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Development of a Speech Translator for Medical Use : A Joint Project Between Geneva University Hospitals and the Faculty of Translation and Interpreting of Geneva University

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Poster

Reference

Development of a Speech Translator for Medical Use : A Joint Project Between Geneva University Hospitals and the Faculty of Translation

and Interpreting of Geneva University

SPECHBACH, Hervé, et al.

SPECHBACH, Hervé, et al. Development of a Speech Translator for Medical Use : A Joint Project Between Geneva University Hospitals and the Faculty of Translation and Interpreting of Geneva University. In: 1ère assemblée de printemps de la Société Suisse de Médecine Interne, Basel (Switzerland), 2016

Available at:

http://archive-ouverte.unige.ch/unige:83844

Disclaimer: layout of this document may differ from the published version.

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Preliminary evaluation Solution

The BabelDr web platform supports translation of spoken clinical dialogues for specific medical situations

Distinctive features

BabelDr is different from Google Translate:

Echoes back system’s understanding of question

Translation based on human translation expertise

Output guaranteed correct if recognition is correct

Easy to add new languages, and distant pairs

 French to Tigrinya

Development of a Speech Translator for Medical Use :

A Joint Project Between Geneva University Hospitals and

the Faculty of Translation and Interpreting of Geneva University

2. Methodology

Speech-to-Speech processing

Key characteristics :

 Limited but highly reliable coverage

 Content determined by HUG’s healthcare professionals

 Domains: abdominal pain, chest pain, headaches

 Target languages: Arabic, Italian, Spanish, Tigrinya

1. Goals

Problem

52% of all patients at HUG are foreign

 12% speak no French

Standard solution: employ human interpreters

 Scarce and expensive

Google Translate not sufficiently reliable

Hervé Spechbach, Sophie Durieux-Paillard Jean-Michel Gaspoz and Patricia Hudelson

Pierrette Bouillon, Emmanuel Rayner and Nikos Tsourakis

3. Results

4. Conclusions

The goal of BabelDr is to develop methods that allow rapid prototyping of medium-vocabulary web-enabled medical speech translators, with particular emphasis on languages spoken by victims of the current European refugee crisis.

Other target languages to be added soon include Farsi, Russian and Albanian.

For more information refer to the project’s web site:

http://babeldr.unige.ch

Dr. Hervé Spechbach.

Herve.Spechbach@hcuge.ch

Prof. Pierrette Bouillon Pierrette.Bouillon@unige.ch

In a medical setting, language barriers can be life-threatening

User: “Where is the pain?”

System: “Can you point with the finger where you feel the pain?”

Web platform

System directly accessible over the web (no installation required)

The user can:

Speak to system, Examine the result, Translate it to the target language

See the history of the questions, Learn the system’s coverage and Change the target language and domain

• Focus: Clinical Communication about Abdominal Pain

• Translation into Spanish, Arabic and Tigrinya.

• 413 questions and instructions.

• 7 million different phrases with a vocabulary of about 1400 words.

• Evaluation of performance based on semantic recognition accuracy.

• 73% of the results judged by two judges as very good or adequate(Cohen kappa:0.84).

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Speech recognition Machine translation

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SGAIM – 2016

Références

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