---
title: "Say Again? The Limits of Whisper with Conversation. A Case"
description: "The paper asks how well Whisper preserves interactional material in spontaneous Italian dialogue, where ASR tools often… 40 references."
authors: ["Martina Simonotti", "Ludovica Pannitto", "Caterina Mauri", "Adriano Ferraresi", "Gabriele Carioli"]
year: 2026
venue: "Proceedings of Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC 2026"
source: "https://aclanthology.org/2026.speakable-1.3/"
doi: "10.63317/2so5y449gb4w"
licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)"
licence_url: "https://creativecommons.org/licenses/by-nc/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/simonotti-2026-say-again-limits-whisper-conversation/"
---
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# Say Again? The Limits of Whisper with Conversation. A Case Study on the KIParla Corpus.

**Authors:** [Martina Simonotti](https://md.research.elamur.ai/free/en/authors/martina-simonotti/), [Ludovica Pannitto](https://md.research.elamur.ai/free/en/authors/ludovica-pannitto/), [Caterina Mauri](https://md.research.elamur.ai/free/en/authors/caterina-mauri/), [Adriano Ferraresi](https://md.research.elamur.ai/free/en/authors/adriano-ferraresi/) and Gabriele Carioli · **Year:** 2026 · **Venue:** [Proceedings of Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC 2026](https://md.research.elamur.ai/free/en/venues/speakable/) ([Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC 2026](https://md.research.elamur.ai/free/en/venues/speakable/2026/)) · **Publisher:** [European Language Resources Association (ELRA)](https://md.research.elamur.ai/free/en/publishers/european-language-resources-association-elra/) · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.speakable-1.3/) · [PDF](https://aclanthology.org/2026.speakable-1.3.pdf) · [DOI 10.63317/2so5y449gb4w](https://doi.org/10.63317/2so5y449gb4w) · [OpenAlex](https://openalex.org/W7166524751)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
The paper asks how well Whisper preserves interactional material in spontaneous Italian dialogue, where ASR tools often discard short items as noise. The authors focus on backchannels, self- and other-initiated repairs, and filled pauses. They used 26 two-speaker conversations from the KIParla corpus (interviews, student–professor meetings and free talk), and an expert linguist manually annotated these phenomena in INCEpTION. Audio went through the DIT.DaT pipeline, which uses PyAnnote for diarization and Whisper large-v3 for transcription, under four segmentation settings (A–D). The model was kept fixed while Optuna tuned decoding parameters under two objectives: plain WER, and an Interaction-aware variant that rewards keeping target conversational tokens. Results were assessed with global WER and a Mean Match Ratio over annotated events. Neither objective clearly outperformed the other overall. Recognition depended strongly on the phenomenon: Whisper tends to flatten repairs into a single fluent version and often omits brief conversational tokens. This suggests a structural limitation rather than a tuning issue, and it warns Conversation Analysis researchers against relying on WER alone.

## Key points
- **Data:** 26 dialogues from KIParla totalling 15h48m.
  - The first 20 minutes of each were annotated, giving 8h40m tagged with BC, SR, OR and FP labels.
  - The remainder was split into Subset A (3h25m) for decoding optimization and Subset B (3h22m) for a control check.
- **Interaction-aware objective:** it adds deliberately small weights (λ = 0.3, µ = 0.1) that reward correctly produced target tokens and penalize suppressed ones. Target tokens come from a fixed list of forms (e.g., eh, ehm, mh, sì, okay, cioè).
- **Control results on Subset B:** WER was 34.23% for the WER objective and 33.24% for the Interaction-aware one. In both cases, deletions made up about 58% of the alignment outcomes.
- **Frequent substitutions:** the most common was filled pause "eh" transcribed as "e" (about 50 cases). Other typical cases were "mh" or "sì" rendered as "grazie", which points to normalization of conversational tokens.
- **Availability:** data and code are released at github.com/KIParla/say-again, and the DIT.DaT pipeline is also public on GitHub.

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

## Institutions

- [University of Bologna](https://md.research.elamur.ai/free/en/universities/university-of-bologna/) — University, Bologna, Italy · 19 works · 2,067 citations

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## Cite

Cite as: Martina Simonotti, Ludovica Pannitto, Caterina Mauri, Adriano Ferraresi and Gabriele Carioli. 2026. Say Again? The Limits of Whisper with Conversation. A Case Study on the KIParla Corpus. Proceedings of Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC 2026.

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

```bibtex
@inproceedings{simonotti2026say,
  title = {{Say Again? The Limits of Whisper with Conversation. A Case Study on the KIParla Corpus.}},
  author = {Martina Simonotti, Ludovica Pannitto, Caterina Mauri, Adriano Ferraresi and Gabriele Carioli},
  booktitle = {Proceedings of Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC 2026},
  year = {2026},
  doi = {10.63317/2so5y449gb4w},
  url = {https://doi.org/10.63317/2so5y449gb4w}
}
```

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40. Nigel Ward and Wataru Tsukahara. 2000. Tsukahara, w.: Prosodic features which cue backchannel responses in english and japanese. journal of pragmatics 23, 1177-1207. Journal of Pragmatics, 32:1177–1207. [find](https://scholar.google.com/scholar?q=Nigel+Ward+and+Wataru+Tsukahara%2E+2000%2E+Tsukahara%2C+w%2E%3A+Prosodic+features+which+cue+backchannel+responses+in+english+and+japanese%2E+journal+of+pragmatics+23%2C+1177%2D1207%2E+Journal+of+Pragmatics%2C+32%3A1177%E2%80%93120)

*Updated 2 November 2026*