Text vs. Transcription: A Study of Differences Between the Writing and Speeches of U.S. Presidents

Mina Rajaei Moghadam, Mosab Rezaei, Gülşat Aygen, Reva Freedman


Abstract
Even after many years of research, answering the question of the differences between spoken and written text remains open. This paper aims to study syntactic features that can serve as distinguishing factors. To do so, we focus on the transcribed speeches and written books of United States presidents. We conducted two experiments to analyze high-level syntactic features. In the first experiment, we examine these features while controlling for the effect of sentence length. In the second experiment, we compare the high-level syntactic features with low-level ones. The results indicate that adding high-level syntactic features enhances model performance, particularly in longer sentences. Moreover, the importance of the prepositional phrases in a sentence increases with sentence length. We also find that these longer sentences with more prepositional phrases are more likely to appear in speeches than in written books by U.S. presidents.
Anthology ID:
2024.nlp4dh-1.35
Volume:
Proceedings of the 4th International Conference on Natural Language Processing for Digital Humanities
Month:
November
Year:
2024
Address:
Miami, USA
Editors:
Mika Hämäläinen, Emily Öhman, So Miyagawa, Khalid Alnajjar, Yuri Bizzoni
Venue:
NLP4DH
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
352–361
Language:
URL:
https://aclanthology.org/2024.nlp4dh-1.35
DOI:
Bibkey:
Cite (ACL):
Mina Rajaei Moghadam, Mosab Rezaei, Gülşat Aygen, and Reva Freedman. 2024. Text vs. Transcription: A Study of Differences Between the Writing and Speeches of U.S. Presidents. In Proceedings of the 4th International Conference on Natural Language Processing for Digital Humanities, pages 352–361, Miami, USA. Association for Computational Linguistics.
Cite (Informal):
Text vs. Transcription: A Study of Differences Between the Writing and Speeches of U.S. Presidents (Rajaei Moghadam et al., NLP4DH 2024)
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PDF:
https://aclanthology.org/2024.nlp4dh-1.35.pdf