mlsanityData to 7 Oct 2026

"Mm, Wat?" Detecting Other-initiated Repair Requests in Dialogue

arXiv 2510.24628 ↗First posted 28 Oct 2025cs.CLcited by 1

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Abstract (arXiv)

Maintaining mutual understanding is a key component in human-human conversation to avoid conversation breakdowns, in which repair, particularly Other-Initiated Repair (OIR, when one speaker signals trouble and prompts the other to resolve), plays a vital role. However, Conversational Agents (CAs) still fail to recognize user repair initiation, leading to breakdowns or disengagement. This work proposes a multimodal model to automatically detect repair initiation in Dutch dialogues by integrating linguistic and prosodic features grounded in Conversation Analysis. The results show that prosodic cues complement linguistic features and significantly improve the results of pretrained text and audio embeddings, offering insights into how different features interact. Future directions include incorporating visual cues, exploring multilingual and cross-context corpora to assess the robustness and generalizability.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 45 references that are in the map. First posted on arXiv 28 Oct 2025.

Builds on

6 of 45 references.

References · 6

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialoguecited by 185
  3. 2020RobBERT: a Dutch RoBERTa-based Language Modelcited by 88
  4. 2021Feature Synergy, Redundancy, and Independence in Global Model Explanations using SHAP Vector Decompositioncited by 9
  5. 2023No that's not what I meant: Handling Third Position Repair in Conversational Question Answeringcited by 4
  6. 2024Multimodal Contextual Dialogue Breakdown Detection for Conversational AI Modelscited by 1

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