Document Type

Article

Journal/Book Title/Conference

The Journal of the Acoustical Society of America

Volume

145

Issue

1

Publisher

Acoustical Society of America

Publication Date

1-25-2019

First Page

392

Last Page

399

Abstract

Speech perception studies typically rely on trained research assistants to score orthographic listener transcripts for words correctly identified. While the accuracy of the human scoring protocol has been validated with strong intra- and inter-rater reliability, the process of hand-scoring the transcripts is time-consuming and resource intensive. Here, an open-source computer-based tool for automated scoring of listener transcripts is built (Autoscore) and validated on three different human-scored data sets. Results show that not only is Autoscore highly accurate, achieving approximately 99% accuracy, but extremely efficient. Thus, Autoscore affords a practical research tool, with clinical application, for scoring listener intelligibility of speech.

Comments

Copyright 2019 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.
The following article appeared in The Journal of the Acoustical Society of America 145, 392 (2019); doi: 10.1121/1.5087276 and may be found at https://asa.scitation.org/doi/abs/10.1121/1.5087276

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