---
title: "Determinants of Hesitations and Repetitions in — Sharma 2026"
description: "The paper asks which linguistic properties of neighbouring words make speakers of Hindi, an SOV language, produce disfluencies."
authors: ["Eashani Sharma", "Ishita Arun", "Samar Husain"]
year: 2026
venue: "Proceedings of the Society for Computation in Linguistics 2026"
source: "https://aclanthology.org/2026.scil-main.7/"
doi: "10.18653/v1/2026.scil-main.7"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/sharma-2026-determinants-hesitations-repetitions-hindi-spontaneous/"
---
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# Determinants of Hesitations and Repetitions in Hindi Spontaneous Speech

**Authors:** Eashani Sharma, Ishita Arun, [Samar Husain](https://md.research.elamur.ai/free/en/authors/samar-husain/) · **Year:** 2026 · **Venue:** Proceedings of the Society for Computation in Linguistics 2026 · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.scil-main.7/) · [PDF](https://aclanthology.org/2026.scil-main.7.pdf) · [DOI 10.18653/v1/2026.scil-main.7](https://doi.org/10.18653/v1/2026.scil-main.7) · [OpenAlex](https://openalex.org/W7166849546)

**Citations:** 0 citations (openalex-snapshot · 2026-10-14)

## Summary
The paper asks which linguistic properties of neighbouring words make speakers of Hindi, an SOV language, produce disfluencies. Most corpus work on this question has studied English, mainly Switchboard. The authors use the IIT Delhi Hindi Dialog Corpus, which consists of telephone conversations from CALLFRIEND Hindi annotated in CoNLL-U with token-level disfluency tags. They compare filled pauses (hesitations) and repetitions against length-matched fluent control sentences.

For the words just before and just after each disfluency, they compute:
- **lexical measures:** frequency, bigram probability, semantic similarity
- **structural measures:** surprisal, integration cost
- **phonological measures:** syllable count, CV-based phonotactic complexity

These features feed mixed-effects logistic regression models. A PRAAT-based prosodic analysis was run on a subset of the hesitation data.

The two disfluency types behave differently:
- Hesitations respond to difficulty on both sides of the disruption.
- Repetitions depend mostly on the upcoming word.
- Phonological complexity predicts both types.

Unlike findings for English, difficulty already encountered also raises disfluency rates. The authors suggest that word-order typology shapes production planning, which argues for more cross-linguistic disfluency research.

## Key points
- **Data:** the IIT Delhi Hindi Dialog Corpus has 60 conversations and 39,244 gold-annotated sentences with UPOS and dependency relations. Disfluencies are marked in the MISC column with Hesitation and Disfluency tags. 2,289 utterances (5.8%) contain hesitations and 1,379 (3.6%) contain repetitions.
- **Final modelling sets:** 1,794 sentences for hesitations (897 target plus 897 controls) and 1,560 for repetitions (780 plus 780). Utterances with sentence-initial or sentence-final disfluencies were dropped.
- **Models:** glmer models were fitted with lme4 in R, using conversation ID as a random intercept and model-specific interaction terms (frequency × length for hesitations, frequency × semantic similarity for repetitions).
- **Repetition results:** some effects ran against predictability accounts. A higher bigram probability of the next word increased repetitions, while higher integration cost reduced them.
- **Prosody:** words surrounding hesitations had longer durations. The hesitation tokens themselves showed lower pitch and lower intensity.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{sharma2026determinants,
  title = {{Determinants of Hesitations and Repetitions in Hindi Spontaneous Speech}},
  author = {Sharma, Eashani and Arun, Ishita and Husain, Samar},
  booktitle = {Proceedings of the Society for Computation in Linguistics 2026},
  year = {2026},
  doi = {10.18653/v1/2026.scil-main.7},
  url = {https://doi.org/10.18653/v1/2026.scil-main.7}
}
```

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