@inproceedings{chen-etal-2026-completing,
    title = "Completing and Validating the Re-Aligned Switchboard Dialog Act Corpus",
    author = "Chen, Run  and
      Tao, Zihao  and
      Prado, John  and
      LaManna, Ignazio  and
      Puterbaugh, Ryan  and
      Datta, Mim  and
      Hirschberg, Julia",
    editor = "Liu, Yang Janet  and
      Gessler, Luke",
    booktitle = "Proceedings of the 20th Linguistic Annotation Workshop ({LAW} {XX})",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.law-main.13/",
    pages = "173--177",
    ISBN = "979-8-89176-404-0",
    abstract = "Although widely used in dialog act prediction and generation, the Switchboard Dialog Act (SwDA) corpus has performed poorly in models incorporating prosodic information because of misalignment between speech and text data. In this paper, we report our completion of the work begun in Chen et al. (2024) in addressing these misalignment issues with an improved SwDA corpus called RASwDA (Re-Aligned Switchboard Dialog Act Corpus). Now fully re-aligned and validated, RASwDA finally meets standards of accuracy allowing for classification models trained on it to exceed classification benchmarks set by models trained on other Switchboard subcorpora."
}