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://aclanthology.org/N18-1195
- DOI:
- 10.18653/v1/N18-1195
- Cite (ACL):
- Anastassia Loukina, Van Rynald T. Liceralde, and Beata Beigman Klebanov. 2018. Towards Understanding Text Factors in Oral Reading. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 2143–2154, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Towards Understanding Text Factors in Oral Reading (Loukina et al., NAACL 2018)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/N18-1195.pdf