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Published in: Journal of Digital Imaging 6/2013

01-12-2013

Learning Curve of Speech Recognition

Authors: Tomi A. Kauppinen, Johanna Kaipio, Mika P. Koivikko

Published in: Journal of Imaging Informatics in Medicine | Issue 6/2013

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Abstract

Speech recognition (SR) speeds patient care processes by reducing report turnaround times. However, concerns have emerged about prolonged training and an added secretarial burden for radiologists. We assessed how much proofing radiologists who have years of experience with SR and radiologists new to SR must perform, and estimated how quickly the new users become as skilled as the experienced users. We studied SR log entries for 0.25 million reports from 154 radiologists and after careful exclusions, defined a group of 11 experienced radiologists and 71 radiologists new to SR (24,833 and 122,093 reports, respectively). Data were analyzed for sound file and report lengths, character-based error rates, and words unknown to the SR’s dictionary. Experienced radiologists corrected 6 characters for each report and for new users, 11. Some users presented a very unfavorable learning curve, with error rates not declining as expected. New users’ reports were longer, and data for the experienced users indicates that their reports, initially equally lengthy, shortened over a period of several years. For most radiologists, only minor corrections of dictated reports were necessary. While new users adopted SR quickly, with a subset outperforming experienced users from the start, identification of users struggling with SR will help facilitate troubleshooting and support.
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Metadata
Title
Learning Curve of Speech Recognition
Authors
Tomi A. Kauppinen
Johanna Kaipio
Mika P. Koivikko
Publication date
01-12-2013
Publisher
Springer US
Published in
Journal of Imaging Informatics in Medicine / Issue 6/2013
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-013-9614-7

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