Leveraging AI Technologies for Enhanced Multimedia Localization

Ashley Mondello, Sahil Rasane, Alina Karakanta, Laura Casanellas


Abstract
As demand for multilingual video content rises, multimedia localization is becoming crucial for Language Service Providers (LSPs), offering revenue growth and new business opportunities. To cope with labor-intensive multimedia workflows and the rise in client demand for cheaper and faster multimedia localization services, LSPs are starting to leverage advanced AI applications to streamline the localization process. However, workflows and tools adopted by media service providers may not be suitable for LSPs, while the plethora of available solutions makes it hard for LSPs to choose the ones that most effectively optimize their workflows. In this presentation, we assess AI technologies that offer efficiency and cost reduction in the traditionally human-driven workflows of transcription, translation, voice-over (VO), and subtitling with the goal to provide recommendations for LSPs on how to evaluate which tools work best for their processes.
Anthology ID:
2024.amta-presentations.10
Volume:
Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 2: Presentations)
Month:
September
Year:
2024
Address:
Chicago, USA
Editors:
Marianna Martindale, Janice Campbell, Konstantin Savenkov, Shivali Goel
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
145–151
Language:
URL:
https://aclanthology.org/2024.amta-presentations.10
DOI:
Bibkey:
Cite (ACL):
Ashley Mondello, Sahil Rasane, Alina Karakanta, and Laura Casanellas. 2024. Leveraging AI Technologies for Enhanced Multimedia Localization. In Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 2: Presentations), pages 145–151, Chicago, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Leveraging AI Technologies for Enhanced Multimedia Localization (Mondello et al., AMTA 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.amta-presentations.10.pdf