MINTZAISistemas de Aprendizaje Profundo E2E para Traducción Automática del Habla

  1. Thierry Etchegoyhen
  2. Haritz Arzelus
  3. Harritxu Gete
  4. Aitor Alvarez
  5. Inma Hernaez
  6. Eva Navas
  7. Ander González-Docasal
  8. Jaime Osácar
  9. Edson Benites
  10. Igor Ellakuria
  11. Eusebi Calonge
  12. Maite Martin
Journal:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Year of publication: 2020

Issue: 65

Pages: 97-100

Type: Article

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More publications in: Procesamiento del lenguaje natural

Abstract

Speech Translation consists in translating speech in one language into text or speech in a different language. These systems have numerous applications, particularly in multilingual communities such as the European Union. The standard approach in the field involves the chaining of separate components for speech recognition, machine translation and speech synthesis. With the advances made possible by artificial neural networks and Deep Learning, training end-to-end speech translation systems has given rise to intense research and development activities in recent times. In this paper, we review the state of the art and describe project mintzai, which is being carried out in this field.

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