Speech- and Text-driven Features for Automated Scoring of English Speaking Tasks

Anastassia Loukina, Nitin Madnani, Aoife Cahill


Abstract
We consider the automatic scoring of a task for which both the content of the response as well its spoken fluency are important. We combine features from a text-only content scoring system originally designed for written responses with several categories of acoustic features. Although adding any single category of acoustic features to the text-only system on its own does not significantly improve performance, adding all acoustic features together does yield a small but significant improvement. These results are consistent for responses to open-ended questions and to questions focused on some given source material.
Anthology ID:
W17-4609
Volume:
Proceedings of the Workshop on Speech-Centric Natural Language Processing
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
67–77
Language:
URL:
https://www.aclweb.org/anthology/W17-4609
DOI:
10.18653/v1/W17-4609
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-4609.pdf