Translating Medical Dialogues into Pictographs: An Approach Using UMLS.

This paper describes a first attempt to map UMLS concepts to pictographs as a resource for translation systems for the medical domain. An evaluation of pictographs from two freely available sets shows that for many concepts no pictograph could be found and that word-based lookup is inadequate for this task.

Communicating in Emergency Settings: BabelDr or Telephone Interpreting?

In this paper, we present a study comparing two mediums that can be used to communicate with allophone patients: a speech-enabled phraselator (BabelDr) and telephone interpreting. To identify the satisfaction provided by these mediums and their pros and cons, we conducted a crossover experiment where doctors and standardized patients completed anamneses and filled in surveys. Our findings suggest that telephone interpreting offers better overall satisfaction, but both mediums presented advantages.

Predicting the Linguistic Accessibility of Chinese Health Translations: Machine Learning Algorithm Development.

Background: Linguistic accessibility has an important impact on the reception and utilization of translated health resources among multicultural and multilingual populations. Linguistic understandability of health translation has been understudied.

Objective: Our study aimed to develop novel machine learning models for the study of the linguistic accessibility of health translations comparing Chinese translations of the World Health Organization health materials with original Chinese health resources developed by the Chinese health authorities.

[I'm having trouble communicating with my patient at the emergency unit: what tools are available ?].

Today's healthcare systems are increasingly confronted with communication problems between allophone patients and health care staff. Geneva, due to its cosmopolitan character, is at the core of this phenomenon. Several studies attest to the negative effects of the language barrier and its consequences on the quality of care, ethics, safety and financial costs.

User Satisfaction with a Speech-Enabled Translator in Emergency Settings.

In medical emergency situations, the language barrier is often a problem for healthcare quality. To face this situation, we developed BabelDr, an innovative and reliable fixed phrase speech-enabled translator specialised for medical language. Majority of participants (>85%) showed a positive satisfaction level using BabelDr.

An Albanian Text-to-Speech System for the BabelDr Medical Speech Translator.

In this paper we present work on creating and evaluating a Text-to-Speech system for the Albanian language to be used in the BabelDr medical speech translation system. Its quality was assessed by twelve native speakers who provided feedback on 60 prompts generated by the synthesizer and on 60 real human recordings across three dimensions, namely comprehensibility, naturalness and likeability. The results suggest that the newly created voice can be incorporated in the content creation pipeline of the BabelDr platform.

A Speech-Enabled Fixed-Phrase Translator for Emergency Settings: Crossover Study.

Background: In the context of the current refugee crisis, emergency services often have to deal with patients who have no language in common with the staff. As interpreters are not always available, especially in emergency settings, medical personnel rely on alternative solutions such as machine translation, which raises reliability and data confidentiality issues, or medical fixed-phrase translators, which sometimes lack usability. A collaboration between Geneva University Hospitals and Geneva University led to the development of BabelDr, a new type of speech-enabled fixed-phrase translator.

Semantic Relations in Compound Nouns: Perspectives from Inter-Annotator Agreement.

Semantic relations have been studied for decades without yet reaching consensus on the set of these relations. However, biomedical language processing and ontologies rely on these relations, so it is important to be able to evaluate their suitability. In this paper we examine the role of inter-annotator agreement in choosing between competing proposals regarding the set of such relations.

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.