Abstract
Every day, millions of people sacrifice their privacy and browsing habits in exchange for online machine translation. Companies and governments with confidentiality requirements often ban online translation or pay a premium to disable logging. To bring control back to the end user and demonstrate speed, we developed translateLocally. Running locally on a desktop or laptop CPU, translateLocally delivers cloud-like translation speed and quality even on 10 year old hardware. The open-source software is based on Marian and runs on Linux, Windows, and macOS.- Anthology ID:
- 2021.emnlp-demo.20
- Volume:
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Month:
- November
- Year:
- 2021
- Address:
- Online and Punta Cana, Dominican Republic
- Editors:
- Heike Adel, Shuming Shi
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 168–174
- Language:
- URL:
- https://aclanthology.org/2021.emnlp-demo.20
- DOI:
- 10.18653/v1/2021.emnlp-demo.20
- Cite (ACL):
- Nikolay Bogoychev, Jelmer Van der Linde, and Kenneth Heafield. 2021. TranslateLocally: Blazing-fast translation running on the local CPU. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 168–174, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- TranslateLocally: Blazing-fast translation running on the local CPU (Bogoychev et al., EMNLP 2021)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.emnlp-demo.20.pdf