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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

DOI:10.63317/2so5y449gb4w

Abstract

This study investigates how Whisper handles interactional phenomena in spontaneous Italian conversation, focusing on backchannels, repairs, and filled pauses. We compare standard Word Error Rate (WER) optimization with a decoding strategy that explicitly rewards the preservation of interactional events. Results show that decoding choices have limited impact on overall accuracy, while recognition remains strongly phenomenon-dependent, suggesting structural limitations in the handling of interactional phenomena, with systematic linearization of repairs and frequent suppression of short conversational items.

Details

Paper ID
lrec2026-ws-speakable-03
Pages
pp. 16-30
BibKey
simonotti-etal-2026-say
Editors
Nina Hosseini-Kivanani, Alessio Brutti, Marco Matassoni, Sandipana Dowerah, Davide Liga, Christoph Schommer
Publisher
European Language Resources Association (ELRA)
ISSN
N/A
ISBN
N/A
Workshop
Proceedings of Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC 2026
Location
Palma, Mallorca, Spain
Date
11 - 16 May 2026

Authors

  • MS

    Martina Simonotti

  • LP

    Ludovica Pannitto

  • CM

    Caterina Mauri

  • AF

    Adriano Ferraresi

  • GC

    Gabriele Carioli

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