Towards Understanding Text Factors in Oral Reading

Anastassia Loukina, Van Rynald T. Liceralde, Beata Beigman Klebanov


Abstract
Using a case study, we show that variation in oral reading rate across passages for professional narrators is consistent across readers and much of it can be explained using features of the texts being read. While text complexity is a poor predictor of the reading rate, a substantial share of variability can be explained by timing and story-based factors with performance reaching r=0.75 for unseen passages and narrator.
Anthology ID:
N18-1195
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2143–2154
Language:
URL:
https://www.aclweb.org/anthology/N18-1195
DOI:
10.18653/v1/N18-1195
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/N18-1195.pdf