We present a system for automated phonetic clustering analysis of cognitive tests of phonemic verbal fluency, on which one must name words starting with a specific letter (e.g., 'F') for one minute. Test responses are typically subjected to manual phonetic clustering analysis that is labor-intensive and subject to inter-rater variability. Our system provides an automated alternative. In a pilot study, we applied this system to tests of 55 novice and experienced professional fighters (boxers and mixed martial artists) and found that experienced fighters produced significantly longer chains of phonetically similar words, while no differences were found in the total number of words produced. These findings are preliminary, but strongly suggest that our system can be used to detect subtle signs of brain damage due to repetitive head trauma in individuals that are otherwise unimpaired.
|Original language||English (US)|
|Title of host publication||Short Papers|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||6|
|State||Published - 2013|
|Event||51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria|
Duration: Aug 4 2013 → Aug 9 2013
|Name||ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference|
|Other||51st Annual Meeting of the Association for Computational Linguistics, ACL 2013|
|Period||8/4/13 → 8/9/13|
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