Process Innovation Challenge
Track: Process Innovation Challenge | PIC6 |
Wednesday, January 27, 2021, 2:30pm – 3:15pm
Held in: Stream 2
Rafał Jaworski - XTM International
Simone Perone - Translated
Mahmoud Roshdy - Saudisoft Co. Ltd.
Iti Sahai - Chegg
Konstantin Savenkov - Intento
Kirill Soloviev - ContentQuo
Moderator: Dave Ruane
Hosts: Bert Esselink,
SPONSORED BY: XTM International
The PIC is a platform for innovations and innovators in the localization and translation industry, held during LocWorld conferences. Innovators have a stage to pitch their ideas to peers and experts. The audience will vote for the Process Innovator of the year.
Takeaways: Investors and other interested parties will get to meet innovators in the localization industry and see the latest localization innovations.
Global Product Design
Rethinking (software) product development by integrating localization and global thinking in the design and discovery phase for downstream international efficacy.
Iti Sahai – Procore
Ada in Action: Augmented Quality Risk Management for PEMT
Ada, the virtual quality manager, debuted at the last PIC. Her first REAL job is to help reduce post-editing machine translation (PEMT) cost. Ada continuously monitors how much post-editors correct MT output and helps identify which MT errors to focus on during retraining in order to post-edit faster and pay less.
Kirill Soloviev – ContentQuo
Make Localization a Part of the Experience
Make your design and localization tools talk to each other with a plugin to automate the product localization workflow and integrate the localization effort in the product build.
Anne-Sophie Delafosse – Deliveroo
AI-assisted Subtitles Creation Process
Matesub is a brand-new subtitling tool created to produce higher quality subtitles faster. Thanks to AI, it is able to provide automatic suggestions during the transcription, spotting and translation phases, empowering subtitlers and linguists to concentrate on the most inspiring part of their work: delivering emotions.
Simone Perone – Translated
Augmented MT: Language- and Provider-agnostic Fine-tuning of MT Output
Many machine translation (MT) usage scenarios require controlling specific features of the MT output such as tone of voice, gender, proper noun translation and profanity filtering. We introduce a new component of the MT workflow that provides control of those features in a provider-agnostic fashion for all commercial MT engines, both stock and custom.
Konstantin Savenkov – Intento
Time Efficiency in the Bidi Quality Assurance Process
This innovation is designed to detect bidirectional (bidi) issues and other linguistic errors. It provides time efficiency in the bidi quality assurance process for linguists and project managers.
Mahmoud Roshdy – Saudisoft
AI-driven, Computer-assisted Review: Automatic Highlighting of Potential Translation Errors
Computer-assisted review works by highlighting source sentence terms that do not have a good equivalent in the translation — potential translation errors. This is a requirement now as AI systems like neural machine translation have more widespread usage and play a growing role in producing translations within global content workflows.
Rafał Jaworski – XTM International