Machine Assistance in the Real World
Abstract
We have all seen the successes of Machine Assisted captioning, translation, and voiceovers and we have also seen the embarrassing errors of the same engines. Real-life usage, of course, is somewhere between the two. This session will show a couple of real-life examples of Speech To Text (STT), Machine Translation (MT) and Text To Speech (TTS) using Neural voices. We will look at what you would expect to be a perfect candidate for Automatic Speech Recognition (ASR) using multiple commercial engines and then seeing how well they can be transferred to a multiple MT engines. We will also see how its usage in AudioVisual Translation is different from a standard text translation. I will also give a brief demo of how well modern neural voices perform in multiple languages based on input from AVT timed text (vtt) format files.- Anthology ID:
- 2022.amta-upg.6
- Volume:
- Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)
- Month:
- September
- Year:
- 2022
- Address:
- Orlando, USA
- Editors:
- Janice Campbell, Stephen Larocca, Jay Marciano, Konstantin Savenkov, Alex Yanishevsky
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 70–83
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2022.amta-upg.6/
- DOI:
- Cite (ACL):
- Dave Bryant. 2022. Machine Assistance in the Real World. In Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track), pages 70–83, Orlando, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Machine Assistance in the Real World (Bryant, AMTA 2022)