@inproceedings{baker-etal-2024-speech,
    title = "Speech Accommodation in Health-Care Interactions: Evidence Using a Mixed-Reality Platform",
    author = "Baker, Rose  and
      Bobb, Susan C.  and
      Dowson, Dai{'}Sha  and
      Eanes, Elisha  and
      McNeill, Makyah  and
      Ragsdale, Hannah  and
      Eaves, Audrey  and
      Lee, Joseph G.  and
      Rothermich, Kathrin",
    editor = "Demner-Fushman, Dina  and
      Ananiadou, Sophia  and
      Thompson, Paul  and
      Ondov, Brian",
    booktitle = "Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.cl4health-1.26",
    pages = "215--219",
    abstract = "Many people in the US use more than one language at home, yet English remains the dominant (L1) language in US society, which can complicate medical encounters. In this study we ask in what ways effective communication can be ensured in health care settings when speakers differ in language proficiency. One strategy people use is second language (L2) speech accommodation, which is characterized by slowed speech, less complex words, and clearer enunciation. We employ a mixed-reality platform called MURSION to document how a group of Physician Assistant students use speech accommodation during a healthcare encounter. MURSION is a computer-based virtual environment where participants interact with an Avatar controlled by a human interactor in a standardized environment. We record 5-minute interactions between the student and a high or low English proficiency Avatar. Our analyses evaluate lexical choices in L1-L2 interactions with SCOPE (South Carolina Psycholinguistic Metabase) and acoustic properties with PRAAT. Results show that clinical students use slower speech and high frequency words when speaking to a low proficiency virtual patient, indicating a sensitivity for the communicative needs of L2 English users. Speech accommodation results will contribute to communication training modules for clinicians to interact efficiently with linguistically diverse populations.",
}

Many people in the US use more than one language at home, yet English remains the dominant (L1) language in US society, which can complicate medical encounters. In this study we ask in what ways effective communication can be ensured in health care settings when speakers differ in language proficiency. One strategy people use is second language (L2) speech accommodation, which is characterized by slowed speech, less complex words, and clearer enunciation. We employ a mixed-reality platform called MURSION to document how a group of Physician Assistant students use speech accommodation during a healthcare encounter. MURSION is a computer-based virtual environment where participants interact with an Avatar controlled by a human interactor in a standardized environment. We record 5-minute interactions between the student and a high or low English proficiency Avatar. Our analyses evaluate lexical choices in L1-L2 interactions with SCOPE (South Carolina Psycholinguistic Metabase) and acoustic properties with PRAAT. Results show that clinical students use slower speech and high frequency words when speaking to a low proficiency virtual patient, indicating a sensitivity for the communicative needs of L2 English users. Speech accommodation results will contribute to communication training modules for clinicians to interact efficiently with linguistically diverse populations.
Baker, Rose Bobb, Susan C. Dowson, Dai{'}Sha Eanes, Elisha McNeill, Makyah Ragsdale, Hannah Eaves, Audrey Lee, Joseph G. Rothermich, Kathrin
Speech Accommodation in Health-Care Interactions: Evidence Using a Mixed-Reality Platform