Breaking the language barrier: machine assisted diagnosis using the medical speech translator.
In this paper, we describe and evaluate an Open Source medical speech translation system (MedSLT) intended for safety-critical applications. The aim of this system is to eliminate the language barriers in emergency situation. It translates spoken questions from English into French, Japanese and Finnish in three medical subdomains (headache, chest pain and abdominal pain), using a vocabulary of about 250-400 words per sub-domain. The architecture is a compromise between fixed-phrase translation on one hand and complex linguistically-based systems on the other. Recognition is guided by a Context Free Grammar Language Model compiled from a general unification grammar, automatically specialised for the domain. We present an evaluation of this initial prototype that shows the advantages of this grammar-based approach for this particular translation task in term of both reliability and use.
Starlander
Marianne
M
University of Geneva, TIM/ISSCO, Geneva, Switzerland. Marianne.starlander@eti.unige.ch
Bouillon
Pierrette
P
Rayner
Manny
M
Chatzichrisafis
Nikos
N
Hockey
Beth Ann
BA
Isahara
Hitoshi
H
Kanzaki
Kyoko
K
Nakao
Yukie
Y
Santaholma
Marianne
M
D003144:Communication Barriers; D006801:Humans; D007802:Language; D009323:Natural Language Processing; D015203:Reproducibility of Results; D013060:Speech; D014175:Translating