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Conversational Grounding: Annotation and Analysis of Grounding Acts and Grounding Units

Biswesh Mohapatra, Seemab Hassan, Laurent Romary, Justine Cassell

TL;DR

This work presents the annotation of two dialog corpora employing Grounding Acts, Grounding Units, and a measure of their degree of grounding, and provides a baseline model to test the performance of current Language Models in categorizing the grounding acts of the dialogs.

Abstract

Successful conversations often rest on common understanding, where all parties are on the same page about the information being shared. This process, known as conversational grounding, is crucial for building trustworthy dialog systems that can accurately keep track of and recall the shared information. The proficiencies of an agent in grounding the conveyed information significantly contribute to building a reliable dialog system. Despite recent advancements in dialog systems, there exists a noticeable deficit in their grounding capabilities. Traum provided a framework for conversational grounding introducing Grounding Acts and Grounding Units, but substantial progress, especially in the realm of Large Language Models, remains lacking. To bridge this gap, we present the annotation of two dialog corpora employing Grounding Acts, Grounding Units, and a measure of their degree of grounding. We discuss our key findings during the annotation and also provide a baseline model to test the performance of current Language Models in categorizing the grounding acts of the dialogs. Our work aims to provide a useful resource for further research in making conversations with machines better understood and more reliable in natural day-to-day collaborative dialogs.

Conversational Grounding: Annotation and Analysis of Grounding Acts and Grounding Units

TL;DR

This work presents the annotation of two dialog corpora employing Grounding Acts, Grounding Units, and a measure of their degree of grounding, and provides a baseline model to test the performance of current Language Models in categorizing the grounding acts of the dialogs.

Abstract

Successful conversations often rest on common understanding, where all parties are on the same page about the information being shared. This process, known as conversational grounding, is crucial for building trustworthy dialog systems that can accurately keep track of and recall the shared information. The proficiencies of an agent in grounding the conveyed information significantly contribute to building a reliable dialog system. Despite recent advancements in dialog systems, there exists a noticeable deficit in their grounding capabilities. Traum provided a framework for conversational grounding introducing Grounding Acts and Grounding Units, but substantial progress, especially in the realm of Large Language Models, remains lacking. To bridge this gap, we present the annotation of two dialog corpora employing Grounding Acts, Grounding Units, and a measure of their degree of grounding. We discuss our key findings during the annotation and also provide a baseline model to test the performance of current Language Models in categorizing the grounding acts of the dialogs. Our work aims to provide a useful resource for further research in making conversations with machines better understood and more reliable in natural day-to-day collaborative dialogs.
Paper Structure (10 sections, 7 figures, 4 tables)

This paper contains 10 sections, 7 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Grounding Acts and Common Grounding Units
  4. Datasets
  5. Annotation Scheme
  6. Challenges
  7. Analysis
  8. Model
  9. Conclusion
  10. Bibliographical References

Figures (7)

  • Figure 1: Example of Grounding Acts from the 'Spot the Difference' dataset of a particular CGU starting from initiate and grounding with an acknowledgment
  • Figure 2: Annotation of meetup dataset
  • Figure 3: Instance of confusion between Continue and Repair in Spot the Difference dataset
  • Figure 4: Instance of Cancelation of a re-opened CGU leading to grounding
  • Figure 5: Example of disordered dialog in Meetup
  • ...and 2 more figures