Looks can be Deceptive: Distinguishing Repetition Disfluency from Reduplication
Arif A. Ahmad, Khyathi Gayathri Mothika, Pushpak Bhattacharyya
Abstract
Reduplication and repetition, though similar in form, serve distinct linguistic purposes. Reduplication is a deliberate morphological process used to express grammatical, semantic, or pragmatic nuances, while repetition is often unintentional and indicative of disfluency. This paper presents the first large-scale study of reduplication and repetition in speech using computational linguistics. We introduce IndicRedRep, a new publicly available dataset containing Hindi, Telugu, and Marathi text annotated with reduplication and repetition at the word level. We evaluate transformer-based models for multi-class reduplication and repetition token classification, utilizing the Reparandum-Interregnum-Repair structure to distinguish between the two phenomena. Our models achieve macro F1 scores of up to 85.62% in Hindi, 83.95% in Telugu, and 84.82% in Marathi for reduplication-repetition classification.
BibTeX
@inproceedings{ahmad-etal-2025-looks,
title = "Looks can be Deceptive: Distinguishing Repetition Disfluency from Reduplication",
author = "Ahmad, Arif A. and
Mothika, Khyathi Gayathri and
Bhattacharyya, Pushpak",
editor = "Rambow, Owen and
Wanner, Leo and
Apidianaki, Marianna and
Al-Khalifa, Hend and
Eugenio, Barbara Di and
Schockaert, Steven",
booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.coling-main.15/",
pages = "214--229"
}