Helping Domain Experts Build Phrasal Speech Translation Systems

Rayner, Manny; Armando, Alejandro; Bouillon, Pierrette; Ebling, Sarah; Gerlach, Johanna; Halimi, Sonia; Strasly, Irène; Tsourakis, Nikos

doi:10.1007/978-3-319-33500-1_4

Cited by 2 publications

(1 citation statement)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular, it is easy to extend it to new target languages and situations in order to follow demographic changes and allow its integration in different services. The content is described efficiently with rules (synchronized grammar [13]) that map multiple synonymous patterns (“variations”) to a sentence expressing the core meaning (“core sentence”). For example, “Do you have a fever?” “Is your temperature high?” and “Have you observed a high temperature?” will all be mapped to the core sentence “Do you have fever?” In addition, patterns with variables (eg, “Is it a QUALITATIVE pain?” “Do you have a QUALITATIVE pain?” etc, where “QUALITATIVE” is a variable that can take multiple values such as “severe” and “dull”) allow the description of content in a productive way.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

Self Cite

View full text Add to dashboard Cite

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. Similar to other fixed-phrase translators (such as Medibabble or UniversalDoctor), it relies on a predefined list of pretranslated sentences, but instead of searching for sentences in this list, doctors can freely ask questions. Objective This study aimed to assess if a translation tool, such as BabelDr, can be used by doctors to perform diagnostic interviews under emergency conditions and to reach a correct diagnosis. In addition, we aimed to observe how doctors interact with the system using text and speech and to investigate if speech is a useful modality in this context. Methods We conducted a crossover study in December 2017 at Geneva University Hospitals with 12 French-speaking doctors (6 doctors working at the outpatient emergency service and 6 general practitioners who also regularly work in this service). They were asked to use the BabelDr tool to diagnose two standardized Arabic-speaking patients (one male and one female). The patients received a priori list of symptoms for the condition they presented with and were instructed to provide a negative or noncommittal answer for all other symptoms during the diagnostic interview. The male patient was standardized for nephritic colic and the female, for cystitis. Doctors used BabelDr as the only means of communication with the patient and were asked to make their diagnosis at the end of the dialogue. The doctors also completed a satisfaction questionnaire. Results All doctors were able to reach the correct diagnosis based on the information collected using BabelDr. They all agreed that the system helped them reach a conclusion, even if one-half felt constrained by the tool and some considered that they could not ask enough questions to reach a diagnosis. Overall, participants used more speech than text, thus confirming that speech is an important functionality in this type of tool. There was a negative association ( P =.02) between the percentage of successful speech interactions (spoken sentences sent for translation) and the number of translated text items, showing that the doctors used more text when they had no success with speech. Conclusions In emergency settings, when no interpreter is available, speech-enabled fixed-phrase translators can be a good alternative to reliably collect information from the patie...

show abstract

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

Migrating from ISO/IEC 9126 to SQUARE

Estrella

Tsourakis

2017

Advances in Healthcare Information Systems and Administration

View full text Add to dashboard Cite

When it comes to the evaluation of natural language systems, it is well acknowledged that there is a lack of common evaluation methodologies, making the fair comparison of such systems a difficult task. Many attempts to standardize this process have used a quality model based on the ISO/IEC 9126 standards. The authors have also used these standards for the definition of a weighted quality model for the evaluation of a medical speech translator, showing the relative importance of the system's features depending on the potential user (patient or doctor, developer). More recently, ISO/IEC 9126 has been replaced by a new series of standards, the 25000 or SQuaRE series, indicating that the model should be migrated to the new series in order to maintain compliance adherence to current standards. This chapter demonstrates how to migrate from ISO/IEC 9126 to ISO 25000 by using the authors' previous work as a use case.

show abstract

Helping Domain Experts Build Phrasal Speech Translation Systems

Cited by 2 publications

References 18 publications

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

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

Migrating from ISO/IEC 9126 to SQUARE

Contact Info

Product

Resources

About