The Book of Nightmares

Ransom, W. M.; Kinnell, Galway

doi:10.2307/25294841

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, it may reduce time spent in manual annotation, increasing the amount of time clinicians spend interacting with patients face to face. Second, increased automation may lead to decreased variability in care delivery, a necessary step towards improving outcomes (Ransom et al, 2008). …”

Section: Discussionmentioning

confidence: 99%

Automated morphological analysis of clinical language samples

Gorman¹,

Bedrick²,

Kiss³

et al. 2015

Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Realit

View full text Add to dashboard Cite

Quantitative analysis of clinical language samples is a powerful tool for assessing and screening developmental language impairments, but requires extensive manual transcription, annotation, and calculation, resulting in error-prone results and clinical underutilization. We describe a system that performs automated morphological analysis needed to calculate statistics such as the mean length of utterance in morphemes (MLUM), so that these statistics can be computed directly from orthographic transcripts. Estimates of MLUM computed by this system are closely comparable to those produced by manual annotation. Our system can be used in conjunction with other automated annotation techniques, such as maze detection. This work represents an important first step towards increased automation of language sample analysis, and towards attendant benefits of automation, including clinical greater utilization and reduced variability in care delivery.

show abstract

Section: Discussionmentioning

confidence: 99%