@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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Speech Accommodation in Health-Care Interactions: Evidence Using a Mixed-Reality Platform
%A Baker, Rose
%A Bobb, Susan C.
%A Dowson, Dai’Sha
%A Eanes, Elisha
%A McNeill, Makyah
%A Ragsdale, Hannah
%A Eaves, Audrey
%A Lee, Joseph G.
%A Rothermich, Kathrin
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Thompson, Paul
%Y Ondov, Brian
%S Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F baker-etal-2024-speech
%X 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.
%U https://aclanthology.org/2024.cl4health-1.26
%P 215-219
Markdown (Informal)
[Speech Accommodation in Health-Care Interactions: Evidence Using a Mixed-Reality Platform](https://aclanthology.org/2024.cl4health-1.26) (Baker et al., CL4Health-WS 2024)
ACL
- Rose Baker, Susan C. Bobb, Dai’Sha Dowson, Elisha Eanes, Makyah McNeill, Hannah Ragsdale, Audrey Eaves, Joseph G. Lee, and Kathrin Rothermich. 2024. Speech Accommodation in Health-Care Interactions: Evidence Using a Mixed-Reality Platform. In Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024, pages 215–219, Torino, Italia. ELRA and ICCL.