MINTZAI: End-to-end Deep Learning for Speech Translation.

Autor:	Etchegoyhen, Thierry, Arzelus, Haritz, Gete, Harritxu, Alvarez, Aitor, Hernaez, Inma, Navas, Eva, González-Docasal, Ander, Osácar, Jaime, Benites, Edson, Ellakuria, Igor, Calonge, Eusebi, Martin, Maite
Předmět:	DEEP learning MACHINE translating SPEECH synthesis SPEECH perception TRANSLATING & interpreting ARTIFICIAL neural networks SPEECH
Zdroj:	Procesamiento del Lenguaje Natural; Sep2020, Issue 65, p97-100, 4p
Abstrakt:	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. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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