCI diagnosis","year":2020}