Rapidly Piloting Real-time Linguistic Assistance for Simultaneous Interpreters with Untrained Bilingual Surrogates
Alvin Grissom II, Jo Shoemaker, Ben Goldman, Ruikang Shi, Craig Stewart, C. Anton Rytting, Leah Findlater, Jordan Boyd-Graber
Abstract
Simultaneous interpretation is a cognitively taxing task, and even seasoned professionals benefit from real-time assistance. However, both recruiting professional interpreters and evaluating new assistance techniques are difficult. We present a novel, realistic simultaneous interpretation task that mimics the cognitive load of interpretation with crowdworker surrogates. Our task tests different real-time assistance methods in a Wizard-of-Oz experiment with a large pool of proxy users and compares against professional interpreters. Both professional and proxy participants respond similarly to changes in interpreting conditions, including improvement with two assistance interventions—translation of specific terms and of numbers—compared to a no-assistance control.
BibTeX
@inproceedings{grissom-ii-etal-2024-rapidly,
title = "Rapidly Piloting Real-time Linguistic Assistance for Simultaneous Interpreters with Untrained Bilingual Surrogates",
author = "Grissom II, Alvin and
Shoemaker, Jo and
Goldman, Ben and
Shi, Ruikang and
Stewart, Craig and
Rytting, C. Anton and
Findlater, Leah and
Boyd-Graber, Jordan",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.1185/",
pages = "13548--13556"
}