Speech Translation Systems as a Solution for a Wireless Earpiece

Nicholas Ruiz, Andrew Ochoa, Jainam Shah, William Goethels, Sergio DelRio Diaz


Abstract
The advances of deep learning approaches in automatic speech recognition (ASR) and machine translation (MT) have allowed for levels of accuracy that move speech translation closer to being a commercially viable alternative interpretation solution. In addition, recent improvements in micro-electronic mechanical systems, microphone arrays, speech processing software, and wireless technology have enabled speech recognition software to capture higher quality speech input from wireless earpiece products. With this in mind, we introduce and present a wearable speech translation tool called Pilot, which uses these systems to translate language spoken within the proximity of a user wearing the wireless earpiece.
Anthology ID:
2018.eamt-main.54
Volume:
Proceedings of the 21st Annual Conference of the European Association for Machine Translation
Month:
May
Year:
2018
Address:
Alicante, Spain
Editors:
Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, Miquel Esplà-Gomis, Maja Popović, Celia Rico, André Martins, Joachim Van den Bogaert, Mikel L. Forcada
Venue:
EAMT
SIG:
Publisher:
Note:
Pages:
381
Language:
URL:
https://aclanthology.org/2018.eamt-main.54
DOI:
Bibkey:
Cite (ACL):
Nicholas Ruiz, Andrew Ochoa, Jainam Shah, William Goethels, and Sergio DelRio Diaz. 2018. Speech Translation Systems as a Solution for a Wireless Earpiece. In Proceedings of the 21st Annual Conference of the European Association for Machine Translation, page 381, Alicante, Spain.
Cite (Informal):
Speech Translation Systems as a Solution for a Wireless Earpiece (Ruiz et al., EAMT 2018)
Copy Citation:
PDF:
https://aclanthology.org/2018.eamt-main.54.pdf